[
  {
    "path": "LICENSE",
    "content": "                    GNU GENERAL PUBLIC LICENSE\n                       Version 3, 29 June 2007\n\n Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>\n Everyone is permitted to copy and distribute verbatim copies\n of this license document, but changing it is not allowed.\n\n                            Preamble\n\n  The GNU General Public License is a free, copyleft license for\nsoftware and other kinds of works.\n\n  The licenses for most software and other practical works are designed\nto take away your freedom to share and change the works.  By contrast,\nthe GNU General Public License is intended to guarantee your freedom to\nshare and change all versions of a program--to make sure it remains free\nsoftware for all its users.  We, the Free Software Foundation, use the\nGNU General Public License for most of our software; it applies also to\nany other work released this way by its authors.  You can apply it to\nyour programs, too.\n\n  When we speak of free software, we are referring to freedom, not\nprice.  Our General Public Licenses are designed to make sure that you\nhave the freedom to distribute copies of free software (and charge for\nthem if you wish), that you receive source code or can get it if you\nwant it, that you can change the software or use pieces of it in new\nfree programs, and that you know you can do these things.\n\n  To protect your rights, we need to prevent others from denying you\nthese rights or asking you to surrender the rights.  Therefore, you have\ncertain responsibilities if you distribute copies of the software, or if\nyou modify it: responsibilities to respect the freedom of others.\n\n  For example, if you distribute copies of such a program, whether\ngratis or for a fee, you must pass on to the recipients the same\nfreedoms that you received.  You must make sure that they, too, receive\nor can get the source code.  And you must show them these terms so they\nknow their rights.\n\n  Developers that use the GNU GPL protect your rights with two steps:\n(1) assert copyright on the software, and (2) offer you this License\ngiving you legal permission to copy, distribute and/or modify it.\n\n  For the developers' and authors' protection, the GPL clearly explains\nthat there is no warranty for this free software.  For both users' and\nauthors' sake, the GPL requires that modified versions be marked as\nchanged, so that their problems will not be attributed erroneously to\nauthors of previous versions.\n\n  Some devices are designed to deny users access to install or run\nmodified versions of the software inside them, although the manufacturer\ncan do so.  This is fundamentally incompatible with the aim of\nprotecting users' freedom to change the software.  The systematic\npattern of such abuse occurs in the area of products for individuals to\nuse, which is precisely where it is most unacceptable.  Therefore, we\nhave designed this version of the GPL to prohibit the practice for those\nproducts.  If such problems arise substantially in other domains, we\nstand ready to extend this provision to those domains in future versions\nof the GPL, as needed to protect the freedom of users.\n\n  Finally, every program is threatened constantly by software patents.\nStates should not allow patents to restrict development and use of\nsoftware on general-purpose computers, but in those that do, we wish to\navoid the special danger that patents applied to a free program could\nmake it effectively proprietary.  To prevent this, the GPL assures that\npatents cannot be used to render the program non-free.\n\n  The precise terms and conditions for copying, distribution and\nmodification follow.\n\n                       TERMS AND CONDITIONS\n\n  0. Definitions.\n\n  \"This License\" refers to version 3 of the GNU General Public License.\n\n  \"Copyright\" also means copyright-like laws that apply to other kinds of\nworks, such as semiconductor masks.\n\n  \"The Program\" refers to any copyrightable work licensed under this\nLicense.  Each licensee is addressed as \"you\".  \"Licensees\" and\n\"recipients\" may be individuals or organizations.\n\n  To \"modify\" a work means to copy from or adapt all or part of the work\nin a fashion requiring copyright permission, other than the making of an\nexact copy.  The resulting work is called a \"modified version\" of the\nearlier work or a work \"based on\" the earlier work.\n\n  A \"covered work\" means either the unmodified Program or a work based\non the Program.\n\n  To \"propagate\" a work means to do anything with it that, without\npermission, would make you directly or secondarily liable for\ninfringement under applicable copyright law, except executing it on a\ncomputer or modifying a private copy.  Propagation includes copying,\ndistribution (with or without modification), making available to the\npublic, and in some countries other activities as well.\n\n  To \"convey\" a work means any kind of propagation that enables other\nparties to make or receive copies.  Mere interaction with a user through\na computer network, with no transfer of a copy, is not conveying.\n\n  An interactive user interface displays \"Appropriate Legal Notices\"\nto the extent that it includes a convenient and prominently visible\nfeature that (1) displays an appropriate copyright notice, and (2)\ntells the user that there is no warranty for the work (except to the\nextent that warranties are provided), that licensees may convey the\nwork under this License, and how to view a copy of this License.  If\nthe interface presents a list of user commands or options, such as a\nmenu, a prominent item in the list meets this criterion.\n\n  1. Source Code.\n\n  The \"source code\" for a work means the preferred form of the work\nfor making modifications to it.  \"Object code\" means any non-source\nform of a work.\n\n  A \"Standard Interface\" means an interface that either is an official\nstandard defined by a recognized standards body, or, in the case of\ninterfaces specified for a particular programming language, one that\nis widely used among developers working in that language.\n\n  The \"System Libraries\" of an executable work include anything, other\nthan the work as a whole, that (a) is included in the normal form of\npackaging a Major Component, but which is not part of that Major\nComponent, and (b) serves only to enable use of the work with that\nMajor Component, or to implement a Standard Interface for which an\nimplementation is available to the public in source code form.  A\n\"Major Component\", in this context, means a major essential component\n(kernel, window system, and so on) of the specific operating system\n(if any) on which the executable work runs, or a compiler used to\nproduce the work, or an object code interpreter used to run it.\n\n  The \"Corresponding Source\" for a work in object code form means all\nthe source code needed to generate, install, and (for an executable\nwork) run the object code and to modify the work, including scripts to\ncontrol those activities.  However, it does not include the work's\nSystem Libraries, or general-purpose tools or generally available free\nprograms which are used unmodified in performing those activities but\nwhich are not part of the work.  For example, Corresponding Source\nincludes interface definition files associated with source files for\nthe work, and the source code for shared libraries and dynamically\nlinked subprograms that the work is specifically designed to require,\nsuch as by intimate data communication or control flow between those\nsubprograms and other parts of the work.\n\n  The Corresponding Source need not include anything that users\ncan regenerate automatically from other parts of the Corresponding\nSource.\n\n  The Corresponding Source for a work in source code form is that\nsame work.\n\n  2. Basic Permissions.\n\n  All rights granted under this License are granted for the term of\ncopyright on the Program, and are irrevocable provided the stated\nconditions are met.  This License explicitly affirms your unlimited\npermission to run the unmodified Program.  The output from running a\ncovered work is covered by this License only if the output, given its\ncontent, constitutes a covered work.  This License acknowledges your\nrights of fair use or other equivalent, as provided by copyright law.\n\n  You may make, run and propagate covered works that you do not\nconvey, without conditions so long as your license otherwise remains\nin force.  You may convey covered works to others for the sole purpose\nof having them make modifications exclusively for you, or provide you\nwith facilities for running those works, provided that you comply with\nthe terms of this License in conveying all material for which you do\nnot control copyright.  Those thus making or running the covered works\nfor you must do so exclusively on your behalf, under your direction\nand control, on terms that prohibit them from making any copies of\nyour copyrighted material outside their relationship with you.\n\n  Conveying under any other circumstances is permitted solely under\nthe conditions stated below.  Sublicensing is not allowed; section 10\nmakes it unnecessary.\n\n  3. Protecting Users' Legal Rights From Anti-Circumvention Law.\n\n  No covered work shall be deemed part of an effective technological\nmeasure under any applicable law fulfilling obligations under article\n11 of the WIPO copyright treaty adopted on 20 December 1996, or\nsimilar laws prohibiting or restricting circumvention of such\nmeasures.\n\n  When you convey a covered work, you waive any legal power to forbid\ncircumvention of technological measures to the extent such circumvention\nis effected by exercising rights under this License with respect to\nthe covered work, and you disclaim any intention to limit operation or\nmodification of the work as a means of enforcing, against the work's\nusers, your or third parties' legal rights to forbid circumvention of\ntechnological measures.\n\n  4. Conveying Verbatim Copies.\n\n  You may convey verbatim copies of the Program's source code as you\nreceive it, in any medium, provided that you conspicuously and\nappropriately publish on each copy an appropriate copyright notice;\nkeep intact all notices stating that this License and any\nnon-permissive terms added in accord with section 7 apply to the code;\nkeep intact all notices of the absence of any warranty; and give all\nrecipients a copy of this License along with the Program.\n\n  You may charge any price or no price for each copy that you convey,\nand you may offer support or warranty protection for a fee.\n\n  5. Conveying Modified Source Versions.\n\n  You may convey a work based on the Program, or the modifications to\nproduce it from the Program, in the form of source code under the\nterms of section 4, provided that you also meet all of these conditions:\n\n    a) The work must carry prominent notices stating that you modified\n    it, and giving a relevant date.\n\n    b) The work must carry prominent notices stating that it is\n    released under this License and any conditions added under section\n    7.  This requirement modifies the requirement in section 4 to\n    \"keep intact all notices\".\n\n    c) You must license the entire work, as a whole, under this\n    License to anyone who comes into possession of a copy.  This\n    License will therefore apply, along with any applicable section 7\n    additional terms, to the whole of the work, and all its parts,\n    regardless of how they are packaged.  This License gives no\n    permission to license the work in any other way, but it does not\n    invalidate such permission if you have separately received it.\n\n    d) If the work has interactive user interfaces, each must display\n    Appropriate Legal Notices; however, if the Program has interactive\n    interfaces that do not display Appropriate Legal Notices, your\n    work need not make them do so.\n\n  A compilation of a covered work with other separate and independent\nworks, which are not by their nature extensions of the covered work,\nand which are not combined with it such as to form a larger program,\nin or on a volume of a storage or distribution medium, is called an\n\"aggregate\" if the compilation and its resulting copyright are not\nused to limit the access or legal rights of the compilation's users\nbeyond what the individual works permit.  Inclusion of a covered work\nin an aggregate does not cause this License to apply to the other\nparts of the aggregate.\n\n  6. Conveying Non-Source Forms.\n\n  You may convey a covered work in object code form under the terms\nof sections 4 and 5, provided that you also convey the\nmachine-readable Corresponding Source under the terms of this License,\nin one of these ways:\n\n    a) Convey the object code in, or embodied in, a physical product\n    (including a physical distribution medium), accompanied by the\n    Corresponding Source fixed on a durable physical medium\n    customarily used for software interchange.\n\n    b) Convey the object code in, or embodied in, a physical product\n    (including a physical distribution medium), accompanied by a\n    written offer, valid for at least three years and valid for as\n    long as you offer spare parts or customer support for that product\n    model, to give anyone who possesses the object code either (1) a\n    copy of the Corresponding Source for all the software in the\n    product that is covered by this License, on a durable physical\n    medium customarily used for software interchange, for a price no\n    more than your reasonable cost of physically performing this\n    conveying of source, or (2) access to copy the\n    Corresponding Source from a network server at no charge.\n\n    c) Convey individual copies of the object code with a copy of the\n    written offer to provide the Corresponding Source.  This\n    alternative is allowed only occasionally and noncommercially, and\n    only if you received the object code with such an offer, in accord\n    with subsection 6b.\n\n    d) Convey the object code by offering access from a designated\n    place (gratis or for a charge), and offer equivalent access to the\n    Corresponding Source in the same way through the same place at no\n    further charge.  You need not require recipients to copy the\n    Corresponding Source along with the object code.  If the place to\n    copy the object code is a network server, the Corresponding Source\n    may be on a different server (operated by you or a third party)\n    that supports equivalent copying facilities, provided you maintain\n    clear directions next to the object code saying where to find the\n    Corresponding Source.  Regardless of what server hosts the\n    Corresponding Source, you remain obligated to ensure that it is\n    available for as long as needed to satisfy these requirements.\n\n    e) Convey the object code using peer-to-peer transmission, provided\n    you inform other peers where the object code and Corresponding\n    Source of the work are being offered to the general public at no\n    charge under subsection 6d.\n\n  A separable portion of the object code, whose source code is excluded\nfrom the Corresponding Source as a System Library, need not be\nincluded in conveying the object code work.\n\n  A \"User Product\" is either (1) a \"consumer product\", which means any\ntangible personal property which is normally used for personal, family,\nor household purposes, or (2) anything designed or sold for incorporation\ninto a dwelling.  In determining whether a product is a consumer product,\ndoubtful cases shall be resolved in favor of coverage.  For a particular\nproduct received by a particular user, \"normally used\" refers to a\ntypical or common use of that class of product, regardless of the status\nof the particular user or of the way in which the particular user\nactually uses, or expects or is expected to use, the product.  A product\nis a consumer product regardless of whether the product has substantial\ncommercial, industrial or non-consumer uses, unless such uses represent\nthe only significant mode of use of the product.\n\n  \"Installation Information\" for a User Product means any methods,\nprocedures, authorization keys, or other information required to install\nand execute modified versions of a covered work in that User Product from\na modified version of its Corresponding Source.  The information must\nsuffice to ensure that the continued functioning of the modified object\ncode is in no case prevented or interfered with solely because\nmodification has been made.\n\n  If you convey an object code work under this section in, or with, or\nspecifically for use in, a User Product, and the conveying occurs as\npart of a transaction in which the right of possession and use of the\nUser Product is transferred to the recipient in perpetuity or for a\nfixed term (regardless of how the transaction is characterized), the\nCorresponding Source conveyed under this section must be accompanied\nby the Installation Information.  But this requirement does not apply\nif neither you nor any third party retains the ability to install\nmodified object code on the User Product (for example, the work has\nbeen installed in ROM).\n\n  The requirement to provide Installation Information does not include a\nrequirement to continue to provide support service, warranty, or updates\nfor a work that has been modified or installed by the recipient, or for\nthe User Product in which it has been modified or installed.  Access to a\nnetwork may be denied when the modification itself materially and\nadversely affects the operation of the network or violates the rules and\nprotocols for communication across the network.\n\n  Corresponding Source conveyed, and Installation Information provided,\nin accord with this section must be in a format that is publicly\ndocumented (and with an implementation available to the public in\nsource code form), and must require no special password or key for\nunpacking, reading or copying.\n\n  7. Additional Terms.\n\n  \"Additional permissions\" are terms that supplement the terms of this\nLicense by making exceptions from one or more of its conditions.\nAdditional permissions that are applicable to the entire Program shall\nbe treated as though they were included in this License, to the extent\nthat they are valid under applicable law.  If additional permissions\napply only to part of the Program, that part may be used separately\nunder those permissions, but the entire Program remains governed by\nthis License without regard to the additional permissions.\n\n  When you convey a copy of a covered work, you may at your option\nremove any additional permissions from that copy, or from any part of\nit.  (Additional permissions may be written to require their own\nremoval in certain cases when you modify the work.)  You may place\nadditional permissions on material, added by you to a covered work,\nfor which you have or can give appropriate copyright permission.\n\n  Notwithstanding any other provision of this License, for material you\nadd to a covered work, you may (if authorized by the copyright holders of\nthat material) supplement the terms of this License with terms:\n\n    a) Disclaiming warranty or limiting liability differently from the\n    terms of sections 15 and 16 of this License; or\n\n    b) Requiring preservation of specified reasonable legal notices or\n    author attributions in that material or in the Appropriate Legal\n    Notices displayed by works containing it; or\n\n    c) Prohibiting misrepresentation of the origin of that material, or\n    requiring that modified versions of such material be marked in\n    reasonable ways as different from the original version; or\n\n    d) Limiting the use for publicity purposes of names of licensors or\n    authors of the material; or\n\n    e) Declining to grant rights under trademark law for use of some\n    trade names, trademarks, or service marks; or\n\n    f) Requiring indemnification of licensors and authors of that\n    material by anyone who conveys the material (or modified versions of\n    it) with contractual assumptions of liability to the recipient, for\n    any liability that these contractual assumptions directly impose on\n    those licensors and authors.\n\n  All other non-permissive additional terms are considered \"further\nrestrictions\" within the meaning of section 10.  If the Program as you\nreceived it, or any part of it, contains a notice stating that it is\ngoverned by this License along with a term that is a further\nrestriction, you may remove that term.  If a license document contains\na further restriction but permits relicensing or conveying under this\nLicense, you may add to a covered work material governed by the terms\nof that license document, provided that the further restriction does\nnot survive such relicensing or conveying.\n\n  If you add terms to a covered work in accord with this section, you\nmust place, in the relevant source files, a statement of the\nadditional terms that apply to those files, or a notice indicating\nwhere to find the applicable terms.\n\n  Additional terms, permissive or non-permissive, may be stated in the\nform of a separately written license, or stated as exceptions;\nthe above requirements apply either way.\n\n  8. Termination.\n\n  You may not propagate or modify a covered work except as expressly\nprovided under this License.  Any attempt otherwise to propagate or\nmodify it is void, and will automatically terminate your rights under\nthis License (including any patent licenses granted under the third\nparagraph of section 11).\n\n  However, if you cease all violation of this License, then your\nlicense from a particular copyright holder is reinstated (a)\nprovisionally, unless and until the copyright holder explicitly and\nfinally terminates your license, and (b) permanently, if the copyright\nholder fails to notify you of the violation by some reasonable means\nprior to 60 days after the cessation.\n\n  Moreover, your license from a particular copyright holder is\nreinstated permanently if the copyright holder notifies you of the\nviolation by some reasonable means, this is the first time you have\nreceived notice of violation of this License (for any work) from that\ncopyright holder, and you cure the violation prior to 30 days after\nyour receipt of the notice.\n\n  Termination of your rights under this section does not terminate the\nlicenses of parties who have received copies or rights from you under\nthis License.  If your rights have been terminated and not permanently\nreinstated, you do not qualify to receive new licenses for the same\nmaterial under section 10.\n\n  9. Acceptance Not Required for Having Copies.\n\n  You are not required to accept this License in order to receive or\nrun a copy of the Program.  Ancillary propagation of a covered work\noccurring solely as a consequence of using peer-to-peer transmission\nto receive a copy likewise does not require acceptance.  However,\nnothing other than this License grants you permission to propagate or\nmodify any covered work.  These actions infringe copyright if you do\nnot accept this License.  Therefore, by modifying or propagating a\ncovered work, you indicate your acceptance of this License to do so.\n\n  10. Automatic Licensing of Downstream Recipients.\n\n  Each time you convey a covered work, the recipient automatically\nreceives a license from the original licensors, to run, modify and\npropagate that work, subject to this License.  You are not responsible\nfor enforcing compliance by third parties with this License.\n\n  An \"entity transaction\" is a transaction transferring control of an\norganization, or substantially all assets of one, or subdividing an\norganization, or merging organizations.  If propagation of a covered\nwork results from an entity transaction, each party to that\ntransaction who receives a copy of the work also receives whatever\nlicenses to the work the party's predecessor in interest had or could\ngive under the previous paragraph, plus a right to possession of the\nCorresponding Source of the work from the predecessor in interest, if\nthe predecessor has it or can get it with reasonable efforts.\n\n  You may not impose any further restrictions on the exercise of the\nrights granted or affirmed under this License.  For example, you may\nnot impose a license fee, royalty, or other charge for exercise of\nrights granted under this License, and you may not initiate litigation\n(including a cross-claim or counterclaim in a lawsuit) alleging that\nany patent claim is infringed by making, using, selling, offering for\nsale, or importing the Program or any portion of it.\n\n  11. Patents.\n\n  A \"contributor\" is a copyright holder who authorizes use under this\nLicense of the Program or a work on which the Program is based.  The\nwork thus licensed is called the contributor's \"contributor version\".\n\n  A contributor's \"essential patent claims\" are all patent claims\nowned or controlled by the contributor, whether already acquired or\nhereafter acquired, that would be infringed by some manner, permitted\nby this License, of making, using, or selling its contributor version,\nbut do not include claims that would be infringed only as a\nconsequence of further modification of the contributor version.  For\npurposes of this definition, \"control\" includes the right to grant\npatent sublicenses in a manner consistent with the requirements of\nthis License.\n\n  Each contributor grants you a non-exclusive, worldwide, royalty-free\npatent license under the contributor's essential patent claims, to\nmake, use, sell, offer for sale, import and otherwise run, modify and\npropagate the contents of its contributor version.\n\n  In the following three paragraphs, a \"patent license\" is any express\nagreement or commitment, however denominated, not to enforce a patent\n(such as an express permission to practice a patent or covenant not to\nsue for patent infringement).  To \"grant\" such a patent license to a\nparty means to make such an agreement or commitment not to enforce a\npatent against the party.\n\n  If you convey a covered work, knowingly relying on a patent license,\nand the Corresponding Source of the work is not available for anyone\nto copy, free of charge and under the terms of this License, through a\npublicly available network server or other readily accessible means,\nthen you must either (1) cause the Corresponding Source to be so\navailable, or (2) arrange to deprive yourself of the benefit of the\npatent license for this particular work, or (3) arrange, in a manner\nconsistent with the requirements of this License, to extend the patent\nlicense to downstream recipients.  \"Knowingly relying\" means you have\nactual knowledge that, but for the patent license, your conveying the\ncovered work in a country, or your recipient's use of the covered work\nin a country, would infringe one or more identifiable patents in that\ncountry that you have reason to believe are valid.\n\n  If, pursuant to or in connection with a single transaction or\narrangement, you convey, or propagate by procuring conveyance of, a\ncovered work, and grant a patent license to some of the parties\nreceiving the covered work authorizing them to use, propagate, modify\nor convey a specific copy of the covered work, then the patent license\nyou grant is automatically extended to all recipients of the covered\nwork and works based on it.\n\n  A patent license is \"discriminatory\" if it does not include within\nthe scope of its coverage, prohibits the exercise of, or is\nconditioned on the non-exercise of one or more of the rights that are\nspecifically granted under this License.  You may not convey a covered\nwork if you are a party to an arrangement with a third party that is\nin the business of distributing software, under which you make payment\nto the third party based on the extent of your activity of conveying\nthe work, and under which the third party grants, to any of the\nparties who would receive the covered work from you, a discriminatory\npatent license (a) in connection with copies of the covered work\nconveyed by you (or copies made from those copies), or (b) primarily\nfor and in connection with specific products or compilations that\ncontain the covered work, unless you entered into that arrangement,\nor that patent license was granted, prior to 28 March 2007.\n\n  Nothing in this License shall be construed as excluding or limiting\nany implied license or other defenses to infringement that may\notherwise be available to you under applicable patent law.\n\n  12. No Surrender of Others' Freedom.\n\n  If conditions are imposed on you (whether by court order, agreement or\notherwise) that contradict the conditions of this License, they do not\nexcuse you from the conditions of this License.  If you cannot convey a\ncovered work so as to satisfy simultaneously your obligations under this\nLicense and any other pertinent obligations, then as a consequence you may\nnot convey it at all.  For example, if you agree to terms that obligate you\nto collect a royalty for further conveying from those to whom you convey\nthe Program, the only way you could satisfy both those terms and this\nLicense would be to refrain entirely from conveying the Program.\n\n  13. Use with the GNU Affero General Public License.\n\n  Notwithstanding any other provision of this License, you have\npermission to link or combine any covered work with a work licensed\nunder version 3 of the GNU Affero General Public License into a single\ncombined work, and to convey the resulting work.  The terms of this\nLicense will continue to apply to the part which is the covered work,\nbut the special requirements of the GNU Affero General Public License,\nsection 13, concerning interaction through a network will apply to the\ncombination as such.\n\n  14. Revised Versions of this License.\n\n  The Free Software Foundation may publish revised and/or new versions of\nthe GNU General Public License from time to time.  Such new versions will\nbe similar in spirit to the present version, but may differ in detail to\naddress new problems or concerns.\n\n  Each version is given a distinguishing version number.  If the\nProgram specifies that a certain numbered version of the GNU General\nPublic License \"or any later version\" applies to it, you have the\noption of following the terms and conditions either of that numbered\nversion or of any later version published by the Free Software\nFoundation.  If the Program does not specify a version number of the\nGNU General Public License, you may choose any version ever published\nby the Free Software Foundation.\n\n  If the Program specifies that a proxy can decide which future\nversions of the GNU General Public License can be used, that proxy's\npublic statement of acceptance of a version permanently authorizes you\nto choose that version for the Program.\n\n  Later license versions may give you additional or different\npermissions.  However, no additional obligations are imposed on any\nauthor or copyright holder as a result of your choosing to follow a\nlater version.\n\n  15. Disclaimer of Warranty.\n\n  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY\nAPPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT\nHOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM \"AS IS\" WITHOUT WARRANTY\nOF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,\nTHE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR\nPURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM\nIS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF\nALL NECESSARY SERVICING, REPAIR OR CORRECTION.\n\n  16. Limitation of Liability.\n\n  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING\nWILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS\nTHE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY\nGENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE\nUSE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF\nDATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD\nPARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),\nEVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF\nSUCH DAMAGES.\n\n  17. Interpretation of Sections 15 and 16.\n\n  If the disclaimer of warranty and limitation of liability provided\nabove cannot be given local legal effect according to their terms,\nreviewing courts shall apply local law that most closely approximates\nan absolute waiver of all civil liability in connection with the\nProgram, unless a warranty or assumption of liability accompanies a\ncopy of the Program in return for a fee.\n\n                     END OF TERMS AND CONDITIONS\n\n            How to Apply These Terms to Your New Programs\n\n  If you develop a new program, and you want it to be of the greatest\npossible use to the public, the best way to achieve this is to make it\nfree software which everyone can redistribute and change under these terms.\n\n  To do so, attach the following notices to the program.  It is safest\nto attach them to the start of each source file to most effectively\nstate the exclusion of warranty; and each file should have at least\nthe \"copyright\" line and a pointer to where the full notice is found.\n\n    <one line to give the program's name and a brief idea of what it does.>\n    Copyright (C) <year>  <name of author>\n\n    This program is free software: you can redistribute it and/or modify\n    it under the terms of the GNU General Public License as published by\n    the Free Software Foundation, either version 3 of the License, or\n    (at your option) any later version.\n\n    This program is distributed in the hope that it will be useful,\n    but WITHOUT ANY WARRANTY; without even the implied warranty of\n    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n    GNU General Public License for more details.\n\n    You should have received a copy of the GNU General Public License\n    along with this program.  If not, see <http://www.gnu.org/licenses/>.\n\nAlso add information on how to contact you by electronic and paper mail.\n\n  If the program does terminal interaction, make it output a short\nnotice like this when it starts in an interactive mode:\n\n    <program>  Copyright (C) <year>  <name of author>\n    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.\n    This is free software, and you are welcome to redistribute it\n    under certain conditions; type `show c' for details.\n\nThe hypothetical commands `show w' and `show c' should show the appropriate\nparts of the General Public License.  Of course, your program's commands\nmight be different; for a GUI interface, you would use an \"about box\".\n\n  You should also get your employer (if you work as a programmer) or school,\nif any, to sign a \"copyright disclaimer\" for the program, if necessary.\nFor more information on this, and how to apply and follow the GNU GPL, see\n<http://www.gnu.org/licenses/>.\n\n  The GNU General Public License does not permit incorporating your program\ninto proprietary programs.  If your program is a subroutine library, you\nmay consider it more useful to permit linking proprietary applications with\nthe library.  If this is what you want to do, use the GNU Lesser General\nPublic License instead of this License.  But first, please read\n<http://www.gnu.org/philosophy/why-not-lgpl.html>.\n"
  },
  {
    "path": "Main.cpp",
    "content": "#include <opencv2/opencv.hpp>\n#include \"NT.h\"\n#include \"StrCommon.h\"\n\nNT *_tt = NULL;\n\n\nvoid DrawData(cv::Mat mm, cv::Mat frame, const std::map<int, DSResult> &map, \n\t\tconst std::vector<cv::Rect> &outRcs,\n\t\tbool detect){\n\tstd::map<int, DSResult>::const_iterator it;\n\tfor(it = map.begin(); it != map.end(); ++it){\n\t\tCvScalar clr = cvScalar(0, 255, 0);\n\t\tcv::Rect rc = it->second.rc_;\n    \t\tcv::rectangle(frame, rc, clr);\n\t\tstd::string disp = toStr(it->first);\n\t\tcv::putText(frame, \n\t\t\tdisp, \n\t\t\tcvPoint(rc.x, rc.y), \n\t\t\tCV_FONT_HERSHEY_SIMPLEX, \n\t\t\t0.6, \n\t\t\tcv::Scalar(0, 0, 255));\n\t}\n\t//\n\tCvScalar clr = cvScalar(0, 0, 255);\n\tfor(cv::Rect rc:outRcs){\n\t\tcv::rectangle(mm, rc, clr);\t\n\t\tif(detect){\n\t\t\tstd::string disp = \"detect\";\n\t\t\tcv::putText(frame, \n\t\t\t\tdisp, \n\t\t\t\tcvPoint(100, 100), \n\t\t\t\tCV_FONT_HERSHEY_SIMPLEX, \n\t\t\t\t1, \n\t\t\t\tcv::Scalar(0, 0, 255));\n\t\t}\n\t}\n}\n\n\nvoid ReadFileContent(const std::string &file, std::string &content){\n\tFILE *fl = fopen(file.c_str(), \"rb\");\n\tif(fl == NULL){\n\t\treturn;\n\t}\n\tfseek(fl, 0, SEEK_END);\n\tint len = ftell(fl);\n\tif(len <= 0){\n\t\treturn;\n\t}\n\tfseek(fl, 0, SEEK_SET);\n\tchar *buf = new char[len+1];\n\tmemset(buf, 0, len+1);\n\tfread(buf, 1, len, fl);\n\tcontent = std::string(buf);\n\tdelete []buf;\n\tfclose(fl);\n}\n\nstd::map<int, std::vector<cv::Rect>> _rcMap;\nvoid ReadRcFileTotal(const std::string &file) {\n\tstd::string content = \"\";\n\tReadFileContent(file, content);\n\n\n\tstd::vector<std::string> lines;\n\tsplitStr(content, \"\\n\", lines);\n\tstd::vector<cv::Rect> rcs;\n\tint num = -1;\n\tint tmpNum = -1;\n\tfor (int i = 0; i < lines.size(); i++) {\n\t\tstd::vector<std::string> cols;\n\t\tsplitStr(lines[i], \",\", cols);\n\t\tif (cols.size() < 6) {\n\t\t\tcontinue;\n\t\t}\n\t\ttmpNum = toInt(trim(cols[0]));\n\t\tif (num!=-1 && tmpNum!=num) {\n\t\t\t_rcMap.insert(std::make_pair(num, rcs));\n\t\t\trcs.clear();\n\t\t\tnum = tmpNum;\n\t\t}\n\t\tif (num == -1) {\n\t\t\tnum = tmpNum;\n\t\t}\n\t\tcv::Rect rc;\n\t\trc.x = toInt(trim(cols[2]));\n\t\trc.y = toInt(trim(cols[3]));\n\t\trc.width = toInt(trim(cols[4]));\n\t\trc.height = toInt(trim(cols[5]));\n\t\trcs.push_back(rc);\n\t}\n\tif (!rcs.empty()) {\n\t\t_rcMap.insert(std::make_pair(tmpNum, rcs));\n\t}\n}\nstd::string _rcFile = \"\";\nstd::string _imgDir;\ncv::VideoWriter *_vw = NULL;\nbool _isShow = false;\nint _imgCount = 0;\n\nvoid CB(cv::Mat &frame, int num){\n\tif (_vw == NULL) {\n\t\t_vw = new cv::VideoWriter(\"out.avi\", CV_FOURCC('M', 'J', 'P', 'G'), 25.0, cv::Size(frame.cols, frame.rows));\n\t}\n\tif (_rcMap.empty()) {\n\t\tReadRcFileTotal(_rcFile);\n\t}\n\tstd::vector<cv::Rect> rcs;\n\tstd::map<int, std::vector<cv::Rect>>::iterator it = _rcMap.find(num);\n\tif (it != _rcMap.end()) {\n\t\trcs = it->second;\n\t}\n\tstd::vector<cv::Rect> outRcs;\n\t\n\tint64_t tm0 = gtm();\n\tstd::map<int, DSResult> map = _tt->UpdateAndGet(frame, rcs, num, outRcs);\n\tint64_t tm1 = gtm();\n\tMat mm = frame.clone();\n\tbool detect = (!rcs.empty());\n\tDrawData(mm, frame, map, outRcs, detect);\n\tprintf(\"finish %d frame, updatecasttime:%ld\\n\", num, tm1-tm0);\n\t//(*_vw) << frame;\n\tif(_isShow){\n\t\tstd::string disp = \"frame\";\n\t\tcv::resize(mm, mm, cv::Size(mm.cols/2, mm.rows/2));\n\t\tcv::resize(frame, frame, cv::Size(frame.cols/2, frame.rows/2));\n\t\tcv::imshow(\"mm\", mm);\n\t\tcv::imshow(disp, frame);\n\t\tcv::waitKey(1);\n\t}\n}\n\nvoid Go() {\n\tstd::string root = _imgDir;\n\tfor (int i = 1; i < _imgCount; i++) {\n\t\tstd::string path = root;\n\t\tpath += to6dStr(i);\n\t\tpath += \".jpg\";\n\t\tcv::Mat mat = cv::imread(path);\n\t\tCB(mat, i);\n\t}\n\n}\n\nint main(int argc, char **argv){\n\tif (argc < 2) {\n\t\tprintf(\"usage:\\n./tt showornot(0/1)\\n\");\n\t\treturn 0;\n\t}\n\t_isShow = toInt(argv[1]);\n\t_tt = new NT();\n\tif(!_tt->Init()){\n\t\treturn 0;\n\t}\n\n\t//_imgDir = \"e:/code/deep_sort-master/MOT16/tt/xyz/img1/\";\n\t//_rcFile = \"e:/code/deep_sort-master/MOT16/tt/xyz/det/det.txt\";\n\t_imgDir = \"/home/xyz/code1/xyz/img1/\";\n\t_rcFile = \"/home/xyz/code1/xyz/det/det.txt\";\n\t//_rcFile = \"/home/xyz/code/test/pp/FaceNumGetter/out/102.txt\";\n\n\n\t//_imgDir = \"/home/xyz/code1/GEP/FrameBuffer/imglog/img1/\";\n\t//_rcFile = \"/home/xyz/code1/GEP/FrameBuffer/imglog/det/det.txt\";\n\t_imgCount = 650;// 2001;// 750;// 680;\n\tGo();\n\treturn 0;\n}\n"
  },
  {
    "path": "NT.cpp",
    "content": "#include \"NT.h\"\n\n//#define UDL\n#ifdef UDL\n\t//#define UBC\n\t#include \"deepsort/FeatureGetter/FeatureGetter.h\"\n#endif\n\n#include \"./deepsort/tracker.h\"\n#include \"StrCommon.h\"\n#include \"fdsst/fdssttracker.hpp\"\n#include \"fdsst/fhog.h\"\n#include <boost/thread/mutex.hpp>\n\n\nboost::shared_ptr<NearestNeighborDistanceMetric> NearestNeighborDistanceMetric::self_;\nboost::shared_ptr<KF> KF::self_;\n\n#define UHOG\n\n\nvoid ExtractFeatureHog(const cv::Mat &in, \n\tconst std::vector<cv::Rect> &rcsin,\n\tstd::vector<FEATURE> &fts){\n\tcv::Mat frame;\n\tcvtColor(in, frame, cv::COLOR_RGB2GRAY);\n\tfor(int i = 0; i < rcsin.size(); i++){\n\t\tMat nnn = frame(rcsin[i]);\n\t\tresize(nnn, nnn, Size(32, 32));\n\t\tint len = 0;\n\t\tfloat *hog = HOGXYZ(nnn, len);\n\t\tif(hog==NULL || len!=128){\n\t\t\tprintf(\"hog(%d) is null or len(%d)!=128,exit!\\n\", hog==NULL, len);\n\t\t\texit(0);\n\t\t}\n\t\tFEATURE ft;\n\t\tfor(int j = 0; j < len; j++){\n\t\t\tft(j) = hog[j];\n\t\t}\n\t\tdelete []hog;\n\t\tfts.push_back(ft);\n\t}\n}\n#ifdef UDL\nvoid ExtractFeature(const cv::Mat &in, \n\tconst std::vector<cv::Rect> &rcsin,\n\tstd::vector<FEATURE> &fts) {\n\tint maxw = 0;\n\tint maxh = 0;\n\tint count = rcsin.size(); \n#ifdef UBC\n\tint BC = 1;\n\tif(count < BC)count=BC;\n#endif\n\tstd::vector<cv::Mat> faces;\n\tcv::Rect lr;\n\tfor (int i = 0; i < count; i++) {\n\t\tcv::Rect rc;\n\t\tif(i < rcsin.size()){\n\t\t\trc = rcsin[i];\n\t\t\tlr = rc;\n\t\t}\n\t\telse{\n\t\t\trc = lr;\n\t\t}\n\t\tfaces.push_back(in(rc).clone());\n\t\tint w = rc.width;\n\t\tint h = rc.height;\n\t\tif (w > maxw) {\n\t\t\tmaxw = w;\n\t\t}\n\t\tif (h > maxh) {\n\t\t\tmaxh = h;\n\t\t}\n\t}\n\tmaxw += 10;\n\tmaxh += 10;\n\n\tcv::Mat frame(maxh, maxw*count, CV_8UC3);\n\tstd::vector<cv::Rect> rcs;\n\tfor (int i = 0; i < count; i++) {\n\t\tcv::Mat &face = faces[i];\n\t\tcv::Rect rc = cv::Rect(i*maxw + 5, 5, face.cols, face.rows);\n\t\trcs.push_back(rc);\n\t\tcv::Mat tmp = frame(rc);\n\t\tface.copyTo(tmp);\n\t}\n\tstd::vector<FEATURE> newfts;\n\tFeatureGetter::Instance()->Get(frame, rcs, newfts);\n\tfor(int i = 0; i < rcsin.size(); i++){\n\t\tfts.push_back(newfts[i]);\n\t}\n}\n#endif\n\nNT::NT(){\n\ttt_ = TTrackerP(new TTracker(0.7, 30, 1));\n}\n\nNT::~NT(){\n}\nbool NT::Init(){\n#ifdef UDL\n\tif(!FeatureGetter::Instance()->Init()){\n\t\treturn false;\n\t}\n#endif\n\tif(0){// just a test\n\t\tMat frame = cv::imread(\"/home/xyz/code1/xyz/img1/000001.jpg\");\n\t\tMat nnn;\n       \t\tcvtColor(frame, nnn, cv::COLOR_RGB2GRAY);\n\t\tresize(nnn, nnn, Size(32, 32));\n\t\tMat a = fhog(nnn, 4, 9, 0.2f, false);\n\t\tstd::cout << \"a:cols:\" << a.cols << \"a:rows:\" << a.rows << \"\\njust a test, exit\\n\";\n\t\texit(0);\n\t}\n\n\tKF::Instance()->Init();\n#ifdef UDL\n\t#ifdef UBC\n\t\tMat frame = cv::imread(\"/home/xyz/code1/xyz/img1/000001.jpg\");\n\t\tstd::vector<Detection> dets;\n\t\tstd::vector<FEATURE> fts;\n\t\tstd::vector<cv::Rect> rcs;\n\t\tsrand((unsigned)time(NULL));\n\t\tint width = frame.cols;\n\t\tint height = frame.rows;\n\t\t//for(int i = 0; i < 30; i++){\n\t\t\t\t\tint x = rand()%width;\n\t\t\t\t\tint y = rand()%height;\n\t\t\t\t\tint w = 100;\n\t\t\t\t\tint h = 100;\n\t\t\t\t\t//std::cout << x << \",\" << y  << \",\" << w  << \",\" << h << \"\\n\";\n\t\t\t\t\tif(x+w > width){\n\t\t\t\t\t\tw = width - x;\n\t\t\t\t\t}\n\t\t\t\t\tif(y+h > height){\n\t\t\t\t\t\th = height - y;\n\t\t\t\t\t}\n\t\t\t\t\tcv::Rect rc(x, y, w, h);\t\n\t\t\t\t\trcs.push_back(rc);\n\t\t//}\n\t\tExtractFeature(frame, rcs, fts);\n\t#endif\n#endif\n\tNearestNeighborDistanceMetric::Instance()->Init(0.2, 100);\n\n\treturn true;\n}\nNewAndDelete NT::UpdateDS(const cv::Mat &frame, const std::vector<cv::Rect> &rcs, int num, const std::vector<int> &oriPos){\n\t\tint64_t tm1 = gtm();\n\t\tstd::vector<Detection> dets;\n\t\tstd::vector<FEATURE> fts;\n\t\tif(rcs.size() > 0){\n#ifdef UHOG\n\t\t\tExtractFeatureHog(frame, rcs, fts);\n#else\n\t\t\tExtractFeature(frame, rcs, fts);\n#endif\n\t\t}\n\t\tint64_t tm2 = gtm();\n\t\tfor (int i = 0; i < rcs.size(); i++){\t\n\t\t\tDSBOX box;\n\t\t\tcv::Rect rc = rcs[i];\n\t\t\tbox(0) = rc.x;\n\t\t\tbox(1) = rc.y;\n\t\t\tbox(2) = rc.width;\n\t\t\tbox(3) = rc.height;\n\t\t\tDetection det(box, 1, fts[i]);\n\t\t\t//printf(\"oriPos.size():%d\\n\", oriPos.size());\n\t\t\tif(i < (int)oriPos.size()-1){\n\t\t\t\tdet.oriPos_ = oriPos[i];\n\t\t\t}\n\t\t\tdets.push_back(det);\n\t\t}\n   \t \tNewAndDelete nad = tt_->update(dets);\n\t\tint64_t tm3 = gtm();\n\t\tstd::string tail = \"\";\n\t\tif(tm3-tm1 > 30000){\n\t\t\ttail = \"****\";\n\t\t}\n\n\t\tstd::cout << num << \"----rcs.size():\" << rcs.size() << \"[tm1:\" << tm1 << \",tm2:\" << tm2 << \"(\"<< (tm2 - tm1) << \")\"<< \",tm3:\"\n\t\t\t<< tm3 << \"(\" << (tm3-tm1) << \")]\" << tail.c_str() << \"\\n\";\n\t\treturn nad;\n}\n\n\nstruct RRS{\n\tvoid Push(const cv::Rect &rc){\n\t\tboost::mutex::scoped_lock lock(mutex_);\n\t\trcs_.push_back(rc);\n\t}\n\tvoid Get(std::vector<cv::Rect> &rcs){\n\t\trcs = rcs_;\n\t}\nprivate:\n\tstd::vector<cv::Rect> rcs_;\n\tboost::mutex mutex_;\n};\nstruct FFS{\npublic:\n\tvoid Push(int id, const FDSSTTrackerP &ff){\n\t\tboost::mutex::scoped_lock lock(mutex_);\n\t\tffs_.push_back(std::make_pair(id, ff));\n\t}\n\tvoid Get(std::vector<std::pair<int, FDSSTTrackerP> > &ffs){\n\t\tffs = ffs_;\n\t}\nprivate:\n\tstd::vector<std::pair<int, FDSSTTrackerP > > ffs_;\n\tboost::mutex mutex_;\n};\n\n// for framebuffer\nvoid NT::UpdateFDSST(const Mat &frame, std::vector<cv::Rect> &rcs){\n\tstd::map<int, FDSSTTrackerP>::iterator it;\n\tstd::vector<int> lostIds;\n\tRRS rrs;\n\tstd::vector<FDSSTTrackerP> ffs;\n\tfor(it = fdssts_.begin(); it != fdssts_.end(); ++it){\n\t\tFDSSTTrackerP fdsst = it->second;\n\t\tffs.push_back(fdsst);\n\t}\n\t#pragma omp parallel for\n\tfor(int i = 0; i < ffs.size(); i++){\n\t\tcv::Rect rc = ffs[i]->update(frame);\n\t\trrs.Push(rc);\n\t}\n\t//\n\tstd::vector<cv::Rect> rrcs;\n\trrs.Get(rrcs);\n\tfor(int i = 0; i < rrcs.size(); i++){\n\t\tcv::Rect rc = rrcs[i];\n\t\tint ww = frame.cols;\n\t\tint hh = frame.rows;\n\t\tint min = 8;\n                if(rc.x<0 || rc.y<0 ||\n                        (rc.x+rc.width)>ww ||\n                        (rc.y+rc.height)>hh ||\n                        rc.width<=min || rc.height<=min){\n\t\t\tlostIds.push_back(it->first);\n\t\t\tcontinue;\n\t\t}\n\t\trcs.push_back(ToOriRect(rc));\n\t}\n\t// remove\n\tfor(int id:lostIds){\n\t\tfdssts_.erase(id);\n\t}\n}\nstd::map<int, DSResult> NT::UpdateAndGet(const cv::Mat &frame, \n\tconst std::vector<cv::Rect> &rcsin, \n\tint num,\n\tstd::vector<cv::Rect> &outRcs,\n\tconst std::vector<int> &oriPos){\n\tstd::vector<cv::Rect> rcs = rcsin;\n        \n\t//{\t\n\tMat ffMat;\n        cvtColor(frame, ffMat, cv::COLOR_RGB2GRAY);\n\tresize(ffMat, ffMat, Size(ffMat.cols*scale_, ffMat.rows*scale_));\n\tstd::cout << \"NT::UpdateAndGet1\\n\";\n\t//}\n\tif(!rcsin.empty()){\n\t\tfdssts_.clear();\n\t}\t\n\telse{\n\t\tUpdateFDSST(ffMat, rcs);\n\t}\n\tstd::cout << \"NT::UpdateAndGet1.5\\n\";\n\toutRcs = rcs;\n\tNewAndDelete nad = UpdateDS(frame, rcs, num, oriPos);\n\n\n\tstd::map<int, DSResult> map;\n\tstd::vector<KalmanTracker> &kalmanTrackers =\n\t\t\ttt_->kalmanTrackers_;\n\n\tstd::cout << \"NT::UpdateAndGet2\\n\";\n\tstd::vector<std::pair<int, cv::Rect> > idrcs;\t\n    \tfor (const auto& track : kalmanTrackers){\n\t\tint id = (int)track->track_id;\n\t\tprintf(\"trackid:%d, is_confirmed:%d, time_since_update:%d\\n\", id, track->is_confirmed(), track->time_since_update_);\n\t\t//if (!track->is_confirmed() || track->time_since_update_ > 0) {\n\t\t//\tcontinue;\n\t\t//}\n\t\tif(track->time_since_update_ > 0){\n\t\t\tcontinue;\n\t\t}\n\t\tDSBOX box = track->to_tlwh();\n\t\tcv::Rect rc;\n\t\trc.x = box(0);\n\t\trc.y = box(1);\n\t\trc.width = box(2);\n\t\trc.height = box(3);\n\t\tint oriPos= track->oriPos_;\n\t\tDSResult tr;\n\t\ttr.rc_ = rc;\n\t\ttr.oriPos_ = oriPos;\n\t\tif(!rcsin.empty()){\n\t\t\tidrcs.push_back(std::make_pair(id, rc));\t\n\t\t\tprintf(\"id:%d, rc:(%d, %d, %d, %d), oriPos:%d, rcsin.size():%d, rcs.size():%d\\n\", \n\t\t\t\t\tid, rc.x, rc.y, rc.width, rc.height,\n\t\t\t\t\toriPos, rcsin.size(), rcs.size());\n\t\t\t\n\t\t}\n\t\tif (!track->is_confirmed() || track->time_since_update_ > 0) {\n\t\t\tcontinue;\n\t\t}\n\n\t\tmap.insert(std::make_pair(id, tr));\n    \t}\n\tstd::cout << \"NT::UpdateAndGet3\\n\";\n\tFFS ffs;\n\t#pragma omp parallel for\n\tfor(int i = 0; i < idrcs.size(); i++){\n\t\tstd::pair<int, cv::Rect> pa = idrcs[i];\n\t\tint id = pa.first;\n\t\tcv::Rect rc = pa.second;\n\t\tprintf(\"id:%d, rc:(%d, %d, %d, %d)\\n\", \n\t\t\t\tid, rc.x, rc.y, rc.width, rc.height);\n\n\t\tFDSSTTrackerP fdsst(new FDSSTTracker());\n\t\tfdsst->init(ToScaleRect(rc), ffMat);\n\t\tffs.Push(id, fdsst);\n\t}\n\tstd::cout << \"NT::UpdateAndGet4\\n\";\n\tstd::vector<std::pair<int, FDSSTTrackerP> > pps;\n\tffs.Get(pps);\n\tfor(int i = 0; i < pps.size(); i++){\n\t\tstd::pair<int, FDSSTTrackerP> pa = pps[i];\n\t\tfdssts_.insert(pa);\n\t}\n\treturn map;\n}\n\n\n\n\n\n"
  },
  {
    "path": "NT.h",
    "content": "#ifndef _NTH_\n#define _NTH_\n#include <opencv2/opencv.hpp>\n#include <boost/shared_ptr.hpp>\n#include \"NTN.h\"\nusing namespace cv;\n\nstruct DSResult{\n\tcv::Rect rc_;\n\tint oriPos_;\n\tDSResult(){\n\t\trc_ = cv::Rect(0, 0, 0, 0);\n\t\toriPos_ = -1;\n\t}\n};\n\nclass TTracker;\ntypedef boost::shared_ptr<TTracker> TTrackerP;\n\nclass FDSSTTracker;\ntypedef boost::shared_ptr<FDSSTTracker> FDSSTTrackerP;\n\n\nclass NT{\npublic:\n\tNT();\n\t~NT();\n\tbool Init();\n\n\t// for framebuffer\n\tstd::map<int, DSResult> UpdateAndGet(const cv::Mat &frame, \n\t\tconst std::vector<cv::Rect> &rcs, \n\t\tint num,\n\t\tstd::vector<cv::Rect> &outRcs, \n\t\tconst std::vector<int> &oriPos=std::vector<int>(0));\nprivate:\n\tvoid UpdateFDSST(const Mat &frame, std::vector<cv::Rect> &rcs);\t\n\tNewAndDelete UpdateDS(const cv::Mat &frame, \n\t\tconst std::vector<cv::Rect> &rcs, \n\t\tint num,\n\t\tconst std::vector<int> &oriPos);\nprivate:\n\tcv::Rect ToOriRect(const cv::Rect &rc){\n\t\tcv::Rect re;\n\t\tfloat x = ((float)rc.x)/scale_;\n\t\tfloat y = ((float)rc.y)/scale_;\n\t\tfloat w = ((float)rc.width)/scale_;\n\t\tfloat h = ((float)rc.height)/scale_;\n\t\tre.x = x;\n\t\tre.y = y;\n\t\tre.width = w;\n\t\tre.height = h;\n\t\treturn re;\n\t}\n\tcv::Rect ToScaleRect(const cv::Rect &rc){\n\t\tcv::Rect re;\n\t\tfloat x = ((float)rc.x)*scale_;\n\t\tfloat y = ((float)rc.y)*scale_;\n\t\tfloat w = ((float)rc.width)*scale_;\n\t\tfloat h = ((float)rc.height)*scale_;\n\t\tre.x = x;\n\t\tre.y = y;\n\t\tre.width = w;\n\t\tre.height = h;\n\t\treturn re;\n\t}\nprivate:\n\tTTrackerP tt_;\n\tstd::map<int, FDSSTTrackerP> fdssts_;\n\tfloat scale_ = 0.25;\n};\n#endif\n\n\n"
  },
  {
    "path": "NTN.h",
    "content": "#ifndef _NTNH_\n#define _NTNH_\n\nstruct NewAndDelete{\n\tstd::map<int, int> news_;// id, pos\n\tstd::vector<int> deletes_;\n};\n\n#endif\n"
  },
  {
    "path": "README.md",
    "content": "**DS**(~~deepsort cpp version~~)\n\nC++ implementation of Simple Online Realtime Tracking with a Deep Association Metric\n\n# 1. dependencies\ncomponent|version\n-|-\neigen|3.3\nopencv|-\nboost|-\ntensorflow|1.4\n\n# 2. build\n./make.sh\n\n# 3. prepare data\n\nchange the var values at [lines160-162 in Main.cpp](https://github.com/oylz/DS/blob/master/Main.cpp#L160TL162):\n```\n_imgDir = \"/home/xyz/code1/xyz/img1/\"; // MOT format\n\n_rcFile = \"/home/xyz/code1/xyz/det/det.txt\"; // MOT format\n\n_imgCount = 680;  // frames count\n```\n\n\n# 4. run\n\n./r.sh\n\n# 5.tips\n\ntensorflow build:\n```\n(1) ./configure\n(2) bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=cuda  tensorflow:libtensorflow_cc.so\n```\n\n\n\n\n\n\n\n\n"
  },
  {
    "path": "StrCommon.h",
    "content": "#ifndef _STRCOMMONH_\n#define _STRCOMMONH_\n#include <string>\n#include <vector>\n#ifdef WIN32\n#include <winsock2.h>\n#include <windows.h>\n#include <time.h>\n\nstatic int gettimeofday(struct timeval *tp, void *tzp)\n{\n\ttime_t clock;\n\tstruct tm tm;\n\tSYSTEMTIME wtm;\n\n\tGetLocalTime(&wtm);\n\ttm.tm_year = wtm.wYear - 1900;\n\ttm.tm_mon = wtm.wMonth - 1;\n\ttm.tm_mday = wtm.wDay;\n\ttm.tm_hour = wtm.wHour;\n\ttm.tm_min = wtm.wMinute;\n\ttm.tm_sec = wtm.wSecond;\n\ttm.tm_isdst = -1;\n\tclock = mktime(&tm);\n\ttp->tv_sec = clock;\n\ttp->tv_usec = wtm.wMilliseconds * 1000;\n\n\treturn (0);\n}\nstatic void usleep(int64_t us) {\n\tint64_t s = us / 1000;\n\tSleep(s);\n}\n#else\n#include <sys/time.h>\n#endif\n\nusing namespace cv;\n\n\nstatic int64_t gtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\n\nstatic void splitStr(const std::string& inputStr, const std::string &key, std::vector<std::string>& outStrVec) {\n\tif (inputStr == \"\") {\n\t\treturn;\n\t}\n\tint pos = inputStr.find(key);\n\tint oldpos = 0;\n\tif (pos > 0) {\n\t\tstd::string tmp = inputStr.substr(0, pos);\n\t\toutStrVec.push_back(tmp);\n\t}\n\twhile (1) {\n\t\tif (pos < 0) {\n\t\t\tbreak;\n\t\t}\n\t\toldpos = pos;\n\t\tint newpos = inputStr.find(key, pos + key.length());\n\t\tstd::string tmp = inputStr.substr(pos + key.length(), newpos - pos - key.length());\n\t\toutStrVec.push_back(tmp);\n\t\tpos = newpos;\n\t}\n\tint tmplen = 0;\n\tif (outStrVec.size() > 0) {\n\t\ttmplen = outStrVec.at(outStrVec.size() - 1).length();\n\t}\n\tif (oldpos + tmplen < inputStr.length() - 1) {\n\t\tstd::string tmp = inputStr.substr(oldpos + key.length());\n\t\toutStrVec.push_back(tmp);\n\t}\n}\n\nstatic std::string trim(std::string &s) {\n\tif (s.empty()) {\n\t\treturn s;\n\t}\n\n\ts.erase(0, s.find_first_not_of(\" \"));\n\ts.erase(s.find_last_not_of(\" \") + 1);\n\treturn s;\n}\n\nstatic int toInt(const std::string &in){\n\tint re = 0;\n\tsscanf(in.c_str(), \"%d\", &re);\n\treturn re;\n}\nstatic float toFloat(const std::string &in) {\n\tfloat re = 0;\n\tsscanf(in.c_str(), \"%f\", &re);\n\treturn re;\n}\nstatic std::string toStr(float in) {\n\tchar chr[20] = { 0 };\n\tsprintf(chr, \"%f\", in);\n\tstd::string re(chr);\n\treturn re;\n}\nstatic std::string toStr(int in){\n\tchar chr[20] = {0};\n\tsprintf(chr, \"%d\", in);\n\tstd::string re(chr);\n\treturn re;\n}\nstatic std::string to4dStr(int in){\n\tchar chr[20] = {0};\n\tsprintf(chr, \"%04d\", in);\n\tstd::string re(chr);\n\treturn re;\n}\nstatic std::string to5dStr(int in){\n\tchar chr[20] = {0};\n\tsprintf(chr, \"%05d\", in);\n\tstd::string re(chr);\n\treturn re;\n}\nstatic std::string to6dStr(int in){\n\tchar chr[20] = {0};\n\tsprintf(chr, \"%06d\", in);\n\tstd::string re(chr);\n\treturn re;\n}\n#endif\n"
  },
  {
    "path": "deepsort/Detection.h",
    "content": "#ifndef _DETECTIONH_\n#define _DETECTIONH_\n#include <vector>\n#include <Eigen>\n\ntypedef Eigen::Matrix<float, 1, 4, Eigen::RowMajor> DSBOX;\ntypedef Eigen::Matrix<float, -1, 4, Eigen::RowMajor> DSBOXS;\ntypedef Eigen::Matrix<float, 1, 128, Eigen::RowMajor> FEATURE;\ntypedef Eigen::Matrix<float, -1, 128, Eigen::RowMajor> FEATURESS;\ntypedef std::vector<int> IDS;\ntypedef Eigen::Matrix<float, 1, 2, Eigen::RowMajor> PT2;\ntypedef Eigen::Matrix<float, -1, -1, Eigen::RowMajor> DYNAMICM;\ntypedef Eigen::Matrix<float, 1, 8, Eigen::RowMajor> MEAN;\ntypedef Eigen::Matrix<float, 8, 8, Eigen::RowMajor> VAR;\ntypedef Eigen::Matrix<float, 1, 4, Eigen::RowMajor> NMEAN;\ntypedef Eigen::Matrix<float, 4, 4, Eigen::RowMajor> NVAR;\n\nstruct Detection {\n\tDSBOX tlwh_;\n\tfloat confidence_;\n\tFEATURE feature_;\n\tint oriPos_ = -1;\n\tDetection(const DSBOX &tlwh, float confidence, const FEATURE &feature) {\n\t\ttlwh_ = tlwh;\n\t\tconfidence_ = confidence;\n\t\t//std::cout << feature;\n\t\tfeature_ = feature;\n\t}\n\tDSBOX to_tlbr() const{\n\t\tDSBOX ret = tlwh_;\n\t\tret(0, 2) += ret(0, 0);\n\t\tret(0, 3) += ret(0, 1);\n\t\treturn ret;\n\t}\n\tDSBOX to_xyah() const{\n\t\tDSBOX ret = tlwh_;\n\t\tret(0, 0) += ret(0, 2) / 2;\n\t\tret(0, 1) += ret(0, 3) / 2;\n\t\tret(0, 2) /= ret(0, 3);\n\t\treturn ret;\n\t}\n};\n#endif\n"
  },
  {
    "path": "deepsort/FeatureGetter/CaffeShuffeNetFeatureGetter.cpp",
    "content": "\n#include \"FeatureGetter.h\"\n\n#include <caffe/net.hpp>\n\n#include <fstream>\n#include <iostream>\n#include <opencv2/opencv.hpp>\n#include <sys/time.h>\n#include <map>\n#include <vector>\n#include <boost/shared_ptr.hpp>\n#include <boost/thread/mutex.hpp>\n\n\nstatic int64_t fgtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\n\n\nboost::shared_ptr<FeatureGetter> FeatureGetter::self_;\n\ntypedef unsigned char uint8;\n\ntypedef boost::shared_ptr<caffe::Net<float> >  XNET;\ntypedef caffe::Blob<float>* XINPUT;\n\n#ifdef OONE\nstatic const int XCOUNT = 1;\n#else\nstatic const int XCOUNT = 10;\n#endif\nstd::map<int, XNET> _xnets;\nstd::map<int, XINPUT> _xinputs;\nint _iw = -1;\nint _ih = -1;\nint _outLayer = -1;\nstatic const std::string _outLayerName = \"fc1000\";\n\nstatic const std::string rootp = \"/home/xyz/code1/ShuffleNet-Model/\";\nstatic const std::string modelp = rootp + \"incode.prototxt\";//\"ssd_shufflenet_21_test.prototxt\";\n//static const std::string modelp = rootp + \"ssd_shufflenet_21_test.prototxt\";\nstatic const std::string weightp = rootp + \"shufflenet_1x_g3.caffemodel\";\n\nvoid to_buffer(const cv::Mat &img, float *buf){\n    if (img.isContinuous()) {\n      memcpy(buf, img.ptr<float>(0),\n             static_cast<size_t>(img.total()) * sizeof(float));\n    } \n    else {\n      for (int i = 0; i < img.rows; i++) {\n        memcpy(buf, img.ptr<float>(i),\n               static_cast<size_t>(img.cols) * sizeof(float));\n        buf += img.cols;\n      }\n    }\n}\n\n\n\tbool FeatureGetter::Init() {\n     \t\tcaffe::Caffe::set_mode(caffe::Caffe::GPU);\n    \t\tcaffe::Caffe::SetDevice(0);\n\t\tfor(int i = 0; i < XCOUNT; i++){\n        \t\tcaffe::Net<float> *net = new caffe::Net<float>(modelp, caffe::TEST);\n      \t\t\tnet->CopyTrainedLayersFrom(weightp);\n\t\t\tXNET xnet;\n      \t\t\txnet.reset(net); \n\t\t\t//\n\t\t\txnet->ForwardFrom(0);\n\t\t\t_xnets.insert(std::make_pair(i, xnet));\n\n\t\t\tauto &blobs = xnet->input_blobs();\n\t\t\tXINPUT xinput = blobs[0];\n\t\t\t_xinputs.insert(std::make_pair(i, xinput));\n\n\t\t\tif(i == 0){\n    \t\t\t\tauto shape = blobs[0]->shape();\n    \t\t\t\t//////shape[0] = 1;\n    \t\t\t\t//////blobs[0]->Reshape(shape);\n\t\t\t\t_iw = (int)shape[2];\n\t\t\t\t_ih = (int)shape[3];\t\n\t\t\t\tprintf(\"_iw:%d, _ih:%d\\n\", _iw, _ih);\n\n\t\t\t\tint index = 0;\n  \t\t\t\tfor (auto const &layer : xnet->layers()) {\n    \t\t\t\t\tauto const &param = layer->layer_param();\n    \t\t\t\t\tfor (auto const &top_name : param.top()) {\n      \t\t\t\t\t\tif (top_name == _outLayerName) {\n\t\t\t\t\t\t\t_outLayer = index;\n        \t\t\t\t\t\tbreak;\t\n      \t\t\t\t\t\t}\n    \t\t\t\t\t}\n    \t\t\t\t\tindex++;\n  \t\t\t\t}\n\t\t\t\tstd::cout << \"_outLayer:\" << _outLayer << \"\\n\";\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t}\n\t// -----------------------------------------\n\tbool GetCore(const XNET &xnet, const XINPUT &xinput, const cv::Mat &imgin, FFEATURE &ft) {\n\t\tauto dst_data = xinput->mutable_cpu_data();\n\t\tcv::Mat mm;\n\t\tcv::resize(imgin, mm, cv::Size(_iw, _ih));\n\t\tcv::Mat img;\n\t\tmm.convertTo(img, CV_32FC3, 1, 0);\n\t\tstd::vector<cv::Mat> channels;\n\t\tcv::split(img, channels);\n  \t\tfor (size_t j = 0; j < channels.size(); j++) {\n    \t\t\tchannels[j] += (-175);\n\t\t\tto_buffer(channels[j], dst_data);\n    \t\t\tdst_data += _iw*_ih;\n\t\t}\n\t\t// go\n\t\txnet->ForwardFrom(0);\n\t\txnet->ForwardTo(_outLayer);\n\t\t// get\n\t\tstd::map<std::string, std::pair<const float *, size_t>> output_data;\n   \t\tauto output_blob = xnet->blob_by_name(_outLayerName);\n    \t\tif (output_blob->count() == 0) {\n      \t\t\t//throw std::runtime_error(name + \" blob is empty\");\n      \t\t\tprintf(\"blob is empty\");\n\t\t\treturn false;\n    \t\t}\n\t\tauto tmp1 = output_blob->cpu_data();\n\t\tauto len = output_blob->count();\n\t\tstd::cout << \"begin tmp1:\\n\" << tmp1 << \n\t\t\t\"\\nend tmp1\\nbegin len:\\n\" \n\t\t\t<< len << \"\\nend len\\n\";\n\t\tfor(int i = 0; i < len; i++){\n\t\t\tif(i>=128){\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tft(i) = tmp1[i];\n\t\t}\n\t\treturn true;\n  \t}\n\nstruct XFTS{\npublic:\n\tvoid Push(int id, const FFEATURE &ff){\n\t\tboost::mutex::scoped_lock lock(mutex_);\n\t\tffs_.push_back(std::make_pair(id, ff));\n\t}\n\tvoid Get(std::vector<std::pair<int, FFEATURE> > &ffs){\n\t\tffs = ffs_;\n\t}\nprivate:\n\tstd::vector<std::pair<int, FFEATURE > > ffs_;\n\tboost::mutex mutex_;\n};\n\n\n\tbool FeatureGetter::Get(const cv::Mat &img, const std::vector<cv::Rect> &rcs,\n\t\tstd::vector<FFEATURE> &fts) {\n\t\tint64_t ftm1 = fgtm();\t\n\t\tXFTS xfts;\n#ifndef OONE\n\t\t#pragma omp parallel for\n#endif\n\t\tfor(int i = 0; i < rcs.size(); i++){\n\t\t\tcv::Mat tmp = img(rcs[i]);\n\t\t\tFFEATURE ft;\n\t\t\tint64_t ftm11 = fgtm();\t\n#ifndef OONE\n\t\t\tXNET &xnet = _xnets[i];\n\t\t\tXINPUT &xinput = _xinputs[i];\n#else\n\t\t\tXNET &xnet = _xnets[0];\n\t\t\tXINPUT &xinput = _xinputs[0];\n#endif\n\t\t\tbool re = GetCore(xnet, xinput, tmp, ft);\n\t\t\tint64_t ftm12 = fgtm();\t\n\t\t\tstd::cout << \"\\t----ftm12-ftm11:\" << (ftm12-ftm11) << \"\\n\";\n\t\t\tif(!re){\n\t\t\t\tprintf(\"error!\\n\");\n\t\t\t\texit(0);\n\t\t\t}\n\t\t\txfts.Push(i, ft);\n\t\t\tfts.push_back(ft);\n\t\t}\n\t\t//\n\t\tfts.resize(rcs.size());\n\t\tstd::vector<std::pair<int, FFEATURE> > pairs;\n\t\txfts.Get(pairs);\n\t\tfor(int i = 0; i < pairs.size(); i++){\n\t\t\tstd::pair<int, FFEATURE> pa = pairs[i];\n\t\t\tfts[pa.first] = pa.second;\t\n\t\t}\n\t\tint64_t ftm2 = fgtm();\n\t\tstd::cout << \"caffe.forward--shufflenet--rcs.size():\" << rcs.size() \n\t\t\t<< \", ftm2-ftm1:\" << (ftm2-ftm1) << \"\\n\";\n \n\t}\n\n\n"
  },
  {
    "path": "deepsort/FeatureGetter/FaceNetFeatureGetter.cpp",
    "content": "\n#include \"FeatureGetter.h\"\n\n\n#include <tensorflow/core/public/session.h>\n#include <fstream>\n#include <iostream>\n\n#include <tensorflow/cc/saved_model/loader.h>\n#include <tensorflow/core/graph/default_device.h>\n#include <tensorflow/core/platform/env.h>\n#include <tensorflow/core/protobuf/config.pb.h>\n#include <tensorflow/c/checkpoint_reader.h>\n#include <tensorflow/c/c_api_internal.h>\n#include <opencv2/opencv.hpp>\n#include <tensorflow/cc/ops/math_ops.h>\nnamespace tf = tensorflow;\n\n#include <sys/time.h>\n\n\nstatic int64_t fgtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\n\n\nboost::shared_ptr<FeatureGetter> FeatureGetter::self_;\n\ntypedef float uint8;\n\nstd::unique_ptr<tf::Session> session;\n\nvoid tobuffer(const std::vector<cv::Mat> &imgs, uint8 *buf) {\n\tint pos = 0;\n\tfor (cv::Mat img : imgs) {\n\t\tint LLL = img.cols*img.rows * 3;\n\t\tint nr = img.rows;\n\t\tint nc = img.cols;\n\t\tif (img.isContinuous())\n\t\t{\n\t\t\tnr = 1;\n\t\t\tnc = LLL;\n\t\t}\n\n\t\tfor (int i = 0; i < nr; i++)\n\t\t{\n\t\t\tconst uchar* inData = img.ptr<uchar>(i);\n\t\t\tfor (int j = 0; j < nc; j++)\n\t\t\t{\n\t\t\t\tbuf[pos] = *inData++;\n\t\t\t\tpos++;\n\t\t\t}\n\t\t}\n\t}\n}\nvoid tobufferA(const std::vector<cv::Mat> &imgs, float *buf){\n\tint pos = 0;\n\tfor (cv::Mat img : imgs) {\n    \t\tif (img.isContinuous()) {\n      \t\t\tmemcpy(buf+pos, img.ptr<float>(0),\n             \t\t\tstatic_cast<size_t>(img.total()) * sizeof(float));\n\t\t\tpos += static_cast<size_t>(img.total()) * sizeof(float);\n    \t\t} \n\t\telse {\n\t\t\tprintf(\"error\\n\");\n\t\t\texit(0);\n      \t\t}\n\t}\n}\n\n\n\n\ntypedef std::vector<double> DSR;\ntypedef std::vector<DSR> DSRS;\ntypedef std::vector<int> IDSR;\ntypedef std::vector<IDSR> IDSRS;\n\n\n\tbool FeatureGetter::Init() {\n        tf::Session* session_ptr;\n        auto status = NewSession(tf::SessionOptions(), &session_ptr);\n        if (!status.ok()) {\n            std::cout << status.ToString() << \"\\n\";\n            return false;\n        }\n        session.reset(session_ptr);\n\n        //------------------\n        tf::GraphDef graph_def;\n\n        auto status1 = ReadBinaryProto(tf::Env::Default(), \"./data/facenet.pb\", &graph_def);\n        if (!status1.ok()) {\n            printf(\"ReadBinaryProto failed: %s\\n\", status1.ToString().c_str());\n\t\t\treturn false;\n        }\n\n        status = session->Create(graph_def);\n        if (!status.ok()) {\n            printf(\"create graph in session failed: %s\\n\", status.ToString().c_str());\n\t\t\treturn false;\n        }\n\n        std::vector<std::string> node_names;\n        for (const auto &node : graph_def.node()) {\n\t\tprintf(\"node name:%s\\n\", node.name().c_str());\n            node_names.push_back(node.name());\n        }\n        \n\t\treturn true;\n\t}\n\tbool FeatureGetter::Get(const cv::Mat &img, const std::vector<cv::Rect> &rcs,\n\t\tstd::vector<FFEATURE> &fts) {\n        std::vector<cv::Mat> mats;\n        for(cv::Rect rc:rcs){\n            cv::Mat mat1 = img(rc).clone();\n            cv::resize(mat1, mat1, cv::Size(160, 160));\n\n \t/*auto face_mat = face.get_face_image()                                                            \n                          .resize(input_width, input_height)                                           \n                          .convert_to(CV_32FC3)                                                        \n                          .get_cv_mat();*/\n/*\tcv::Mat face_mat;\n\t//模型希望是rgb顺序\n\tcv::cvtColor(mat1, face_mat, CV_BGR2RGB);\n\tface_mat = face_mat.reshape(1);\n\n\t// whitten\n\tcv::Scalar means;\n\tcv::Scalar stds;\n\tcv::meanStdDev(face_mat, means, stds);\n \n\tstds[0] =\n    \t\tstd::max(float(stds[0]), 1.0f / sqrtf(160 * 160 * 3));\n\tface_mat -= means[0];\n\tface_mat /= stds[0];\n\n\t\tcv::Mat tmp = face_mat.clone();\n            mats.push_back(tmp);\n*/\n\t\tmats.push_back(mat1);\n        }\n        int count = mats.size();\n        \n        tensorflow::Tensor input_tensor0(tensorflow::DT_FLOAT, { count, 160, 160, 3 });\n        tobuffer(mats, input_tensor0.flat<uint8>().data());\n\n        std::vector<tensorflow::Tensor> output_tensors;\n\n        std::vector<std::pair<std::string, tensorflow::Tensor>> ins;\n        std::pair<std::string, tensorflow::Tensor> pa;\n        pa.first = \"input\";\n        pa.second = input_tensor0;\n        ins.push_back(pa);\n\t{\n        \tstd::pair<std::string, tensorflow::Tensor> pa1;\n        \tpa1.first =\"phase_train\";\n\t\ttf::Tensor phase_train(tf::DT_BOOL, tf::TensorShape());\n\t\tphase_train.scalar<bool>()() = false;\n\t\tpa1.second = phase_train;\n\t\tins.push_back(pa1);\n\t}\n        std::vector<std::string> outnames;\n        outnames.push_back(\"embeddings\");\n        std::vector<std::string> ts;\n\tint64_t ftm1 = fgtm();\t\n        auto status = session->Run(\n            ins,\n            outnames,\n            ts,\n            &output_tensors);\n\tint64_t ftm2 = fgtm();\n\tstd::cout << \"session.run----rcs.size():\" << rcs.size() << \", ftm2-ftm1:\" << (ftm2-ftm1) << \"\\n\";\n        if (!status.ok()) {\n            printf(\"error 3%s \\n\", status.ToString().c_str());\n            return false;\n        }\n        float *tensor_buffer = \n            output_tensors[0].flat<float>().data();\n        int len = output_tensors[0].flat<float>().size() / count;\n        for (int i = 0; i < count; i++) {\n            //printf(\"begin====\\n\");\n\t\t\tFFEATURE ft;\n            for (int j = 0; j < len; j++) {\n\t\t\t\tft(j) = tensor_buffer[i*len + j];\n                //printf(\",%f\", tensor_buffer[i*len+j]);\n            }\n\t\t\tfts.push_back(ft);\n            //printf(\"\\nend====\\n\");\n        }            \n\t\treturn true;\n\t}\n\n\n\n"
  },
  {
    "path": "deepsort/FeatureGetter/FeatureGetter.cpp",
    "content": "\n#ifdef USE_FACE_NET\n#include \"FaceNetFeatureGetter.cpp\"\n\n#else\n\t#ifdef USE_MOBILE_NET\n\t\t#include \"MobileNetFeatureGetter.cpp\"\n\t#else\n\t\t#ifdef USE_CAFFE_SHUFFE_NET\n\t\t\t#include \"CaffeShuffeNetFeatureGetter.cpp\"\n\t\t#else\n\n#include \"FeatureGetter.h\"\n\n\n#include <tensorflow/core/public/session.h>\n#include <fstream>\n#include <iostream>\n\n#include <tensorflow/cc/saved_model/loader.h>\n#include <tensorflow/core/graph/default_device.h>\n#include <tensorflow/core/platform/env.h>\n#include <tensorflow/core/protobuf/config.pb.h>\n#include <tensorflow/c/checkpoint_reader.h>\n#include <tensorflow/c/c_api_internal.h>\n#include <opencv2/opencv.hpp>\n#include <tensorflow/cc/ops/math_ops.h>\nnamespace tf = tensorflow;\n\n#include <sys/time.h>\n\n\nstatic int64_t fgtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\n\n\nboost::shared_ptr<FeatureGetter> FeatureGetter::self_;\n\ntypedef unsigned char uint8;\n\nstd::unique_ptr<tf::Session> session;\n\nvoid tobuffer(const std::vector<cv::Mat> &imgs, uint8 *buf) {\n\tint pos = 0;\n\tfor (cv::Mat img : imgs) {\n\t\tint LLL = img.cols*img.rows * 3;\n\t\tint nr = img.rows;\n\t\tint nc = img.cols;\n\t\tif (img.isContinuous())\n\t\t{\n\t\t\tnr = 1;\n\t\t\tnc = LLL;\n\t\t}\n\n\t\tfor (int i = 0; i < nr; i++)\n\t\t{\n\t\t\tconst uchar* inData = img.ptr<uchar>(i);\n\t\t\tfor (int j = 0; j < nc; j++)\n\t\t\t{\n\t\t\t\tbuf[pos] = *inData++;\n\t\t\t\tpos++;\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n\ntypedef std::vector<double> DSR;\ntypedef std::vector<DSR> DSRS;\ntypedef std::vector<int> IDSR;\ntypedef std::vector<IDSR> IDSRS;\n\n\n\tbool FeatureGetter::Init() {\n        tf::Session* session_ptr;\n        auto status = NewSession(tf::SessionOptions(), &session_ptr);\n        if (!status.ok()) {\n            std::cout << status.ToString() << \"\\n\";\n            return false;\n        }\n        session.reset(session_ptr);\n\n        //------------------\n        tf::GraphDef graph_def;\n\n        auto status1 = ReadBinaryProto(tf::Env::Default(), \"./data/tt1.pb\", &graph_def);\n        if (!status1.ok()) {\n            printf(\"ReadBinaryProto failed: %s\\n\", status1.ToString().c_str());\n\t\t\treturn false;\n        }\n\n        status = session->Create(graph_def);\n        if (!status.ok()) {\n            printf(\"create graph in session failed: %s\\n\", status.ToString().c_str());\n\t\t\treturn false;\n        }\n\n        std::vector<std::string> node_names;\n        for (const auto &node : graph_def.node()) {\n\t\tprintf(\"node name:%s\\n\", node.name().c_str());\n            node_names.push_back(node.name());\n        }\n        \n\t\treturn true;\n\t}\n\tbool FeatureGetter::Get(const cv::Mat &img, const std::vector<cv::Rect> &rcs,\n\t\tstd::vector<FFEATURE> &fts) {\n        std::vector<cv::Mat> mats;\n        for(cv::Rect rc:rcs){\n            cv::Mat mat1 = img(rc).clone();\n            cv::resize(mat1, mat1, cv::Size(64, 128));\n            mats.push_back(mat1);\n        }\n        int count = mats.size();\n        \n        tensorflow::Tensor input_tensor0(tensorflow::DT_UINT8, { count, 128, 64, 3 });\n        tobuffer(mats, input_tensor0.flat<uint8>().data());\n\n        std::vector<tensorflow::Tensor> output_tensors;\n\n        std::vector<std::pair<std::string, tensorflow::Tensor>> ins;\n        std::pair<std::string, tensorflow::Tensor> pa;\n        pa.first = \"Placeholder\";\n        pa.second = input_tensor0;\n        ins.push_back(pa);\n        std::vector<std::string> outnames;\n        outnames.push_back(\"truediv\");\n        std::vector<std::string> ts;\n\tint64_t ftm1 = fgtm();\t\n        auto status = session->Run(\n            ins,\n            outnames,\n            ts,\n            &output_tensors);\n\tint64_t ftm2 = fgtm();\n\tstd::cout << \"session.run----rcs.size():\" << rcs.size() << \", ftm2-ftm1:\" << (ftm2-ftm1) << \"\\n\";\n        if (!status.ok()) {\n            printf(\"error 3%s \\n\", status.ToString().c_str());\n            return false;\n        }\n        float *tensor_buffer = \n            output_tensors[0].flat<float>().data();\n        int len = output_tensors[0].flat<float>().size() / count;\n        for (int i = 0; i < count; i++) {\n            //printf(\"begin====\\n\");\n\t\t\tFFEATURE ft;\n            for (int j = 0; j < len; j++) {\n\t\t\t\tft(j) = tensor_buffer[i*len + j];\n                //printf(\",%f\", tensor_buffer[i*len+j]);\n            }\n\t\t\tfts.push_back(ft);\n            //printf(\"\\nend====\\n\");\n        }            \n\t\treturn true;\n\t}\n\t\t#endif\n\t#endif\n#endif\n"
  },
  {
    "path": "deepsort/FeatureGetter/FeatureGetter.h",
    "content": "#ifndef _FEATUREGETTERH_\n#define _FEATUREGETTERH_\n\n#include <boost/shared_ptr.hpp>\n#include <opencv2/opencv.hpp>\n#include <Eigen>\ntypedef Eigen::Matrix<float, 1, 128, Eigen::RowMajor> FFEATURE;\n\n\n\n\n\nclass FeatureGetter {\nprivate:\n\tstatic boost::shared_ptr<FeatureGetter> self_;\npublic:\n\tstatic boost::shared_ptr<FeatureGetter> Instance() {\n\t\tif (self_.get() == NULL) {\n\t\t\tself_.reset(new FeatureGetter());\n\t\t}\n\t\treturn self_;\n\t}\n\tbool Init(); \n\tbool Get(const cv::Mat &img, const std::vector<cv::Rect> &rcs,\n\t\tstd::vector<FFEATURE> &fts);\n\npublic:\n\t~FeatureGetter() {\n\t}\n\n};\n\n#endif\n"
  },
  {
    "path": "deepsort/FeatureGetter/MobileNetFeatureGetter.cpp",
    "content": "\n#include \"FeatureGetter.h\"\n\n\n#include <tensorflow/core/public/session.h>\n#include <fstream>\n#include <iostream>\n\n#include <tensorflow/cc/saved_model/loader.h>\n#include <tensorflow/core/graph/default_device.h>\n#include <tensorflow/core/platform/env.h>\n#include <tensorflow/core/protobuf/config.pb.h>\n#include <tensorflow/c/checkpoint_reader.h>\n#include <tensorflow/c/c_api_internal.h>\n#include <opencv2/opencv.hpp>\n#include <tensorflow/cc/ops/math_ops.h>\nnamespace tf = tensorflow;\n\n#include <sys/time.h>\n\n\nstatic int64_t fgtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\n\n\nboost::shared_ptr<FeatureGetter> FeatureGetter::self_;\n\ntypedef float uint8;\n\nstd::unique_ptr<tf::Session> session;\n\nvoid tobuffer(const std::vector<cv::Mat> &imgs, uint8 *buf) {\n\tint pos = 0;\n\tfor (cv::Mat img : imgs) {\n\t\tint LLL = img.cols*img.rows * 3;\n\t\tint nr = img.rows;\n\t\tint nc = img.cols;\n\t\tif (img.isContinuous())\n\t\t{\n\t\t\tnr = 1;\n\t\t\tnc = LLL;\n\t\t}\n\n\t\tfor (int i = 0; i < nr; i++)\n\t\t{\n\t\t\tconst uchar* inData = img.ptr<uchar>(i);\n\t\t\tfor (int j = 0; j < nc; j++)\n\t\t\t{\n\t\t\t\tbuf[pos] = *inData++;\n\t\t\t\tpos++;\n\t\t\t}\n\t\t}\n\t}\n}\nvoid tobufferA(const std::vector<cv::Mat> &imgs, float *buf){\n\tint pos = 0;\n\tfor (cv::Mat img : imgs) {\n    \t\tif (img.isContinuous()) {\n      \t\t\tmemcpy(buf+pos, img.ptr<float>(0),\n             \t\t\tstatic_cast<size_t>(img.total()) * sizeof(float));\n\t\t\tpos += static_cast<size_t>(img.total()) * sizeof(float);\n    \t\t} \n\t\telse {\n\t\t\tprintf(\"error\\n\");\n\t\t\texit(0);\n      \t\t}\n\t}\n}\n\n\n\n\ntypedef std::vector<double> DSR;\ntypedef std::vector<DSR> DSRS;\ntypedef std::vector<int> IDSR;\ntypedef std::vector<IDSR> IDSRS;\n\n\n\tbool FeatureGetter::Init() {\n        tf::Session* session_ptr;\n        auto status = NewSession(tf::SessionOptions(), &session_ptr);\n        if (!status.ok()) {\n            std::cout << status.ToString() << \"\\n\";\n            return false;\n        }\n        session.reset(session_ptr);\n\n        //------------------\n        tf::GraphDef graph_def;\n\n        auto status1 = ReadBinaryProto(tf::Env::Default(), \"./data/mobilenet.pb\", &graph_def);\n        if (!status1.ok()) {\n            printf(\"ReadBinaryProto failed: %s\\n\", status1.ToString().c_str());\n\t\t\treturn false;\n        }\n\n        status = session->Create(graph_def);\n        if (!status.ok()) {\n            printf(\"create graph in session failed: %s\\n\", status.ToString().c_str());\n\t\t\treturn false;\n        }\n\n        std::vector<std::string> node_names;\n        for (const auto &node : graph_def.node()) {\n\t\tprintf(\"node name:%s\\n\", node.name().c_str());\n            node_names.push_back(node.name());\n        }\n        \n\t\treturn true;\n\t}\n\tbool FeatureGetter::Get(const cv::Mat &img, const std::vector<cv::Rect> &rcs,\n\t\tstd::vector<FFEATURE> &fts) {\n        std::vector<cv::Mat> mats;\n        for(cv::Rect rc:rcs){\n            cv::Mat mat1 = img(rc).clone();\n            cv::resize(mat1, mat1, cv::Size(224, 224));\n\n\t\tmats.push_back(mat1);\n        }\n        int count = mats.size();\n        \n        tensorflow::Tensor input_tensor0(tensorflow::DT_FLOAT, { count, 224, 224, 3 });\n        tobuffer(mats, input_tensor0.flat<uint8>().data());\n\n        std::vector<tensorflow::Tensor> output_tensors;\n\n        std::vector<std::pair<std::string, tensorflow::Tensor>> ins;\n        std::pair<std::string, tensorflow::Tensor> pa;\n        pa.first = \"input\";\n        pa.second = input_tensor0;\n        ins.push_back(pa);\n        std::vector<std::string> outnames;\n        outnames.push_back(\"MobilenetV1/Predictions/Reshape_1\");\n        std::vector<std::string> ts;\n\tint64_t ftm1 = fgtm();\t\n        auto status = session->Run(\n            ins,\n            outnames,\n            ts,\n            &output_tensors);\n\tint64_t ftm2 = fgtm();\n\tstd::cout << \"session.run--mobilenet--rcs.size():\" << rcs.size() << \", ftm2-ftm1:\" << (ftm2-ftm1) << \"\\n\";\n        if (!status.ok()) {\n            printf(\"error 3%s \\n\", status.ToString().c_str());\n            return false;\n        }\n        float *tensor_buffer = \n            output_tensors[0].flat<float>().data();\n        int len = output_tensors[0].flat<float>().size() / count;\n        for (int i = 0; i < count; i++) {\n            //printf(\"begin====\\n\");\n\t\t\tFFEATURE ft;\n            for (int j = 0; j < len; j++) {\n\t\t\t\tif(j>=128){\n\t\t\t\t\tcontinue;\n\t\t\t\t}\n\t\t\t\tft(j) = tensor_buffer[i*len + j];\n                //printf(\",%f\", tensor_buffer[i*len+j]);\n            }\n\t\t\tfts.push_back(ft);\n            //printf(\"\\nend====\\n\");\n        }            \n\t\treturn true;\n\t}\n\n\n\n"
  },
  {
    "path": "deepsort/FeatureGetter/make.sh",
    "content": "#!/bin/bash\nfunction getbazel(){\n\tLINE=`readlink -f /home/$USER/code1/tensorflow-1.4.0-rc0/bazel-bin/`\n\n\tPOS1=\"_bazel_$USER/\"\n\tSTR=${LINE##*$POS1}\n\n\tBAZEL=${STR:0:32}\n\n\techo $BAZEL\n}\n\n\n\nBAZEL=`getbazel`\n\nfunction TF(){\nIINCLUDE=\"-I/home/$USER/code/test/pp/opencvlib/include -I/usr/local/include -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/eigen_archive/Eigen -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/eigen_archive -I/home/$USER/code1/tensorflow-1.4.0-rc0 -I/home/$USER/code1/tensorflow-1.4.0-rc0/bazel-genfiles -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/nsync/public\"\n\nLLIBPATH=\"-L/home/$USER/code/test/pp/opencvlib/lib -L/usr/local/lib -L/home/$USER/code1/tensorflow-1.4.0-rc0/bazel-bin/tensorflow\"\nLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz -lopencv_highguixyz -ltensorflow_cc -ltensorflow_framework\"\n\nrm libFeatureGetter.so -rf\ng++ --std=c++14 -O3 -fopenmp -fPIC -shared -o libFeatureGetter.so $IINCLUDE $LLIBPATH  FeatureGetter.cpp $LLIBS\n\n}\n\n\n#CAFFEROOT=\"/home/xyz/code/py-faster-rcnn/caffe-fast-rcnn\"\nCAFFEROOT=\"/home/$USER/code1/caffe-master\"\n#CAFFEROOT=\"/home/$USER/code1/caffe-ssd\"\n\n\nfunction CAFFE(){\nIINCLUDE=\"-I/home/$USER/code/test/pp/opencvlib/include -I/usr/local/include -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/eigen_archive/Eigen -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/eigen_archive -I$CAFFEROOT/include -I/usr/local/cuda-8.0-cudnn5.0.5/include -I$CAFFEROOT/build/src\"\nLLIBPATH=\"-L/home/$USER/code/test/pp/opencvlib/lib -L$CAFFEROOT/distribute/lib\"\nLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz -lopencv_highguixyz -lcaffe\"\n\nrm libFeatureGetter.so -rf\ng++ --std=c++14 -O3 -fopenmp -DOONE -DUSE_CAFFE_SHUFFE_NET -fPIC -shared -o libFeatureGetter.so $IINCLUDE $LLIBPATH  FeatureGetter.cpp $LLIBS\n#g++ --std=c++14 -O3 -fopenmp  -DUSE_CAFFE_SHUFFE_NET -fPIC -shared -o libFeatureGetter.so $IINCLUDE $LLIBPATH  FeatureGetter.cpp $LLIBS\n\n\n}\n\n\n\n#CAFFE\nTF\n\n\n\n\n\n\n"
  },
  {
    "path": "deepsort/HungarianOper.h",
    "content": "#ifndef _HUNGARIANOPERH_\n#define _HUNGARIANOPERH_\n#include \"munkres/munkres.h\"\n#include \"munkres/adapters/boostmatrixadapter.h\"\n#include \"Detection.h\"\n\nclass HungarianOper {\npublic:\n\tstatic Eigen::Matrix<float, -1, 2> Solve(const DYNAMICM &cost_matrix) {\n\t\tint rows = cost_matrix.rows();\n\t\tint cols = cost_matrix.cols();\n\t\tMatrix<double> matrix(rows, cols);\n\t\tfor (int row = 0; row < rows; row++) {\n\t\t\tfor (int col = 0; col < cols; col++) {\n\t\t\t\tmatrix(row, col) = cost_matrix(row, col);\n\t\t\t}\n\t\t}\n\t\t//\n\t\tMunkres<double> m;\n\t\tm.solve(matrix);\n\n\t\t// \n\t\tstd::vector<std::pair<int, int>> pairs;\n\t\tfor (int row = 0; row < rows; row++) {\n\t\t\tfor (int col = 0; col < cols; col++) {\n\t\t\t\tint tmp = (int)matrix(row, col);\n\t\t\t\tif (tmp == 0) {\n\t\t\t\t\tstd::pair<int, int> pa;\n\t\t\t\t\tpa.first = row;\n\t\t\t\t\tpa.second = col;\n\t\t\t\t\tpairs.push_back(pa);\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\t//\n\t\tint count = pairs.size();\n\t\tEigen::Matrix<float, -1, 2> re(count, 2);\n\t\tfor (int i = 0; i < count; i++) {\n\t\t\tstd::pair<int, int> &pa = pairs[i];\n\t\t\tre(i, 0) = pa.first;\n\t\t\tre(i, 1) = pa.second;\n\t\t}\n\t\treturn re;\n\t}\n};\n\n#endif"
  },
  {
    "path": "deepsort/KalmanTracker.h",
    "content": "#ifndef _KALMANTRACKERH_\n#define _KALMANTRACKERH_\n#include \"FeatureGetter/FeatureGetter.h\"\n#include \"kalman_filter.h\"\n#include <boost/shared_ptr.hpp>\n\nenum TrackState{\n    TS_NONE = 0,\n    Tentative,\n    Confirmed,\n    Deleted\n};\nclass KalmanTrackerN;\ntypedef boost::shared_ptr<KalmanTrackerN> KalmanTracker;\n\nclass KalmanTrackerN{\npublic:\n\tint time_since_update_ = 0;\n\tMEAN mean_;\n\tVAR covariance_;\n\tint track_id = 0;\n\tstd::vector<FEATURE> features_;\n\tint oriPos_;\nprivate:\n\tint hits_ = 0;\n\tint age_ = 0;\n\tTrackState state_ = TS_NONE;\n\tint _n_init_;\n\tint _max_age_;\n\npublic:\n    KalmanTrackerN(const MEAN &mean, \n\t\tconst VAR &covariance, \n\t\tint tid, \n\t\tint n_init, \n\t\tint max_age,\n        const FEATURE &feature, bool featureFull, int oriPos){\n        \n\t\tmean_ = mean;\n\t\tcovariance_ = covariance;\n\t\tthis->track_id = tid;\n\t\thits_ = 1;\n\t\tage_ = 1;\n\t\ttime_since_update_ = 0;\n\n\t\tstate_ = Tentative;\n\t\tif (featureFull) {\n\t\t\tfeatures_.push_back(feature);\n\t\t}\n\n\t\t_n_init_ = n_init;\n\t\t_max_age_ = max_age;\n\t\toriPos_ = oriPos;\n    }\n    DSBOX to_tlwh() const{\n\t\tDSBOX ret;\n\t\tret(0) = mean_(0);\n\t\tret(1) = mean_(1);\n\t\tret(2) = mean_(2);\n\t\tret(3) = mean_(3);\n\t\tret(2) *= ret(3);\n\t\tret(0) -= ret(2) / 2;\n\t\tret(1) -= ret(3) / 2;\n\t\treturn ret;\n    }\n    DSBOX to_tlbr(){\n\t\tDSBOX ret = to_tlwh();\n\t\tret(2) = ret(0) + ret(2);\n\t\tret(3) = ret(1) + ret(3);\n\t\treturn ret;\n    }\n    void predict(const KF &kalmanFilter, bool only=false){\n\t\tstd::pair<MEAN, VAR> pa = kalmanFilter.predict(mean_, covariance_);\n\t\tmean_ = pa.first;\n\t\tcovariance_ = pa.second;\n\t\tif(only){// 2017.10.18\n\t\t\treturn;\n\t\t}\n\t\tage_ += 1;\n\t\ttime_since_update_ += 1;\n    }\n    void update(const KF &kalmanFilter, const Detection &detection){\n\t\tDSBOX box = detection.to_xyah();\n\t\tstd::pair<MEAN, VAR> pa = kalmanFilter.update(\n\t\t\tmean_, covariance_, box);\n\t\tmean_ = pa.first;\n\t\tcovariance_ = pa.second;\n\t\tfeatures_.push_back(detection.feature_);\n\n\t\thits_ += 1;\n\t\ttime_since_update_ = 0;\n\t\tif (state_ == Tentative && hits_ >= _n_init_) {\n\t\t\tstate_ = Confirmed;\n\t\t}\n    }\n    void mark_missed(){\n        if(state_ == Tentative){\n            state_ = Deleted;\n        }\n        else if(time_since_update_ > _max_age_){\n            state_ = Deleted;\n        }\n    }\n    bool is_tentative(){\n\t\treturn state_ == Tentative;\n    }\n    bool is_confirmed()const {\n\t\treturn state_ == Confirmed;\n    }\n\n    bool is_deleted(){\n\t\treturn state_ == Deleted;\n    }\n};\n#endif\n\n\n"
  },
  {
    "path": "deepsort/iou_matching.h",
    "content": "#ifndef _IOUMH_\n#define _IOUMH_\n#include <vector>\n#include \"Detection.h\"\n#include <Eigen>\n#include \"linear_assignment.h\"\n#include <iterator>\n\nclass iou_matching{\nprivate:\n    static Eigen::VectorXf _iouFun(const DSBOX &bbox, const DSBOXS &candidates){\n\t\tEigen::VectorXf area_candidates(candidates.rows());\n\n\t\t//\n\t\tPT2 bbox_tl; bbox_tl(0, 0) = bbox[0]; bbox_tl(0, 1) = bbox[1];\n\t\tPT2 bbox_br; bbox_br(0, 0) = (bbox[0] + bbox[2]); bbox_br(0, 1) = (bbox[1] + bbox[3]);\n\t\tDYNAMICM ctl(candidates.rows(), 2);\n\t\tDYNAMICM cbr(candidates.rows(), 2);\n\t\tfor(int i = 0; i < candidates.rows(); i++){\n\t\t\tDSBOX candidate = candidates.row(i);\n\t\t\tPT2 candidates_tl;\n\t\t\tcandidates_tl(0, 0) = candidate[0]; candidates_tl(0, 1) = candidate[1];\n\t\t\tctl.row(i) = candidates_tl;\n\t\t\tPT2 candidates_br;\n\t\t\tcandidates_br(0, 0) = (candidate[0] + candidate[2]);\n\t\t\tcandidates_br(0, 1) = (candidate[1] + candidate[3]);\n\t\t\tcbr.row(i) = candidates_br;\n\t\t\t{\n\t\t\t\tarea_candidates(i) = candidate[2] * candidate[3];\n\t\t\t}\n\t\t}\n\t\t//std::cout << \"ctl-b:\\n\" << ctl << \"ctl-e\\n\" << std::endl;\n\t\t//std::cout << \"cbr-b:\\n\" << cbr << \"cbr-e\\n\" << std::endl;\n\t\tDYNAMICM tl(candidates.rows(), 2);\n\t\tfloat btl0 = bbox_tl(0, 0);\n\t\tfloat btl1 = bbox_tl(0, 1);\n\t\tfor (int i = 0; i < tl.rows(); i++) {\n\t\t\t//DYNAMICM row = tl.row(i);\n\t\t\tfloat m = cv::max(btl0, ctl(i, 0));\n\t\t\ttl(i, 0) = m;\n\t\t\tm = cv::max(btl1, ctl(i, 1));\n\t\t\ttl(i, 1) = m;\n\t\t\t//std::cout << \"tl-b:\\n\" << tl << \"tl-e\\n\" << std::endl;\n\t\t}\n\t\t//std::cout << \"tl-b:\\n\" << tl << \"tl-e\\n\" << std::endl;\n\t\tDYNAMICM br(candidates.rows(), 2);\n\t\tfloat bbr0 = bbox_br(0, 0);\n\t\tfloat bbr1 = bbox_br(0, 1);\n\t\tfor (int i = 0; i < br.rows(); i++) {\n\t\t\t//DYNAMICM row = br.row(i);\n\t\t\tbr(i, 0) = cv::min(bbr0, cbr(i, 0));\n\t\t\tbr(i, 1) = cv::min(bbr1, cbr(i, 1));\n\t\t}\n\t\t//std::cout << \"br-b:\\n\" << br << \"br-e\\n\" << std::endl;\n\t\tDYNAMICM wh(candidates.rows(), 2);\n\t\tEigen::VectorXf area_intersection(candidates.rows());\n\t\tfor (int i = 0; i < wh.rows(); i++) {\n\t\t\tfor (int j = 0; j < wh.cols(); j++) {\n\t\t\t\tfloat tmp = br(i, j) - tl(i, j);\n\t\t\t\twh(i, j) = tmp>0?tmp:0;\n\t\t\t}\n\t\t\tarea_intersection(i) = wh(i, 0)*wh(i, 1);\n\t\t}\n\t\t//std::cout << \"wh-b:\\n\" << wh << \"wh-e\\n\" << std::endl;\n\t\tfloat area_bbox = bbox(0, 2)*bbox(0, 3);\n\t\t\n\t\tEigen::VectorXf re(candidates.rows());\n\t\tfor (int i = 0; i < re.rows(); i++) {\n\t\t\tre(i) = area_intersection(i) / (area_bbox +\n\t\t\t\t\t\t\t\t\t\tarea_candidates(i) -\n\t\t\t\t\t\t\t\t\t\tarea_intersection(i));\n\t\t}\n\t\treturn re;\n    }\n\npublic:\n    static DYNAMICM getCostMatrixByIOU(const std::vector<KalmanTracker> &tracks, \n                    const std::vector<Detection> &detections, \n                    IDS *track_indicesi=NULL,\n                    IDS *detection_indicesi=NULL){\n\t\tIDS track_indices;\n\t\tif (track_indicesi == NULL) {\n\t\t\tfor (int i = 0; i < tracks.size(); i++) {\n\t\t\t\ttrack_indices.push_back(i);\n\t\t\t}\n\t\t}\n\t\telse {\n\t\t\ttrack_indices = *track_indicesi;\n\t\t}\n\n\t\tIDS detection_indices;\n\t\tif (detection_indicesi == NULL) {\n\t\t\tfor (int i = 0; i < detections.size(); i++) {\n\t\t\t\tdetection_indices.push_back(i);\n\t\t\t}\n\t\t}\n\t\telse {\n\t\t\tdetection_indices = *detection_indicesi;\n\t\t}\n\t\tDYNAMICM cost_matrix(track_indices.size(), detection_indices.size());\n\t\tfor (int row = 0; row < track_indices.size(); row++) {\n\t\t\tint track_idx = track_indices[row];\n\t\t\tif (tracks[track_idx]->time_since_update_ > 1) {\n\t\t\t\tfor (int c = 0; c < cost_matrix.cols(); c++) {\n\t\t\t\t\tcost_matrix(row, c) = INFTY_COST;\n\t\t\t\t}\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tDSBOX bbox = tracks[track_idx]->to_tlwh();\n\t\t\tDSBOXS candidates(detection_indices.size(), 4);\n\t\t\tfor (int k = 0; k < detection_indices.size(); k++) {\n\t\t\t\tDSBOX tmp = detections[detection_indices[k]].tlwh_;\n\t\t\t\tcandidates.row(k) = tmp;\n\t\t\t}\n\t\t\t//std::cout << \"mmm\" << candidates << \"vvvv\" << std::endl;\n\t\t\tEigen::VectorXf tmpm = _iouFun(bbox, candidates);\n\t\t\t//std::cout << \"tmpm--b\" << tmpm << \"tmpm--e\" << std::endl;\n\t\t\tauto tmp1 = tmpm.array();\n\t\t\tauto tmp2 = -(tmp1 - 1);\n\t\t\tcost_matrix.row(row) = tmp2.matrix();\n\t\t\t//std::cout << \"nnnnn\" << cost_matrix << \"uuuu\" << std::endl;\n\t\t}\n\t\treturn cost_matrix;\n    }\n};\n#endif\n"
  },
  {
    "path": "deepsort/kalman_filter.h",
    "content": "#ifndef PYKF\n#ifndef _KKALMANFILTERH_\n#define _KKALMANFILTERH_\n#include <boost/shared_ptr.hpp>\n\ntypedef Eigen::Matrix<float, 4, 8, Eigen::RowMajor> UPM;\n\nclass KF{\nprivate:\n    static boost::shared_ptr<KF> self_;\n    VAR _motion_mat_;\n    UPM _update_mat_;\n    double _std_weight_position_;\n    double _std_weight_velocity_;\npublic:\n\tstatic boost::shared_ptr<KF> Instance() {\n\t\tif (self_.get() == NULL) {\n\t\t\tself_.reset(new KF());\n\t\t}\n\t\treturn self_;\n\t}\n    bool Init(){\n        return true;\n    }\nprivate:        \n     KF(){\n        int ndim = 4;\n        double dt = 1.;\n\n        _motion_mat_ = Eigen::MatrixXf::Identity(8, 8);\n        for(int i = 0; i < ndim; i++){\n            _motion_mat_(i, ndim + i) = dt;\n        }\n        _update_mat_ = Eigen::MatrixXf::Identity(4, 8);\n        \n        _std_weight_position_ = 1. / 20;\n        _std_weight_velocity_ = 1. / 160;\n    }\n\tVAR Diag(const MEAN &mean) const{\n\t        VAR var;\n\t        for(int i = 0; i < var.rows(); i++){\n\t                for(int j = 0; j < var.cols(); j++){\n\t                        if(i == j){\n\t                                var(i, j) = mean(i);\n\t                        }\n\t                        else{\n\t                                var(i, j) = 0;\n\t                        }\n\t                }\n\t        }\n\t\treturn var;\n\t}\n\tNVAR NDiag(const NMEAN &mean) const{\n\t        NVAR var;\n\t        for(int i = 0; i < var.rows(); i++){\n\t                for(int j = 0; j < var.cols(); j++){\n\t                        if(i == j){\n\t                                var(i, j) = mean(i);\n\t                        }\n\t                        else{\n\t                                var(i, j) = 0;\n\t                        }\n\t                }\n\t        }\n\t\treturn var;\n\t}\npublic:\n    std::pair<MEAN, VAR> initiate(const DSBOX &measurement) const{\n        DSBOX mean_pos = measurement;\n        DSBOX mean_val;\n        for(int i = 0; i < 4; i++){\n            mean_val(i) = 0;\n        } \n        MEAN mean;\n        for(int i = 0; i < 8; i++){\n            if(i < 4){\n                mean(i) = mean_pos(i);\n                continue;\n            }\n            mean(i) = mean_val(i - 4);\n        }\n\n\n        MEAN std;\n        std(0) = 2 * _std_weight_position_ * measurement[3];\n        std(1) = 2 * _std_weight_position_ * measurement[3];\n        std(2) = 1e-2;\n        std(3) = 2 * _std_weight_position_ * measurement[3];\n        std(4) = 10 * _std_weight_velocity_ * measurement[3];\n        std(5) = 10 * _std_weight_velocity_ * measurement[3];\n        std(6) = 1e-5;\n        std(7) = 10 * _std_weight_velocity_ * measurement[3];\n\n\n        MEAN tmp = std.array().square();\n        \n        VAR var = Diag(tmp); \n#ifdef KLOG\n      \tstd::cout << \"[-4--]begin mean:\\n\"  << mean << \"\\n[-4--]end mean\\n\";\n\tstd::cout << \"[-4--]begin covariance:\\n\" << var << \"\\n[-4--]end covariance\\n\";\n#endif\n        std::pair<MEAN, VAR> pa;\n        pa.first = mean;\n        pa.second = var;\n        return pa;\n    }\n\n    std::pair<MEAN, VAR> predict(const MEAN &mean, const VAR &covariance) const{\n        DSBOX std_pos;\n        std_pos <<  \n            _std_weight_position_ * mean(3),\n            _std_weight_position_ * mean(3),\n            1e-2,\n            _std_weight_position_ * mean(3);\n\n        DSBOX std_vel;\n        std_vel << \n            _std_weight_velocity_ * mean(3),\n            _std_weight_velocity_ * mean(3),\n            1e-5,\n            _std_weight_velocity_ * mean(3);\n\n        MEAN mtmp;\n        for(int i = 0; i < 8; i++){\n            if(i < 4){\n                mtmp(i) = std_pos(i);\n                continue;\n            }\n            mtmp(i) = std_vel(i - 4);\n        }\n        MEAN tmp = mtmp.array().square();\n        VAR motion_cov = Diag(tmp);\n#ifdef KLOG \n        std::cout << \"[-3--]begin square\\n\";\n        std::cout << tmp << \"\\n\";\n        std::cout << \"[-3--]end square\\n\";\n#endif \n        //\n        MEAN mean1 = _motion_mat_ * mean.transpose();\n#ifdef KLOG\n\n        std::cout << \"[-3--]begin self._motion_mat_\\n\";\n        std::cout << _motion_mat_ << \"\\n\";\n        std::cout << \"[-3--]end self._motion_mat_\\n\";\n        std::cout << \"[-3--]begin covariance\\n\";\n        std::cout << covariance << \"\\n\";\n        std::cout << \"[-3--]end covariance\\n\";\n    \n        std::cout << \"[-3--]begin motion_cov:\\n\";\n        std::cout << motion_cov << \"\\n\";\n        std::cout << \"[-3--]end motion_cov:\\n\";\n#endif\n\n        VAR var = _motion_mat_ * covariance * (_motion_mat_.transpose());\n\tVAR var1 = var + motion_cov;\n#ifdef KLOG\n\n        std::cout << \"[-3--]begin covariance result\\n\";\n        std::cout << var1 << \"\\n\";\n        std::cout << \"[-3--]end covariance result\\n\";\n#endif \n        std::pair<MEAN, VAR> pa;\n        pa.first = mean1;\n        pa.second = var1;\n        return pa;\n    }\n\n    std::pair<MEAN, VAR> update(const MEAN &mean,  const VAR &covariance, const DSBOX &measurement) const{\n       \n        std::pair<NMEAN, NVAR> pa1 = _project(mean, covariance); \n        NMEAN projected_mean = pa1.first;\n        NVAR projected_cov = pa1.second;\n\n        auto ddd = covariance * (_update_mat_.transpose());\n        Eigen::Matrix<float, -1, 4> kalman_gain = projected_cov.llt().solve(ddd.transpose()).transpose(); // eg.8x4\n        Eigen::Matrix<float, 1, 4> innovation = measurement - projected_mean; //eg.1x4\n#ifdef KLOG\n\n        std::cout << \"[-1--]bbegin ddd\\n\";\n        std::cout << ddd << \"\\n\";\n        std::cout << \"[-1--]bend ddd\\n\";\n        std::cout << \"[-1--]bbegin kalman_gain\\n\";\n        std::cout << kalman_gain << \"\\n\";\n        std::cout << \"[-1--]bend kalman_gain\\n\";\n        std::cout << \"[-1--]begin measurement\\n\";\n        std::cout << measurement << \"\\n\";\n        std::cout << \"[-1--]end measurement\\n\";\n        std::cout << \"[-1--]begin projected_mean\\n\";\n        std::cout << projected_mean << \"\\n\";\n        std::cout << \"[-1--]end projectd_mean\\n\";\n        std::cout << \"[-1--]begin innovation\\n\";\n        std::cout << innovation << \"\\n\";\n        std::cout << \"[-1--]end innovation\\n\";\n        std::cout << \"[-1--]begin projected_cov\\n\";\n        std::cout << projected_cov << \"\\n\";\n        std::cout << \"[-1--]end projectd_cov\\n\";\n#endif\n\n\tauto tmp = innovation*(kalman_gain.transpose());\n        MEAN new_mean = (mean.array() + tmp.array()).matrix();\n        VAR new_covariance = covariance - kalman_gain*projected_cov*(kalman_gain.transpose());\n        std::pair<MEAN, VAR> pa2;\n        pa2.first = new_mean;\n        pa2.second = new_covariance;\n        return pa2;\n    }\n    Eigen::Matrix<float, 1, -1> gating_distance(const MEAN &meani, const VAR &covariance, \n                        const DSBOXS &measurements,\n                        bool only_position=false) const{\n        MEAN mean = meani; \n#ifdef KLOG\n\n        std::cout << \"[-2--]begin mean\\n\";\n        std::cout << mean << \"\\n\";\n        std::cout << \"[-2--]end mean\\n\";\n        std::cout << \"[-2--]begin covariance\\n\";\n        std::cout << covariance << \"\\n\";\n        std::cout << \"[-2--]end covariance\\n\";\n        std::cout << \"[-2--]begin measurements\\n\";\n        std::cout << measurements << \"\\n\";\n        std::cout << \"[-2--]end measurements\\n\";\n#endif \n        std::pair<NMEAN, NVAR>  pa1 = _project(mean, covariance);\n        if(only_position){\n             printf(\"not implement!!!exit\\n\");\n             exit(0);\n        }\n        NMEAN mean1 = pa1.first;\n        NVAR var1 = pa1.second;\n#ifdef KLOG\n\n        std::cout << \"[-2--]begin mean1\\n\";\n        std::cout << mean1 << \"\\n\";\n        std::cout << \"[-2--]end mean1\\n\";\n        std::cout << \"[-2--]begin covariance1\\n\";\n        std::cout << var1 << \"\\n\";\n        std::cout << \"[-2--]end covariance1\\n\";\n#endif \n\tint count = measurements.rows();\n\tDSBOXS d(count, 4);\n\tfor(int i = 0; i < count; i++){\n\t\td.row(i) = measurements.row(i) - mean1;\n\t}\n#ifdef KLOG\n\n        std::cout << \"[-2--]bbegin d\\n\";\n        std::cout << d << \"\\n\";\n        std::cout << \"[-2--]bend d\\n\";\n#endif\n \tEigen::Matrix<float, -1, -1, Eigen::RowMajor> factor = var1.llt().matrixL();\n        Eigen::Matrix<float, -1, -1> z = factor.triangularView<Eigen::Lower>().solve<Eigen::OnTheRight>(d).transpose();\n#ifdef KLOG\n\n        std::cout << \"[-2--]begin z\\n\";\n        std::cout << z << \"\\n\";\n        std::cout <<  \"[-2--]end z\\n\";\n#endif\n#if 1\n\tauto zz = ((z.array())*(z.array())).matrix();\n\tauto squared_maha = zz.colwise().sum();\n#else \n        Eigen::Matrix<float, 1, -1> squared_maha = z.colwise().sum();\n#endif\n#ifdef KLOG\n\n        std::cout << \"[-2--]begin squared_maha\\n\";\n        std::cout << squared_maha << \"\\n\";\n        std::cout << \"[-2--]end squared_maha\\n\";\n#endif \n        return squared_maha;\n\n    } \n    std::pair<NMEAN, NVAR> _project(const MEAN &mean, const VAR &covariance) const{\n        NMEAN std;\n        std <<\n            _std_weight_position_ * mean[3],\n            _std_weight_position_ * mean[3],\n            1e-1,\n            _std_weight_position_ * mean[3];\n        NMEAN mtmp = std.array().square();\n#ifdef KLOG\n\n        std::cout << \"[-0--]begin mtmp\\n\";\n        std::cout << mtmp << \"\\n\";\n        std::cout << \"[-0--]end mtmp\\n\";\n#endif\n\n        NVAR innovation_cov = NDiag(mtmp);\n        NMEAN mean1 = _update_mat_*mean.transpose();\n#ifdef KLOG\n\n        std::cout << \"[-0--]begin innovation_cov\\n\";\n        std::cout << innovation_cov << \"\\n\";\n        std::cout << \"[-0--]end innovation_cov\\n\";\n\n        std::cout << \"[-0--]begin var\\n\";\n        std::cout << covariance << \"\\n\";\n        std::cout << \"[-0--]end var\\n\";\n\n        std::cout << \"[-0--]begin _update_mat_\\n\";\n        std::cout << _update_mat_ << \"\\n\";\n        std::cout << \"[-0--]end _update_mat_\\n\";\n#endif\n\n        NVAR var = _update_mat_ * covariance * (_update_mat_.transpose());\n        NVAR var1 = var + innovation_cov;\n#ifdef KLOG\n\n        std::cout << \"[-0--]begin var1\\n\";\n        std::cout << var << \"\\n\";\n        std::cout << \"[-0--]end var1\\n\";\n#endif\n\n        std::pair<NMEAN, NVAR> pa;\n        pa.first = mean1;\n        pa.second = var1;\n        return pa;\n    }\n\n};\n\n#endif \n#endif\n\n\n\n"
  },
  {
    "path": "deepsort/linear_assignment.h",
    "content": "#ifndef _LASMH_\n#define _LASMH_\n#include <vector>\n#include \"Detection.h\"\n#include <Eigen>\n\n#include \"KalmanTracker.h\"\n#include \"FeatureGetter/FeatureGetter.h\"\n#include \"HungarianOper.h\"\n\n#include <sys/time.h>\nstatic int64_t line_gtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\nconst static int INFTY_COST = 1e+5;\nstruct RR {\n\tstd::vector<std::pair<int, int> > matches;\n\tIDS unmatched_detections;\n\tIDS unmatched_tracks;\n};\n\ntypedef DYNAMICM (*GetCostMarixFun)(const std::vector<KalmanTracker> &tracks,\n\tconst std::vector<Detection> &detections,\n\tIDS *track_indices,\n\tIDS *detection_indices);\n\ndouble chi2inv95[10] = {\n\t0,\n\t3.8415,\n\t5.9915,\n\t7.8147,\n\t9.4877,\n\t11.070,\n\t12.592,\n\t14.067,\n\t15.507,\n\t16.919 };\n\nclass linear_assignment{\npublic:\n    static RR min_cost_matching(\n            const GetCostMarixFun &getCostMarixFun, float max_distance,\n        const std::vector<KalmanTracker> &tracks, \n        const std::vector<Detection> &detections, \n        IDS *track_indicesi=NULL,\n        IDS *detection_indicesi=NULL){\n\t\tint64_t mintm1 = line_gtm();\n\t\tIDS track_indices;\n\t\tIDS detection_indices;\n\t\tif (track_indicesi == NULL) {\n\t\t\tfor (int i = 0; i < tracks.size(); i++) {\n\t\t\t\ttrack_indices.push_back(i);\n\t\t\t}\n\t\t}\n\t\telse {\n\t\t\ttrack_indices = *track_indicesi;\n\t\t}\n\n\t\tif (detection_indicesi == NULL) {\n\t\t\tfor (int i = 0; i < detections.size(); i++) {\n\t\t\t\tdetection_indices.push_back(i);\n\t\t\t}\n\t\t}\n\t\telse {\n\t\t\tdetection_indices = *detection_indicesi;\n\t\t}\n\n        if (detection_indices.empty() || track_indices.empty()) {\n            RR rr;\n            rr.unmatched_tracks = track_indices;\n            rr.unmatched_detections = detection_indices;\n            return rr;\n        }\n\tint64_t mintm2 = line_gtm();\n        // 5x5\n        DYNAMICM cost_matrix = getCostMarixFun(\n            tracks, detections, &track_indices, &detection_indices);\n\t\t//std::cout << \"\\n----mmmmm----\\n\" << cost_matrix << \"\\n----vvvvv-----\\n\" << std::endl;\n\t\tfor (int i = 0; i < cost_matrix.rows(); i++) {\n\t\t\tfor (int j = 0; j < cost_matrix.cols(); j++) {\n\t\t\t\tfloat tmp = cost_matrix(i, j);\n\t\t\t\tif (tmp > max_distance) {\n\t\t\t\t\tcost_matrix(i, j) = max_distance + 1e-5;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\tint64_t mintm3 = line_gtm();\n\t\t//std::cout << \"\\n----222mmmmm----\\n\" << cost_matrix << \"\\n----222vvvvv-----\\n\" << std::endl;\n\t\t//Eigen::Matrix<float, -1, 2> indices = KF::Instance()->LinearAssignmentForCpp(cost_matrix);\n\t\tEigen::Matrix<float, -1, 2> indices =\n\t\t\tHungarianOper::Solve(cost_matrix);\n\tint64_t mintm4 = line_gtm();\n\t\t//std::cout << \"indices:\\n\" << indices << std::endl;\n        //xyztodo: indices = linear_assignment(cost_matrix)\n        // (-1, 2)\n\n        RR rr;\n        // Ƿڵ2\n        for (int col = 0; col < detection_indices.size(); col++) {\n            // check if col is in indecis[:,1]\n            bool isIn = false;\n            for (int i = 0; i < indices.rows(); i++) {\n                int iid = indices(i, 1);\n                if (col == iid) {\n                    isIn = true;\n                    break;\n                }\n            }\n            if (!isIn) {\n                int detection_idx = detection_indices[col];\n                rr.unmatched_detections.push_back(detection_idx);\n            }\n        }\n        // Ƿڵ1\n        for (int row = 0; row < track_indices.size(); row++) {\n            // check of row is in indecis[:,0]\n            bool isIn = false;\n            for (int i = 0; i < indices.rows(); i++) {\n                int iid = indices(i, 0);\n                if (row == iid) {\n                    isIn = true;\n                    break;\n                }\n            }\n            if (!isIn) {\n                int track_idx = track_indices[row];\n                rr.unmatched_tracks.push_back(track_idx);\n            }\n        }\n        for (int i = 0; i < indices.rows(); i++) {\n\t\t\tint row = indices(i, 0);\n\t\t\tint col = indices(i, 1);\n            //for (int j = 0; j < indices.cols(); j++) {\n             //   int row = i;\n             //   int col = j;\n                int track_idx = track_indices[row];\n                int detection_idx = detection_indices[col];\n                if (cost_matrix(row, col) > max_distance) {\n                    rr.unmatched_tracks.push_back(track_idx);\n                    rr.unmatched_detections.push_back(detection_idx);\n                }\n                else {\n                    rr.matches.push_back(std::make_pair(track_idx, detection_idx));\n                }\n            //}\n        }\n\tint64_t mintm5 = line_gtm();\n\tstd::cout << \"min_cost_matching----mintm2-mintm1:\" << (mintm2-mintm1) <<\n\t\t\t\", mintm3-mintm1:\" << (mintm3-mintm1) << \n\t\t\t\", mintm4-mintm1:\" << (mintm4-mintm1) << \n\t\t\t\", mintm5-mintm1:\" << (mintm5-mintm1) << \"\\n\";\n        return rr;\n    }\n\n    static RR matching_cascade(\n        const GetCostMarixFun &getCostMarixFun, float max_distance,\n        int cascade_depth,\n        const std::vector<KalmanTracker> &tracks,\n        const std::vector<Detection> &detections,\n        IDS *track_indicesi = NULL,\n        IDS *detection_indicesi = NULL){\n\t\tint64_t ctm0 = line_gtm();\n\t\tIDS track_indices;\n\t\tIDS detection_indices;\n        if(track_indicesi == NULL) {\n\t\t\tfor (int i = 0; i < tracks.size(); i++) {\n\t\t\t\ttrack_indices.push_back(i);\n\t\t\t}\n        }\n\t\telse {\n\t\t\ttrack_indices = *track_indicesi;\n\t\t}\n\n        if (detection_indicesi == NULL) {\n\t\t\tfor (int i = 0; i < detections.size(); i++) {\n\t\t\t\tdetection_indices.push_back(i);\n\t\t\t}\n        }\n\t\telse {\n\t\t\tdetection_indices = *detection_indicesi;\n\t\t}\n        RR re;\n        std::map<int, int> tmpMap;\n        IDS unmatched_detections = detection_indices;\n        for (int level = 0; level < cascade_depth; level++) {\n\t\tint64_t ctm1 = line_gtm();\n            if (unmatched_detections.empty()) {\n                break;\n            }\n            IDS track_indices_l;\n            for (int k = 0; k < track_indices.size(); k++) {\n                if (tracks[k]->time_since_update_ == level + 1) {\n                    track_indices_l.push_back(track_indices[k]);\n                }\n            }\n            if (track_indices_l.empty()) {\n                continue;\n            }\n            RR rr = min_cost_matching(\n                getCostMarixFun, max_distance, tracks, detections,\n                &track_indices_l, &unmatched_detections);\n            unmatched_detections = rr.unmatched_detections;\n            for (int i = 0; i < rr.matches.size(); i++) {\n                std::pair<int, int> pa = rr.matches[i];\n                re.matches.push_back(pa);\n                tmpMap.insert(pa);\n            }\n\t\tint64_t ctm2 = line_gtm();\n\t\tstd::cout << \"cascade(\"<< level << \")----ctm2-ctm1:\" << (ctm2-ctm1) << \"\\n\";\n        }\n        re.unmatched_detections = unmatched_detections;\n        for (int i = 0; i < track_indices.size(); i++) {\n            int tid = track_indices[i];\n            std::map<int, int>::iterator it = tmpMap.find(tid);\n            if (it == tmpMap.end()) {\n                re.unmatched_tracks.push_back(tid);\n            }\n        }\n\tint64_t ctm4 = line_gtm();\n\tstd::cout << \"cascade----ctm4-ctm0:\" << (ctm4-ctm0) << \"\\n\";\n        return re;\n    }\n\n    static DYNAMICM gate_cost_matrix(\n        const KF &kalmanFilter,\n        DYNAMICM &cost_matrix, \n        const std::vector<KalmanTracker> &tracks,\n        const std::vector<Detection> &detections,\n        IDS track_indices,\n        IDS detection_indices,\n        int gated_cost=INFTY_COST, \n        bool only_position=false){\n        int gating_dim = only_position ? 2 : 4;\n\t\tfloat gating_threshold = chi2inv95[gating_dim];\n        DSBOXS measurements(detection_indices.size(), 4);\n        for (int i = 0; i < detection_indices.size(); i++) {\n            int pos = detection_indices[i];\n\t\t\tDSBOX tmp = detections[pos].to_xyah();\n\t\t\tmeasurements.row(i) = tmp;\n        }\n        for (int row = 0; row < track_indices.size(); row++) {\n            int track_idx = track_indices[row];\n            KalmanTracker track = tracks[track_idx];\n\t\t\t// gating_distance is a vector\n\t\t\tEigen::Matrix<float, 1, -1> gating_distance = kalmanFilter.gating_distance(\n                track->mean_, track->covariance_, measurements, only_position);\n\t\t\tfor (int i = 0; i < gating_distance.cols(); i++) {\n\t\t\t\t\tif (gating_distance(0, i) > gating_threshold) {\n\t\t\t\t\t\tcost_matrix(row, i) = gated_cost;\n\t\t\t\t\t}\n\t\t\t}\n\t\t\t//std::cout << \"\\nb--ggg\\n\" << cost_matrix << \"\\e--ggg\\n\";\n        }\n        return cost_matrix;\n    }\n};\n#endif\n"
  },
  {
    "path": "deepsort/munkres/adapters/adapter.cpp",
    "content": "/*\n *   Copyright (c) 2015 Miroslav Krajicek\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#include \"adapter.h\"\n"
  },
  {
    "path": "deepsort/munkres/adapters/adapter.h",
    "content": "/*\n *   Copyright (c) 2015 Miroslav Krajicek\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#ifndef _ADAPTER_H_\n#define _ADAPTER_H_\n\n#include \"../matrix.h\"\n#include \"../munkres.h\"\n\ntemplate<typename Data, class Container > class Adapter\n{\npublic:\n    virtual Matrix<Data> convertToMatrix(const Container &con) const = 0;\n    virtual void convertFromMatrix(Container &con, const Matrix<Data> &matrix) const = 0;\n    virtual void solve(Container &con)\n    {\n        auto matrix = convertToMatrix(con);\n        m_munkres.solve(matrix);\n        convertFromMatrix(con, matrix);\n    }\nprotected:\n    Munkres<Data> m_munkres;\n};\n\n#endif /* _ADAPTER_H_ */\n"
  },
  {
    "path": "deepsort/munkres/adapters/boostmatrixadapter.cpp",
    "content": "/*\n *   Copyright (c) 2015 Miroslav Krajicek\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#include \"boostmatrixadapter.h\"\n\ntemplate class BoostMatrixAdapter<double>;\ntemplate class BoostMatrixAdapter<float>;\ntemplate class BoostMatrixAdapter<int>;\n"
  },
  {
    "path": "deepsort/munkres/adapters/boostmatrixadapter.h",
    "content": "/*\n *   Copyright (c) 2015 Miroslav Krajicek\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#ifndef _BOOSTMATRIXADAPTER_H_\n#define _BOOSTMATRIXADAPTER_H_\n\n#include \"adapter.h\"\n#ifndef WIN32\n#include <boost/serialization/array_wrapper.hpp>\n#endif\n#include <boost/numeric/ublas/matrix.hpp>\n\ntemplate<typename Data> class BoostMatrixAdapter : public Adapter<Data,boost::numeric::ublas::matrix<Data> >\n{\npublic:\n    virtual Matrix<Data> convertToMatrix(const boost::numeric::ublas::matrix<Data> &boost_matrix) const override\n    {\n        const auto rows = boost_matrix.size1 ();\n          const auto columns = boost_matrix.size2 ();\n          Matrix <Data> matrix (rows, columns);\n          for (int i = 0; i < rows; ++i) {\n            for (int j = 0; j < columns; ++j) {\n              matrix (i, j) = boost_matrix (i, j);\n            }\n          }\n          return matrix;\n    }\n\n    virtual void convertFromMatrix(boost::numeric::ublas::matrix<Data> &boost_matrix,const Matrix<Data> &matrix) const override\n    {\n        const auto rows = matrix.rows();\n          const auto columns = matrix.columns();\n          for (int i = 0; i < rows; ++i) {\n            for (int j = 0; j < columns; ++j) {\n              boost_matrix (i, j) = matrix (i, j);\n            }\n          }\n    }\n};\n\n#endif /* _BOOSTMATRIXADAPTER_H_ */\n"
  },
  {
    "path": "deepsort/munkres/matrix.cpp",
    "content": "/*\n *   Copyright (c) 2007 John Weaver\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#include \"matrix.h\"\n\n#include <cassert>\n#include <cstdlib>\n#include <algorithm>\n\n/*export*/ template <class T>\nMatrix<T>::Matrix() {\n  m_rows = 0;\n  m_columns = 0;\n  m_matrix = nullptr;\n}\n\n\n/*export*/ template <class T>\nMatrix<T>::Matrix(const std::initializer_list<std::initializer_list<T>> init) {\n  m_matrix = nullptr;\n  m_rows = init.size();\n  if ( m_rows == 0 ) {\n    m_columns = 0;\n  } else {\n    m_columns = init.begin()->size();\n    if ( m_columns > 0 ) {\n      resize(m_rows, m_columns);\n    }\n  }\n\n  size_t i = 0, j;\n  for ( auto row = init.begin() ; row != init.end() ; ++row, ++i ) {\n    assert ( row->size() == m_columns && \"All rows must have the same number of columns.\" );\n    j = 0;\n    for ( auto value = row->begin() ; value != row->end() ; ++value, ++j ) {\n      m_matrix[i][j] = *value;\n    }\n  }\n}\n\n/*export*/ template <class T>\nMatrix<T>::Matrix(const Matrix<T> &other) {\n  if ( other.m_matrix != nullptr ) {\n    // copy arrays\n    m_matrix = nullptr;\n    resize(other.m_rows, other.m_columns);\n    for ( size_t i = 0 ; i < m_rows ; i++ ) {\n      for ( size_t j = 0 ; j < m_columns ; j++ ) {\n        m_matrix[i][j] = other.m_matrix[i][j];\n      }\n    }\n  } else {\n    m_matrix = nullptr;\n    m_rows = 0;\n    m_columns = 0;\n  }\n}\n\n/*export*/ template <class T>\nMatrix<T>::Matrix(const size_t rows, const size_t columns) {\n  m_matrix = nullptr;\n  resize(rows, columns);\n}\n\n/*export*/ template <class T>\nMatrix<T> &\nMatrix<T>::operator= (const Matrix<T> &other) {\n  if ( other.m_matrix != nullptr ) {\n    // copy arrays\n    resize(other.m_rows, other.m_columns);\n    for ( size_t i = 0 ; i < m_rows ; i++ ) {\n      for ( size_t j = 0 ; j < m_columns ; j++ ) {\n          m_matrix[i][j] = other.m_matrix[i][j];\n      }\n    }\n  } else {\n    // free arrays\n    for ( size_t i = 0 ; i < m_columns ; i++ ) {\n      delete [] m_matrix[i];\n    }\n\n    delete [] m_matrix;\n\n    m_matrix = nullptr;\n    m_rows = 0;\n    m_columns = 0;\n  }\n  \n  return *this;\n}\n\n/*export*/ template <class T>\nMatrix<T>::~Matrix() {\n  if ( m_matrix != nullptr ) {\n    // free arrays\n    for ( size_t i = 0 ; i < m_rows ; i++ ) {\n      delete [] m_matrix[i];\n    }\n\n    delete [] m_matrix;\n  }\n  m_matrix = nullptr;\n}\n\n/*export*/ template <class T>\nvoid\nMatrix<T>::resize(const size_t rows, const size_t columns, const T default_value) {\n  assert ( rows > 0 && columns > 0 && \"Columns and rows must exist.\" );\n\n  if ( m_matrix == nullptr ) {\n    // alloc arrays\n    m_matrix = new T*[rows]; // rows\n    for ( size_t i = 0 ; i < rows ; i++ ) {\n      m_matrix[i] = new T[columns]; // columns\n    }\n\n    m_rows = rows;\n    m_columns = columns;\n    clear();\n  } else {\n    // save array pointer\n    T **new_matrix;\n    // alloc new arrays\n    new_matrix = new T*[rows]; // rows\n    for ( size_t i = 0 ; i < rows ; i++ ) {\n      new_matrix[i] = new T[columns]; // columns\n      for ( size_t j = 0 ; j < columns ; j++ ) {\n        new_matrix[i][j] = default_value;\n      }\n    }\n\n    // copy data from saved pointer to new arrays\n    size_t minrows = XYZMIN(rows, m_rows);\n    size_t mincols = XYZMIN(columns, m_columns);\n    for ( size_t x = 0 ; x < minrows ; x++ ) {\n      for ( size_t y = 0 ; y < mincols ; y++ ) {\n        new_matrix[x][y] = m_matrix[x][y];\n      }\n    }\n\n    // delete old arrays\n    if ( m_matrix != nullptr ) {\n      for ( size_t i = 0 ; i < m_rows ; i++ ) {\n        delete [] m_matrix[i];\n      }\n\n      delete [] m_matrix;\n    }\n\n    m_matrix = new_matrix;\n  }\n\n  m_rows = rows;\n  m_columns = columns;\n}\n\n/*export*/ template <class T>\nvoid\nMatrix<T>::clear() {\n  assert( m_matrix != nullptr );\n\n  for ( size_t i = 0 ; i < m_rows ; i++ ) {\n    for ( size_t j = 0 ; j < m_columns ; j++ ) {\n      m_matrix[i][j] = 0;\n    }\n  }\n}\n\n/*export*/ template <class T>\ninline T&\nMatrix<T>::operator ()(const size_t x, const size_t y) {\n  assert ( x < m_rows );\n  assert ( y < m_columns );\n  assert ( m_matrix != nullptr );\n  return m_matrix[x][y];\n}\n\n\n/*export*/ template <class T>\ninline const T&\nMatrix<T>::operator ()(const size_t x, const size_t y) const {\n  assert ( x < m_rows );\n  assert ( y < m_columns );\n  assert ( m_matrix != nullptr );\n  return m_matrix[x][y];\n}\n\n\n/*export*/ template <class T>\nconst T\nMatrix<T>::mmin() const {\n  assert( m_matrix != nullptr );\n  assert ( m_rows > 0 );\n  assert ( m_columns > 0 );\n  T min = m_matrix[0][0];\n\n  for ( size_t i = 0 ; i < m_rows ; i++ ) {\n    for ( size_t j = 0 ; j < m_columns ; j++ ) {\n      min = std::min<T>(min, m_matrix[i][j]);\n    }\n  }\n\n  return min;\n}\n\n\n/*export*/ template <class T>\nconst T\nMatrix<T>::mmax() const {\n  assert( m_matrix != nullptr );\n  assert ( m_rows > 0 );\n  assert ( m_columns > 0 );\n  T max = m_matrix[0][0];\n\n  for ( size_t i = 0 ; i < m_rows ; i++ ) {\n    for ( size_t j = 0 ; j < m_columns ; j++ ) {\n      max = std::max<T>(max, m_matrix[i][j]);\n    }\n  }\n\n  return max;\n}\n"
  },
  {
    "path": "deepsort/munkres/matrix.h",
    "content": "/*\n *   Copyright (c) 2007 John Weaver\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#ifndef _MATRIX_H_\n#define _MATRIX_H_\n\n#include <initializer_list>\n#include <cstdlib>\n#include <ostream>\n\n#define XYZMIN(x, y) (x)<(y)?(x):(y)\n#define XYZMAX(x, y) (x)>(y)?(x):(y)\n\ntemplate <class T>\nclass Matrix {\npublic:\n  Matrix();\n  Matrix(const size_t rows, const size_t columns);\n  Matrix(const std::initializer_list<std::initializer_list<T>> init);\n  Matrix(const Matrix<T> &other);\n  Matrix<T> & operator= (const Matrix<T> &other);\n  ~Matrix();\n  // all operations modify the matrix in-place.\n  void resize(const size_t rows, const size_t columns, const T default_value = 0);\n  void clear();\n  T& operator () (const size_t x, const size_t y);\n  const T& operator () (const size_t x, const size_t y) const;\n  const T mmin() const;\n  const T mmax() const;\n  inline size_t minsize() { return ((m_rows < m_columns) ? m_rows : m_columns); }\n  inline size_t columns() const { return m_columns;}\n  inline size_t rows() const { return m_rows;}\n\n  friend std::ostream& operator<<(std::ostream& os, const Matrix &matrix)\n  {\n      os << \"Matrix:\" << std::endl;\n      for (size_t row = 0 ; row < matrix.rows() ; row++ )\n      {\n          for (size_t col = 0 ; col < matrix.columns() ; col++ )\n          {\n              os.width(8);\n              os << matrix(row, col) << \",\";\n          }\n          os << std::endl;\n      }\n      return os;\n  }\n\nprivate:\n  T **m_matrix;\n  size_t m_rows;\n  size_t m_columns;\n};\n\n#ifndef USE_EXPORT_KEYWORD\n#include \"matrix.cpp\"\n//#define export /*export*/\n#endif\n\n#endif /* !defined(_MATRIX_H_) */\n\n"
  },
  {
    "path": "deepsort/munkres/munkres.cpp",
    "content": "/*\n *   Copyright (c) 2007 John Weaver\n *   Copyright (c) 2015 Miroslav Krajicek\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#include \"munkres.h\"\n\ntemplate class Munkres<double>;\ntemplate class Munkres<float>;\ntemplate class Munkres<int>;\n\n"
  },
  {
    "path": "deepsort/munkres/munkres.h",
    "content": "/*\n *   Copyright (c) 2007 John Weaver\n *   Copyright (c) 2015 Miroslav Krajicek\n *\n *   This program is free software; you can redistribute it and/or modify\n *   it under the terms of the GNU General Public License as published by\n *   the Free Software Foundation; either version 2 of the License, or\n *   (at your option) any later version.\n *\n *   This program is distributed in the hope that it will be useful,\n *   but WITHOUT ANY WARRANTY; without even the implied warranty of\n *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n *   GNU General Public License for more details.\n *\n *   You should have received a copy of the GNU General Public License\n *   along with this program; if not, write to the Free Software\n *   Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA\n */\n\n#if !defined(_MUNKRES_H_)\n#define _MUNKRES_H_\n\n#include \"matrix.h\"\n\n#include <list>\n#include <utility>\n#include <iostream>\n#include <cmath>\n#include <limits>\n\n\ntemplate<typename Data> class Munkres\n{\n    static constexpr int NORMAL = 0;\n    static constexpr int STAR   = 1;\n    static constexpr int PRIME  = 2;\npublic:\n\n    /*\n     *\n     * Linear assignment problem solution\n     * [modifies matrix in-place.]\n     * matrix(row,col): row major format assumed.\n     *\n     * Assignments are remaining 0 values\n     * (extra 0 values are replaced with -1)\n     *\n     */\n    void solve(Matrix<Data> &m) {\n        const size_t rows = m.rows(),\n                columns = m.columns(),\n                size = XYZMAX(rows, columns);\n\n#ifdef DEBUG\n        std::cout << \"Munkres input: \" << m << std::endl;\n#endif\n\n        // Copy input matrix\n        this->matrix = m;\n\n        if ( rows != columns ) {\n            // If the input matrix isn't square, make it square\n            // and fill the empty values with the largest value present\n            // in the matrix.\n            matrix.resize(size, size, matrix.mmax());\n        }\n\n\n        // STAR == 1 == starred, PRIME == 2 == primed\n        mask_matrix.resize(size, size);\n\n        row_mask = new bool[size];\n        col_mask = new bool[size];\n        for ( size_t i = 0 ; i < size ; i++ ) {\n            row_mask[i] = false;\n        }\n\n        for ( size_t i = 0 ; i < size ; i++ ) {\n            col_mask[i] = false;\n        }\n\n        // Prepare the matrix values...\n\n        // If there were any infinities, replace them with a value greater\n        // than the maximum value in the matrix.\n        replace_infinites(matrix);\n\n        minimize_along_direction(matrix, rows >= columns);\n        minimize_along_direction(matrix, rows <  columns);\n\n        // Follow the steps\n        int step = 1;\n        while ( step ) {\n            switch ( step ) {\n            case 1:\n                step = step1();\n                // step is always 2\n                break;\n            case 2:\n                step = step2();\n                // step is always either 0 or 3\n                break;\n            case 3:\n                step = step3();\n                // step in [3, 4, 5]\n                break;\n            case 4:\n                step = step4();\n                // step is always 2\n                break;\n            case 5:\n                step = step5();\n                // step is always 3\n                break;\n            }\n        }\n\n        // Store results\n        for ( size_t row = 0 ; row < size ; row++ ) {\n            for ( size_t col = 0 ; col < size ; col++ ) {\n                if ( mask_matrix(row, col) == STAR ) {\n                    matrix(row, col) = 0;\n                } else {\n                    matrix(row, col) = -1;\n                }\n            }\n        }\n\n#ifdef DEBUG\n        std::cout << \"Munkres output: \" << matrix << std::endl;\n#endif\n        // Remove the excess rows or columns that we added to fit the\n        // input to a square matrix.\n        matrix.resize(rows, columns);\n\n        m = matrix;\n\n        delete [] row_mask;\n        delete [] col_mask;\n    }\n\n    static void replace_infinites(Matrix<Data> &matrix) {\n      const size_t rows = matrix.rows(),\n                columns = matrix.columns();\n      //assert( rows > 0 && columns > 0 );\n      double max = matrix(0, 0);\n      constexpr auto infinity = std::numeric_limits<double>::infinity();\n\n      // Find the greatest value in the matrix that isn't infinity.\n      for ( size_t row = 0 ; row < rows ; row++ ) {\n        for ( size_t col = 0 ; col < columns ; col++ ) {\n          if ( matrix(row, col) != infinity ) {\n            if ( max == infinity ) {\n              max = matrix(row, col);\n            } else {\n              max = XYZMAX(max, matrix(row, col));\n            }\n          }\n        }\n      }\n\n      // a value higher than the maximum value present in the matrix.\n      if ( max == infinity ) {\n        // This case only occurs when all values are infinite.\n        max = 0;\n      } else {\n        max++;\n      }\n\n      for ( size_t row = 0 ; row < rows ; row++ ) {\n        for ( size_t col = 0 ; col < columns ; col++ ) {\n          if ( matrix(row, col) == infinity ) {\n            matrix(row, col) = max;\n          }\n        }\n      }\n\n    }\n    static void minimize_along_direction(Matrix<Data> &matrix, const bool over_columns) {\n      const size_t outer_size = over_columns ? matrix.columns() : matrix.rows(),\n                   inner_size = over_columns ? matrix.rows() : matrix.columns();\n\n      // Look for a minimum value to subtract from all values along\n      // the \"outer\" direction.\n      for ( size_t i = 0 ; i < outer_size ; i++ ) {\n        double min = over_columns ? matrix(0, i) : matrix(i, 0);\n\n        // As long as the current minimum is greater than zero,\n        // keep looking for the minimum.\n        // Start at one because we already have the 0th value in min.\n        for ( size_t j = 1 ; j < inner_size && min > 0 ; j++ ) {\n          min = XYZMIN(\n            min,\n            over_columns ? matrix(j, i) : matrix(i, j));\n        }\n\n        if ( min > 0 ) {\n          for ( size_t j = 0 ; j < inner_size ; j++ ) {\n            if ( over_columns ) {\n              matrix(j, i) -= min;\n            } else {\n              matrix(i, j) -= min;\n            }\n          }\n        }\n      }\n    }\n\nprivate:\n\n  inline bool find_uncovered_in_matrix(const double item, size_t &row, size_t &col) const {\n    const size_t rows = matrix.rows(),\n              columns = matrix.columns();\n\n    for ( row = 0 ; row < rows ; row++ ) {\n      if ( !row_mask[row] ) {\n        for ( col = 0 ; col < columns ; col++ ) {\n          if ( !col_mask[col] ) {\n            if ( matrix(row,col) == item ) {\n              return true;\n            }\n          }\n        }\n      }\n    }\n\n    return false;\n  }\n\n  bool pair_in_list(const std::pair<size_t,size_t> &needle, const std::list<std::pair<size_t,size_t> > &haystack) {\n    for ( std::list<std::pair<size_t,size_t> >::const_iterator i = haystack.begin() ; i != haystack.end() ; i++ ) {\n      if ( needle == *i ) {\n        return true;\n      }\n    }\n\n    return false;\n  }\n\n  int step1() {\n    const size_t rows = matrix.rows(),\n              columns = matrix.columns();\n\n    for ( size_t row = 0 ; row < rows ; row++ ) {\n      for ( size_t col = 0 ; col < columns ; col++ ) {\n        if ( 0 == matrix(row, col) ) {\n          for ( size_t nrow = 0 ; nrow < row ; nrow++ )\n            if ( STAR == mask_matrix(nrow,col) )\n              goto next_column;\n\n          mask_matrix(row,col) = STAR;\n          goto next_row;\n        }\n        next_column:;\n      }\n      next_row:;\n    }\n\n    return 2;\n  }\n\n  int step2() {\n    const size_t rows = matrix.rows(),\n              columns = matrix.columns();\n    size_t covercount = 0;\n\n    for ( size_t row = 0 ; row < rows ; row++ )\n      for ( size_t col = 0 ; col < columns ; col++ )\n        if ( STAR == mask_matrix(row, col) ) {\n          col_mask[col] = true;\n          covercount++;\n        }\n\n    if ( covercount >= matrix.minsize() ) {\n  #ifdef DEBUG\n      std::cout << \"Final cover count: \" << covercount << std::endl;\n  #endif\n      return 0;\n    }\n\n  #ifdef DEBUG\n    std::cout << \"Munkres matrix has \" << covercount << \" of \" << matrix.minsize() << \" Columns covered:\" << std::endl;\n    std::cout << matrix << std::endl;\n  #endif\n\n\n    return 3;\n  }\n\n  int step3() {\n    /*\n    Main Zero Search\n\n     1. Find an uncovered Z in the distance matrix and prime it. If no such zero exists, go to Step 5\n     2. If No Z* exists in the row of the Z', go to Step 4.\n     3. If a Z* exists, cover this row and uncover the column of the Z*. Return to Step 3.1 to find a new Z\n    */\n    if ( find_uncovered_in_matrix(0, saverow, savecol) ) {\n      mask_matrix(saverow,savecol) = PRIME; // prime it.\n    } else {\n      return 5;\n    }\n\n    for ( size_t ncol = 0 ; ncol < matrix.columns() ; ncol++ ) {\n      if ( mask_matrix(saverow,ncol) == STAR ) {\n        row_mask[saverow] = true; //cover this row and\n        col_mask[ncol] = false; // uncover the column containing the starred zero\n        return 3; // repeat\n      }\n    }\n\n    return 4; // no starred zero in the row containing this primed zero\n  }\n\n  int step4() {\n    const size_t rows = matrix.rows(),\n              columns = matrix.columns();\n\n    // seq contains pairs of row/column values where we have found\n    // either a star or a prime that is part of the ``alternating sequence``.\n    std::list<std::pair<size_t,size_t> > seq;\n    // use saverow, savecol from step 3.\n    std::pair<size_t,size_t> z0(saverow, savecol);\n    seq.insert(seq.end(), z0);\n\n    // We have to find these two pairs:\n    std::pair<size_t,size_t> z1(-1, -1);\n    std::pair<size_t,size_t> z2n(-1, -1);\n\n    size_t row, col = savecol;\n    /*\n    Increment Set of Starred Zeros\n\n     1. Construct the ``alternating sequence'' of primed and starred zeros:\n\n           Z0 : Unpaired Z' from Step 4.2\n           Z1 : The Z* in the column of Z0\n           Z[2N] : The Z' in the row of Z[2N-1], if such a zero exists\n           Z[2N+1] : The Z* in the column of Z[2N]\n\n        The sequence eventually terminates with an unpaired Z' = Z[2N] for some N.\n    */\n    bool madepair;\n    do {\n      madepair = false;\n      for ( row = 0 ; row < rows ; row++ ) {\n        if ( mask_matrix(row,col) == STAR ) {\n          z1.first = row;\n          z1.second = col;\n          if ( pair_in_list(z1, seq) ) {\n            continue;\n          }\n\n          madepair = true;\n          seq.insert(seq.end(), z1);\n          break;\n        }\n      }\n\n      if ( !madepair )\n        break;\n\n      madepair = false;\n\n      for ( col = 0 ; col < columns ; col++ ) {\n        if ( mask_matrix(row, col) == PRIME ) {\n          z2n.first = row;\n          z2n.second = col;\n          if ( pair_in_list(z2n, seq) ) {\n            continue;\n          }\n          madepair = true;\n          seq.insert(seq.end(), z2n);\n          break;\n        }\n      }\n    } while ( madepair );\n\n    for ( std::list<std::pair<size_t,size_t> >::iterator i = seq.begin() ;\n        i != seq.end() ;\n        i++ ) {\n      // 2. Unstar each starred zero of the sequence.\n      if ( mask_matrix(i->first,i->second) == STAR )\n        mask_matrix(i->first,i->second) = NORMAL;\n\n      // 3. Star each primed zero of the sequence,\n      // thus increasing the number of starred zeros by one.\n      if ( mask_matrix(i->first,i->second) == PRIME )\n        mask_matrix(i->first,i->second) = STAR;\n    }\n\n    // 4. Erase all primes, uncover all columns and rows,\n    for ( size_t row = 0 ; row < mask_matrix.rows() ; row++ ) {\n      for ( size_t col = 0 ; col < mask_matrix.columns() ; col++ ) {\n        if ( mask_matrix(row,col) == PRIME ) {\n          mask_matrix(row,col) = NORMAL;\n        }\n      }\n    }\n\n    for ( size_t i = 0 ; i < rows ; i++ ) {\n      row_mask[i] = false;\n    }\n\n    for ( size_t i = 0 ; i < columns ; i++ ) {\n      col_mask[i] = false;\n    }\n\n    // and return to Step 2.\n    return 2;\n  }\n\n  int step5() {\n    const size_t rows = matrix.rows(),\n              columns = matrix.columns();\n    /*\n    New Zero Manufactures\n\n     1. Let h be the smallest uncovered entry in the (modified) distance matrix.\n     2. Add h to all covered rows.\n     3. Subtract h from all uncovered columns\n     4. Return to Step 3, without altering stars, primes, or covers.\n    */\n\tdouble h = 100000;//xyzoylz std::numeric_limits<double>::max();\n    for ( size_t row = 0 ; row < rows ; row++ ) {\n      if ( !row_mask[row] ) {\n        for ( size_t col = 0 ; col < columns ; col++ ) {\n          if ( !col_mask[col] ) {\n            if ( h > matrix(row, col) && matrix(row, col) != 0 ) {\n              h = matrix(row, col);\n            }\n          }\n        }\n      }\n    }\n\n    for ( size_t row = 0 ; row < rows ; row++ ) {\n      if ( row_mask[row] ) {\n        for ( size_t col = 0 ; col < columns ; col++ ) {\n          matrix(row, col) += h;\n        }\n      }\n    }\n\n    for ( size_t col = 0 ; col < columns ; col++ ) {\n      if ( !col_mask[col] ) {\n        for ( size_t row = 0 ; row < rows ; row++ ) {\n          matrix(row, col) -= h;\n        }\n      }\n    }\n\n    return 3;\n  }\n\n  Matrix<int> mask_matrix;\n  Matrix<Data> matrix;\n  bool *row_mask;\n  bool *col_mask;\n  size_t saverow = 0, savecol = 0;\n};\n\n\n#endif /* !defined(_MUNKRES_H_) */\n"
  },
  {
    "path": "deepsort/nn_matching.h",
    "content": "#ifndef _NNMATCHINGH_\n#define _NNMATCHINGH_\n#include <vector>\n#include \"Detection.h\"\n#include <Eigen>\n#include <map>\n#include <sys/time.h>\n\n#ifdef USETBB\n#include <tbb.h>\n#endif\n#include <map>\n#include <boost/shared_ptr.hpp>\n#include <boost/thread/mutex.hpp>\n\n\nstatic int64_t nn_gtm() {\n\tstruct timeval tm;\n\tgettimeofday(&tm, 0);\n\tint64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;\n\treturn re;\n}\nEigen::VectorXf _nn_cosine_distance(const FEATURESS &x, \n\tconst FEATURESS &y){\n\tint64_t nntm1 = nn_gtm();\t\n\tFEATURESS a = x;\n\tFEATURESS b = y;\n\t//std::cout << \"a---b\\n\" << a << \"\\na----e\\n\" << std::endl;\n\t//std::cout << \"b---b\\n\" << b << \"\\nb----e\\n\" << std::endl;\n\n\tfor (int row = 0; row < a.rows(); row++) {\n\t\tauto t = a.row(row);\n\t\tt = t / t.norm();\n\t\ta.row(row) = t;\n\t}\n\tfor (int row = 0; row < b.rows(); row++) {\n\t\tauto t = b.row(row);\n\t\tt = t / t.norm();\n\t\tb.row(row) = t;\n\t}\n\t//std::cout << \"a---b\\n\" << a << \"\\na----e\\n\" << std::endl;\n\t//std::cout << \"b---b\\n\" << b << \"\\nb----e\\n\" << std::endl;\n\tauto tmp = a*b.transpose();\n\tauto tmp1 = tmp.array();\n\tauto tmp2 = -(tmp1 - 1);\n\tDYNAMICM distances = tmp2.matrix();\n\tEigen::VectorXf re(distances.cols());\n#ifdef WIN32\n\tauto rea = re.array();\n\tfor (int col = 0; col < distances.cols(); col++) {\n\t\tauto cc = distances.col(col);\n\t\tfloat min = cc.minCoeff();\n\t\trea.row(col) = min;\n\t}\n\tre = rea.matrix();\n#else\n\tfor (int col = 0; col < distances.cols(); col++) {\n\t\tauto cc = distances.col(col);\n\t\tfloat min = cc.minCoeff();\n\t\tre(col) = min;\n\t}\n#endif\n\tint64_t nntm2 = nn_gtm();\t\n\tstd::cout << \"_nn_cosine_distance(\" << x.rows() << \",\" << y.rows() << \")----nntm2-nntm1:\" << (nntm2-nntm1) << \"\\n\";\n\t//std::cout << \"re---b\\n\" << re << \"\\nre----e\\n\" << std::endl;\n\treturn re;\n}\n\nclass NearestNeighborDistanceMetric{\nprivate:\n    static boost::shared_ptr<NearestNeighborDistanceMetric> self_;\n    float matching_threshold_ = 0;\n    int budget_ = 0;\n    std::map<int, std::vector<FEATURE> > samples_;\npublic:\n\tfloat matching_threshold() {\n\t\treturn matching_threshold_;\n\t}\n    static boost::shared_ptr<NearestNeighborDistanceMetric> Instance(){\n        if(self_.get() == NULL){\n            self_.reset(new NearestNeighborDistanceMetric());\n        }\n        return self_;\n    }\n    void Init(float matching_threshold, int budget){\n\t\tmatching_threshold_ = matching_threshold;\n\t\tbudget_ = budget;\n    }\n    \n    void partial_fit(const FEATURESS &features, \n                        const IDS &ids, \n                        const IDS &active_ids){\n        //samples_.clear();\n        for(int i = 0; i < features.rows(); i++){\n            FEATURE feature = features.row(i);\n            int iid = ids[i];\n            //\n            {\n                bool isIn = false;\n                for(int k = 0; k < active_ids.size(); k++){\n                    if(iid == active_ids[k]){\n                        isIn = true;\n                        break;\n                    }\n                }\n                if(!isIn){\n                    continue;\n                }\n            }\n            //\n            std::map<int, std::vector<FEATURE>>::iterator it = samples_.find(iid);\n            if(it == samples_.end()){\n                std::vector<FEATURE> tmps;\n                samples_.insert(std::make_pair(iid, tmps));\n                it = samples_.find(iid);\n            }\n\t\t\tit->second.push_back(feature);\n#if 1\n\t\t\tstd::vector<FEATURE>::iterator ii = it->second.begin();\n\t\t\tif(it->second.size() > budget_){\n\t\t\t\tit->second.erase(ii);\n\t\t\t}\n#else\n            /*if(samples_.size() > budget_){\n                samples_.erase(samples_.begin());\n            }*/\n#endif\n        }\n    }\n    struct DDS{\n    public:\n\tvoid Push(int pos, const Eigen::VectorXf &dd){\n\t\tboost::mutex::scoped_lock lock(mutex_);\n\t\tdds_.push_back(\n\t\t\tstd::make_pair(pos, dd)\n\t\t);\n\t}\n\tvoid Get(std::vector<std::pair<int, Eigen::VectorXf> > &dds){\n\t\tdds = dds_;\n\t}\n    private:\n\tstd::vector<std::pair<int, Eigen::VectorXf> > dds_;\n\tboost::mutex mutex_;\n    };\n\n    DYNAMICM distance(const FEATURESS &features, const IDS &ids){\n#ifdef USETBB\n\tstatic DYNAMICM cost_matrix;\n\tcost_matrix = DYNAMICM(ids.size(), features.rows());\n\tint64_t dtm0 = nn_gtm();\n\n\tusing namespace tbb;\n \tparallel_for( blocked_range<size_t>(0,ids.size()),\n                [=](const blocked_range<size_t> &r){\n                        for(int i = r.begin(); i != r.end(); ++i){\n \t\t\t        int iid = ids[i];\n\t\t\t\tstd::vector<FEATURE> &ftsvec = samples_[iid];\n\t\t\t\tFEATURESS fts(ftsvec.size(), 128);\n\t\t\t\tfor (int k = 0; k < ftsvec.size(); k++) {\n\t\t\t\t\tfts.row(k) = ftsvec[k];\n\t\t\t\t}\n\t\t\t\tint64_t dtm1 = nn_gtm();\n\t\t\t\tcost_matrix.row(i) = _nn_cosine_distance(fts, features);\n\t\t\t\tint64_t dtm2 = nn_gtm();\n\t\t\t\tstd::cout << \"distance(\" << iid<< \")----dtm2-dtm1:\" << (dtm2-dtm1) << \"\\n\";\n                        }\n                   }\n                );\n#else\n\tstatic DYNAMICM cost_matrix;\n\tcost_matrix = DYNAMICM(ids.size(), features.rows());\n\tint64_t dtm0 = nn_gtm();\n\tDDS dds;\n\t#pragma omp parallel for\n        for(int i = 0; i < ids.size(); i++){\n            int iid = ids[i];\n\t\t\tstd::vector<FEATURE> &ftsvec = samples_[iid];\n\t\t\tFEATURESS fts(ftsvec.size(), 128);\n\t\t\tfor (int k = 0; k < ftsvec.size(); k++) {\n\t\t\t\tfts.row(k) = ftsvec[k];\n\t\t\t}\n\t\t\tint64_t dtm1 = nn_gtm();\n\t\t\t//cost_matrix.row(i) = _nn_cosine_distance(fts, features);\n\t\t\tEigen::VectorXf dd = _nn_cosine_distance(fts, features);\n\t\t\tdds.Push(i, dd);\n\t\t\tint64_t dtm2 = nn_gtm();\n\t\t\tstd::cout << \"distance(\" << iid<< \")----dtm2-dtm1:\" << (dtm2-dtm1) << \"\\n\";\n        }\n\tstd::vector<std::pair<int, Eigen::VectorXf>> vec;\n\tdds.Get(vec);\n\tfor(int i = 0; i < vec.size(); i++){\n\t\tstd::pair<int, Eigen::VectorXf> pa = vec[i];\n\t\tcost_matrix.row(pa.first) =  pa.second;\n\t} \n#endif\n\t\tint64_t dtm4 = nn_gtm();\n\t\tstd::cout << \"distance----dtm4-dtm0:\" << (dtm4-dtm0) << \"\\n\";\n\t\t//std::cout << \"\\nb-haha\\n\" << cost_matrix << \"\\ne-haha\\n\";\n\t\treturn cost_matrix;\n    }\n};\n#endif\n\n\n"
  },
  {
    "path": "deepsort/tracker.h",
    "content": "#ifndef _TTH_\n#define _TTH_\n#include \"nn_matching.h\"\n#include \"linear_assignment.h\"\n#include <algorithm>\n#include <vector>\n#include <iterator>\n#include \"iou_matching.h\"\n#include \"FeatureGetter/FeatureGetter.h\"\n#include \"../NTN.h\"\n\nDYNAMICM getCostMatrixByNND(const std::vector<KalmanTracker> &kalmanTrackers,\n\tconst std::vector<Detection> &dets,\n\tIDS *track_indices,\n\tIDS *detection_indices);\nclass TTracker *p;\n\nclass TTracker{\npublic:\n\tstd::vector<KalmanTracker> kalmanTrackers_;\nprivate:\n        float max_iou_distance_ = 0;\n        int max_age_ = 0;\n        int n_init_ = 0;\n        \n        \n        int _next_id_ = 0;\npublic:    \n    TTracker(float max_iou_distance=0.7, int max_age=30, int n_init=3){\n        max_iou_distance_ = max_iou_distance;\n        max_age_ = max_age;\n        n_init_ = n_init;\n\t\t_next_id_ = 1;\n\t\tp = this;\n    }\n\n    NewAndDelete update(const std::vector<Detection> &detections){\n\tNewAndDelete re;\n\n\tint64_t uptm1 = line_gtm();\n        for(KalmanTracker kalmanTrack : kalmanTrackers_){\n            kalmanTrack->predict(*KF::Instance());\n        }\n\n\tint64_t uptm2 = line_gtm();\n        //# Run matching cascade.\n        RR rr = this->_match(detections);\n\n\tint64_t uptm3 = line_gtm();\n        //# Update track set.\n        //# -matches\n        for(int i = 0; i < rr.matches.size(); i++){\n            std::pair<int, int> pa = rr.matches[i];\n            int track_idx = pa.first;\n            int detection_idx = pa.second;\n            kalmanTrackers_[track_idx]->update(*KF::Instance(), \n                                detections[detection_idx]);\n        }\n        //# -unmatches(track)    \n        for(int i = 0; i < rr.unmatched_tracks.size(); i++){\n            int track_idx = rr.unmatched_tracks[i];\n            kalmanTrackers_[track_idx]->mark_missed();\n        }\n        //# -unmatches(detect)    \n        for(int i = 0; i < rr.unmatched_detections.size(); i++){\n            int detection_idx = rr.unmatched_detections[i];\n            int id = this->_NewTrack(detections[detection_idx]);\n\t\tre.news_.insert(std::make_pair(id, detections[detection_idx].oriPos_));\n        }\n        \n\tint64_t uptm4 = line_gtm();\n        \n\t\tstd::vector<KalmanTracker>::iterator it;\n\t\twhile (1) {\n\t\t\tbool cn = false;\n\t\t\tfor (it = kalmanTrackers_.begin(); it != kalmanTrackers_.end(); ++it) {\n\t\t\t\tKalmanTracker p = *it;\n\t\t\t\tif (p->is_deleted()) {\n\t\t\t\t\tre.deletes_.push_back(p->track_id);\n\t\t\t\t\tkalmanTrackers_.erase(it);\n\t\t\t\t\t//delete p;\n\t\t\t\t\tcn = true;\n\t\t\t\t\tbreak;\n\t\t\t\t}\n\t\t\t}\n\t\t\tif (cn) {\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tbreak;\n\t\t}\n\n        //# Update distance nearestNeighborDistanceMetric.\n        IDS active_ids;\n        for(KalmanTracker t : kalmanTrackers_){\n            if(t->is_confirmed()){\n                active_ids.push_back(t->track_id);\n            }\n        }\n        \n\tint64_t uptm5 = line_gtm();\n\t\tint featureCount = 0;\n        IDS ids;\n        for(KalmanTracker t : kalmanTrackers_){\n            if(!t->is_confirmed()){\n                continue;\n            }\n\t\t\tstd::vector<FEATURE> &fts = t->features_;\n\t\t\tfeatureCount += fts.size();\n\t\t\t//ids += [kalmanTrack.track_id_ for _ in kalmanTrack.features_]\n\t\t\t// ˼ \n\t\t\tfor (int kk = 0; kk < fts.size(); kk++) {\n\t\t\t\tids.push_back(t->track_id);\n\t\t\t}\n        }\n\t\tFEATURESS features(featureCount, 128);\n\t\tint pos = 0;\n\t\tfor (KalmanTracker t : kalmanTrackers_) {\n\t\t\tif (!t->is_confirmed()) {\n\t\t\t\tcontinue;\n\t\t\t}\n\t\t\tstd::vector<FEATURE> &fts = t->features_;\n\t\t\tfor (int i = 0; i < fts.size(); i++) {\n\t\t\t\tFEATURE tt = fts.at(i);\n\t\t\t\tfeatures.row(pos++) = tt;\n\t\t\t}\n\t\t\tt->features_.clear();\n\t\t}\n\n\tint64_t uptm6 = line_gtm();\n\t\tNearestNeighborDistanceMetric::Instance()->partial_fit(\n\t\t\tfeatures, ids, active_ids);\n\tint64_t uptm7 = line_gtm();\n\tstd::cout << \"up----uptm2-uptm1:\" << (uptm2-uptm1) << \n\t\t\t\", uptm3-uptm1:\" << uptm3-uptm1 << \n\t\t\t\", uptm4-uptm1:\" << (uptm4-uptm1) << \n\t\t\t\", uptm5-uptm1:\" << (uptm5-uptm1) << \n\t\t\t\", uptm6-uptm1:\" << (uptm6-uptm1) << \"\\n\";\n\treturn re;\n    }\n    \nprivate:        \n    RR _match(const std::vector<Detection> &detections){\n\tint64_t mtm1 = line_gtm();\n        //Split track set into confirmed and unconfirmed kalmanTrackers.\n        IDS confirmed_trackIds;\n        IDS unconfirmed_trackIds;\n        for(int i = 0; i < kalmanTrackers_.size(); i++){\n            KalmanTracker t = kalmanTrackers_[i]; \n            if(t->is_confirmed()){\n                confirmed_trackIds.push_back(i);\n            }\n            else{\n                unconfirmed_trackIds.push_back(i);\n            }\n        }\n        \n        //# Associate confirmed kalmanTrackers using appearance features.\n        RR rr = linear_assignment::matching_cascade(\n                getCostMatrixByNND, \n                NearestNeighborDistanceMetric::Instance()->matching_threshold(), \n                max_age_,\n                kalmanTrackers_, \n                detections, \n                &confirmed_trackIds);\n        std::vector<std::pair<int, int> > matches_a = rr.matches;\n        IDS unmatched_tracks_a = rr.unmatched_tracks;\n        IDS unmatched_detections = rr.unmatched_detections;\n        \n\tint64_t mtm2 = line_gtm();\n\n        //# Associate remaining kalmanTrackers together with unconfirmed kalmanTrackers using IOU.\n        IDS iou_track_candidateIds, tmp;\n        std::copy(unconfirmed_trackIds.begin(), \n                    unconfirmed_trackIds.end(),\n                    std::back_inserter(iou_track_candidateIds));\n        for(int k = 0; k < unmatched_tracks_a.size(); k++){\n            int id = unmatched_tracks_a[k];\n            if(kalmanTrackers_[id]->time_since_update_ == 1){\n                iou_track_candidateIds.push_back(id);\n            }\n            else{\n                tmp.push_back(id);\n            }\n        }\n        unmatched_tracks_a.clear();\n        unmatched_tracks_a = tmp;\n        \n\tint64_t mtm3 = line_gtm();\n        //\n        RR rr1 = linear_assignment::min_cost_matching(\n                iou_matching::getCostMatrixByIOU, \n                max_iou_distance_, \n                kalmanTrackers_,\n                detections, \n                &iou_track_candidateIds, \n                &unmatched_detections);\n        std::vector<std::pair<int, int> > matches_b = rr1.matches;\n        IDS unmatched_tracks_b = rr1.unmatched_tracks;\n        unmatched_detections = rr1.unmatched_detections;\n                \n\tint64_t mtm4 = line_gtm();\n        // all\n        RR re;\n        re.matches = matches_a;\n        std::copy(matches_b.begin(), matches_b.end(),\n                    std::back_inserter(re.matches));\n        re.unmatched_detections = unmatched_detections;\n        re.unmatched_tracks = unmatched_tracks_a;\n        std::copy(unmatched_tracks_b.begin(),\n                    unmatched_tracks_b.end(),\n                    std::back_inserter(re.unmatched_tracks));\n\tint64_t mtm5 = line_gtm();\n\tstd::cout << \"match----mtm2-mtm1:\" << (mtm2-mtm1) << \n\t\t\t\", mtm3-mtm1:\" << (mtm3-mtm1) << \n\t\t\t\", mtm4-mtm1:\" << (mtm4-mtm1) <<\n\t\t\t\", mtm5-mtm1:\" << (mtm5-mtm1) << \"\\n\";\n        return re;\n    }    \n\n    int _NewTrack(const Detection &detection){\n\tint id = _next_id_;\n        std::pair<MEAN, VAR>  pa = \n                    KF::Instance()->initiate(detection.to_xyah());\n\tKalmanTracker newt(new KalmanTrackerN(\n            pa.first, pa.second, _next_id_, n_init_, max_age_,\n            detection.feature_, true, detection.oriPos_));\n        kalmanTrackers_.push_back(newt);/*new KalmanTracker(\n            pa.first, pa.second, _next_id_, n_init_, max_age_,\n            detection.feature_, true, detection.oriPos_));*/\n        _next_id_ += 1;\n\treturn id;\n    }\n};\n\nDYNAMICM getCostMatrixByNND(const std::vector<KalmanTracker> &kalmanTrackers,\n\tconst std::vector<Detection> &dets,\n\tIDS *track_indicesi,\n\tIDS *detection_indicesi) {\n\tint64_t gtm1 = line_gtm();\n\tIDS track_indices = *track_indicesi;\n\tIDS detection_indices = *detection_indicesi;\n\tFEATURESS features(detection_indices.size(), 128);\n\tfor (int i = 0; i < detection_indices.size(); i++) {\n\t\tint pos = detection_indices[i];\n\t\tfeatures.row(i) = dets[pos].feature_;\n\t}\n\tIDS ids;\n\tfor (int i = 0; i < track_indices.size(); i++) {\n\t\tint pos = track_indices[i];\n\t\tids.push_back(p->kalmanTrackers_[pos]->track_id);\n\t}\n\tDYNAMICM cost_matrix =\n\t\tNearestNeighborDistanceMetric::Instance()->distance(features, ids);\n\tint64_t gtm2 = line_gtm();\n\tcost_matrix = linear_assignment::gate_cost_matrix(\n\t\t*KF::Instance(), cost_matrix, kalmanTrackers, dets, track_indices,\n\t\tdetection_indices);\n\tint64_t gtm3 = line_gtm();\n\tstd::cout << \"getCostMatrixByNND----gtm2-gtm1:\" << (gtm2-gtm1) <<\n\t\t\t\", gtm3-gtm1:\" << (gtm3-gtm1) << \"\\n\";\n\treturn cost_matrix;\n}\n#endif\n\n\n\n\n\n\n\n\n\n\n\n"
  },
  {
    "path": "fdsst/SSE2NEON.h",
    "content": "#ifndef SSE2NEON_H\n#define SSE2NEON_H\n\n// This header file provides a simple API translation layer\n// between SSE intrinsics to their corresponding ARM NEON versions\n//\n// This header file does not (yet) translate *all* of the SSE intrinsics.\n// Since this is in support of a specific porting effort, I have only\n// included the intrinsics I needed to get my port to work.\n//\n// Questions/Comments/Feedback send to: jratcliffscarab@gmail.com\n//\n// If you want to improve or add to this project, send me an\n// email and I will probably approve your access to the depot.\n//\n// Project is located here:\n//\n//\thttps://github.com/jratcliff63367/sse2neon\n//\n// TipJar: 1PzgWDSyq4pmdAXRH8SPUtta4SWGrt4B1p : https://blockchain.info/address/1PzgWDSyq4pmdAXRH8SPUtta4SWGrt4B1p\n//\n// \n// Contributors to this project are:\n//\n// John W. Ratcliff : jratcliffscarab@gmail.com\n// Brandon Rowlett : browlett@nvidia.com\n// Ken Fast : kfast@gdeb.com\n\n#define GCC 1\n#define ENABLE_CPP_VERSION 0\n\n#if GCC\n#define FORCE_INLINE\t\t\t\t\tinline __attribute__((always_inline))\n#else\n#define FORCE_INLINE\t\t\t\t\tinline\n#endif\n\n#include \"arm_neon.h\"\n/*******************************************************/\n/* MACRO for shuffle parameter for _mm_shuffle_ps().   */\n/* Argument fp3 is a digit[0123] that represents the fp*/\n/* from argument \"b\" of mm_shuffle_ps that will be     */\n/* placed in fp3 of result. fp2 is the same for fp2 in */\n/* result. fp1 is a digit[0123] that represents the fp */\n/* from argument \"a\" of mm_shuffle_ps that will be     */\n/* places in fp1 of result. fp0 is the same for fp0 of */\n/* result                                              */\n/*******************************************************/\n#define _MM_SHUFFLE(fp3,fp2,fp1,fp0) (((fp3) << 6) | ((fp2) << 4) | \\\n\t((fp1) << 2) | ((fp0)))\n\ntypedef float32x4_t __m128;\ntypedef int32x4_t __m128i;\n\n// ******************************************\n// Set/get methods\n// ******************************************\n\n// Sets the 128-bit value to zero https://msdn.microsoft.com/en-us/library/vstudio/ys7dw0kh(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_setzero_si128()\n{\n\treturn vdupq_n_s32(0);\n}\n\n// Clears the four single-precision, floating-point values. https://msdn.microsoft.com/en-us/library/vstudio/tk1t2tbz(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_setzero_ps(void)\n{\n\treturn vdupq_n_f32(0);\n}\n\n// Sets the four single-precision, floating-point values to w. https://msdn.microsoft.com/en-us/library/vstudio/2x1se8ha(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_set1_ps(float _w)\n{\n\treturn vdupq_n_f32(_w);\n}\n\n// Sets the four single-precision, floating-point values to w. https://msdn.microsoft.com/en-us/library/vstudio/2x1se8ha(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_set_ps1(float _w)\n{\n\treturn vdupq_n_f32(_w);\n}\n\n// Sets the four single-precision, floating-point values to the four inputs. https://msdn.microsoft.com/en-us/library/vstudio/afh0zf75(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_set_ps(float w, float z, float y, float x)\n{\n\tfloat __attribute__((aligned(16))) data[4] = { x, y, z, w };\n\treturn vld1q_f32(data);\n}\n\n// Sets the four single-precision, floating-point values to the four inputs in reverse order. https://msdn.microsoft.com/en-us/library/vstudio/d2172ct3(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_setr_ps(float w, float z , float y , float x ) \n{\n\tfloat __attribute__ ((aligned (16))) data[4] = { w, z, y, x };\n\treturn vld1q_f32(data);\n}\n\n// Sets the 4 signed 32-bit integer values to i. https://msdn.microsoft.com/en-us/library/vstudio/h4xscxat(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_set1_epi32(int _i)\n{\n\treturn vdupq_n_s32(_i);\n}\n\n// Sets the 4 signed 32-bit integer values. https://msdn.microsoft.com/en-us/library/vstudio/019beekt(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_set_epi32(int i3, int i2, int i1, int i0)\n{\n\tint32_t __attribute__((aligned(16))) data[4] = { i0, i1, i2, i3 };\n\treturn vld1q_s32(data);\n}\n\n// Stores four single-precision, floating-point values. https://msdn.microsoft.com/en-us/library/vstudio/s3h4ay6y(v=vs.100).aspx\nFORCE_INLINE void _mm_store_ps(float *p, __m128 a)\n{\n\tvst1q_f32(p, a);\n}\n\n// Stores four single-precision, floating-point values. https://msdn.microsoft.com/en-us/library/44e30x22(v=vs.100).aspx\nFORCE_INLINE void _mm_storeu_ps(float *p, __m128 a)\n{\n\tvst1q_f32(p, a);\n}\n\n// Stores four 32-bit integer values as (as a __m128i value) at the address p. https://msdn.microsoft.com/en-us/library/vstudio/edk11s13(v=vs.100).aspx\nFORCE_INLINE void _mm_store_si128(__m128i *p, __m128i a ) \n{\n\tvst1q_s32((int32_t*) p,a);\n}\n\n// Stores the lower single - precision, floating - point value. https://msdn.microsoft.com/en-us/library/tzz10fbx(v=vs.100).aspx\nFORCE_INLINE void _mm_store_ss(float *p, __m128 a)\n{\n\tvst1q_lane_f32(p, a, 0);\n}\n\n// Reads the lower 64 bits of b and stores them into the lower 64 bits of a.  https://msdn.microsoft.com/en-us/library/hhwf428f%28v=vs.90%29.aspx\nFORCE_INLINE void _mm_storel_epi64(__m128i* a, __m128i b)\n{\n\t*a = (__m128i)vsetq_lane_s64((int64_t)vget_low_s32(b), *(int64x2_t*)a, 0);\n}\n\n// Loads a single single-precision, floating-point value, copying it into all four words https://msdn.microsoft.com/en-us/library/vstudio/5cdkf716(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_load1_ps(const float * p)\n{\n\treturn vld1q_dup_f32(p);\n}\n\n// Loads four single-precision, floating-point values. https://msdn.microsoft.com/en-us/library/vstudio/zzd50xxt(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_load_ps(const float * p)\n{\n\treturn vld1q_f32(p);\n}\n\n// Loads four single-precision, floating-point values.  https://msdn.microsoft.com/en-us/library/x1b16s7z%28v=vs.90%29.aspx\nFORCE_INLINE __m128 _mm_loadu_ps(const float * p)\n{\n\t// for neon, alignment doesn't matter, so _mm_load_ps and _mm_loadu_ps are equivalent for neon\n\treturn vld1q_f32(p);\n}\n\n// Loads an single - precision, floating - point value into the low word and clears the upper three words.  https://msdn.microsoft.com/en-us/library/548bb9h4%28v=vs.90%29.aspx\nFORCE_INLINE __m128 _mm_load_ss(const float * p)\n{\n\t__m128 result = vdupq_n_f32(0);\n\treturn vsetq_lane_f32(*p, result, 0);\n}\n\n\n// ******************************************\n// Logic/Binary operations\n// ******************************************\n\n// Compares for inequality.  https://msdn.microsoft.com/en-us/library/sf44thbx(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cmpneq_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vmvnq_s32((__m128i)vceqq_f32(a, b));\n}\n\n// Computes the bitwise AND-NOT of the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/68h7wd02(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_andnot_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vbicq_s32((__m128i)b, (__m128i)a); // *NOTE* argument swap\n}\n\n// Computes the bitwise AND of the 128-bit value in b and the bitwise NOT of the 128-bit value in a. https://msdn.microsoft.com/en-us/library/vstudio/1beaceh8(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_andnot_si128(__m128i a, __m128i b)\n{\n\treturn (__m128i)vbicq_s32(b, a); // *NOTE* argument swap\n}\n\n// Computes the bitwise AND of the 128-bit value in a and the 128-bit value in b. https://msdn.microsoft.com/en-us/library/vstudio/6d1txsa8(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_and_si128(__m128i a, __m128i b)\n{\n\treturn (__m128i)vandq_s32(a, b);\n}\n\n// Computes the bitwise AND of the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/73ck1xc5(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_and_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vandq_s32((__m128i)a, (__m128i)b);\n}\n\n// Computes the bitwise OR of the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/7ctdsyy0(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_or_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vorrq_s32((__m128i)a, (__m128i)b);\n}\n\n// Computes bitwise EXOR (exclusive-or) of the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/ss6k3wk8(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_xor_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)veorq_s32((__m128i)a, (__m128i)b);\n}\n\n// Computes the bitwise OR of the 128-bit value in a and the 128-bit value in b. https://msdn.microsoft.com/en-us/library/vstudio/ew8ty0db(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_or_si128(__m128i a, __m128i b)\n{\n\treturn (__m128i)vorrq_s32(a, b);\n}\n\n// Computes the bitwise XOR of the 128-bit value in a and the 128-bit value in b.  https://msdn.microsoft.com/en-us/library/fzt08www(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_xor_si128(__m128i a, __m128i b)\n{\n\treturn veorq_s32(a, b);\n}\n\n// NEON does not provide this method\n// Creates a 4-bit mask from the most significant bits of the four single-precision, floating-point values. https://msdn.microsoft.com/en-us/library/vstudio/4490ys29(v=vs.100).aspx\nFORCE_INLINE int _mm_movemask_ps(__m128 a)\n{\n#if ENABLE_CPP_VERSION // I am not yet convinced that the NEON version is faster than the C version of this\n\tuint32x4_t &ia = *(uint32x4_t *)&a;\n\treturn (ia[0] >> 31) | ((ia[1] >> 30) & 2) | ((ia[2] >> 29) & 4) | ((ia[3] >> 28) & 8);\n#else\n\tstatic const uint32x4_t movemask = { 1, 2, 4, 8 };\n\tstatic const uint32x4_t highbit = { 0x80000000, 0x80000000, 0x80000000, 0x80000000 };\n\tuint32x4_t t0 = vreinterpretq_u32_f32(a);\n\tuint32x4_t t1 = vtstq_u32(t0, highbit);\n\tuint32x4_t t2 = vandq_u32(t1, movemask);\n\tuint32x2_t t3 = vorr_u32(vget_low_u32(t2), vget_high_u32(t2));\n\treturn vget_lane_u32(t3, 0) | vget_lane_u32(t3, 1);\n#endif\n}\n\n// Takes the upper 64 bits of a and places it in the low end of the result\n// Takes the lower 64 bits of b and places it into the high end of the result.\nFORCE_INLINE __m128 _mm_shuffle_ps_1032(__m128 a, __m128 b)\n{\n\treturn vcombine_f32(vget_high_f32(a), vget_low_f32(b));\n}\n\n// takes the lower two 32-bit values from a and swaps them and places in high end of result\n// takes the higher two 32 bit values from b and swaps them and places in low end of result.\nFORCE_INLINE __m128 _mm_shuffle_ps_2301(__m128 a, __m128 b)\n{\t\n\treturn vcombine_f32(vrev64_f32(vget_low_f32(a)), vrev64_f32(vget_high_f32(b)));\n}\n\n// keeps the low 64 bits of b in the low and puts the high 64 bits of a in the high\nFORCE_INLINE __m128 _mm_shuffle_ps_3210(__m128 a, __m128 b)\n{\n\treturn vcombine_f32(vget_low_f32(a), vget_high_f32(b));\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_0011(__m128 a, __m128 b)\n{\n\treturn vcombine_f32(vdup_n_f32(vgetq_lane_f32(a, 1)), vdup_n_f32(vgetq_lane_f32(b, 0)));\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_0022(__m128 a, __m128 b)\n{\n\treturn vcombine_f32(vdup_n_f32(vgetq_lane_f32(a, 2)), vdup_n_f32(vgetq_lane_f32(b, 0)));\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_2200(__m128 a, __m128 b)\n{\n\treturn vcombine_f32(vdup_n_f32(vgetq_lane_f32(a, 0)), vdup_n_f32(vgetq_lane_f32(b, 2)));\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_3202(__m128 a, __m128 b)\n{\n\tfloat32_t a0 = vgetq_lane_f32(a, 0);\n\tfloat32_t a2 = vgetq_lane_f32(a, 2);\n\tfloat32x2_t aVal = vdup_n_f32(a2);\n\taVal = vset_lane_f32(a0, aVal, 1);\n\treturn vcombine_f32(aVal, vget_high_f32(b));\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_1133(__m128 a, __m128 b)\n{\n\treturn vcombine_f32(vdup_n_f32(vgetq_lane_f32(a, 3)), vdup_n_f32(vgetq_lane_f32(b, 1)));\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_2010(__m128 a, __m128 b)\n{\n\tfloat32_t b0 = vgetq_lane_f32(b, 0);\n\tfloat32_t b2 = vgetq_lane_f32(b, 2);\n\tfloat32x2_t bVal = vdup_n_f32(b0);\n\tbVal = vset_lane_f32(b2, bVal, 1);\n\treturn vcombine_f32(vget_low_f32(a), bVal);\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_2001(__m128 a, __m128 b)\n{\n\tfloat32_t b0 = vgetq_lane_f32(b, 0);\n\tfloat32_t b2 = vgetq_lane_f32(b, 2);\n\tfloat32x2_t bVal = vdup_n_f32(b0);\n\tbVal = vset_lane_f32(b2, bVal, 1);\n\treturn vcombine_f32(vrev64_f32(vget_low_f32(a)), bVal);\n}\n\nFORCE_INLINE __m128 _mm_shuffle_ps_2032(__m128 a, __m128 b)\n{\n\tfloat32_t b0 = vgetq_lane_f32(b, 0);\n\tfloat32_t b2 = vgetq_lane_f32(b, 2);\n\tfloat32x2_t bVal = vdup_n_f32(b0);\n\tbVal = vset_lane_f32(b2, bVal, 1);\n\treturn vcombine_f32(vget_high_f32(a), bVal);\n}\n\n\n// NEON does not support a general purpose permute intrinsic\n// Currently I am not sure whether the C implementation is faster or slower than the NEON version.\n// Note, this has to be expanded as a template because the shuffle value must be an immediate value.\n// The same is true on SSE as well.\n// Selects four specific single-precision, floating-point values from a and b, based on the mask i. https://msdn.microsoft.com/en-us/library/vstudio/5f0858x0(v=vs.100).aspx\ntemplate <int i>\nFORCE_INLINE __m128 _mm_shuffle_ps_default(__m128 a, __m128 b)\n{\n#if ENABLE_CPP_VERSION // I am not convinced that the NEON version is faster than the C version yet.\n\t__m128 ret;\n\tret[0] = a[i & 0x3];\n\tret[1] = a[(i >> 2) & 0x3];\n\tret[2] = b[(i >> 4) & 0x03];\n\tret[3] = b[(i >> 6) & 0x03];\n\treturn ret;\n#else\n\t__m128 ret = vmovq_n_f32(vgetq_lane_f32(a, i & 0x3));\n\tret = vsetq_lane_f32(vgetq_lane_f32(a, (i >> 2) & 0x3), ret, 1);\n\tret = vsetq_lane_f32(vgetq_lane_f32(b, (i >> 4) & 0x3), ret, 2);\n\tret = vsetq_lane_f32(vgetq_lane_f32(b, (i >> 6) & 0x3), ret, 3);\n\treturn ret;\n#endif\n}\n\ntemplate <int i >\nFORCE_INLINE __m128 _mm_shuffle_ps_function(__m128 a, __m128 b)\n{\n\tswitch (i)\n\t{\n\t\tcase _MM_SHUFFLE(1, 0, 3, 2): return _mm_shuffle_ps_1032(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 3, 0, 1): return _mm_shuffle_ps_2301(a, b); break;\n\t\tcase _MM_SHUFFLE(3, 2, 1, 0): return _mm_shuffle_ps_3210(a, b); break;\n\t\tcase _MM_SHUFFLE(0, 0, 1, 1): return _mm_shuffle_ps_0011(a, b); break;\n\t\tcase _MM_SHUFFLE(0, 0, 2, 2): return _mm_shuffle_ps_0022(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 2, 0, 0): return _mm_shuffle_ps_2200(a, b); break;\n\t\tcase _MM_SHUFFLE(3, 2, 0, 2): return _mm_shuffle_ps_3202(a, b); break;\n\t\tcase _MM_SHUFFLE(1, 1, 3, 3): return _mm_shuffle_ps_1133(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 0, 1, 0): return _mm_shuffle_ps_2010(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 0, 0, 1): return _mm_shuffle_ps_2001(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 0, 3, 2): return _mm_shuffle_ps_2032(a, b); break;\n\t\tdefault: _mm_shuffle_ps_default<i>(a, b);\n\t}\n}\n\n#define _mm_shuffle_ps(a,b,i) _mm_shuffle_ps_function<i>(a,b)\n\n// Takes the upper 64 bits of a and places it in the low end of the result\n// Takes the lower 64 bits of b and places it into the high end of the result.\nFORCE_INLINE __m128i _mm_shuffle_epi_1032(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vget_high_s32(a), vget_low_s32(b));\n}\n\n// takes the lower two 32-bit values from a and swaps them and places in low end of result\n// takes the higher two 32 bit values from b and swaps them and places in high end of result.\nFORCE_INLINE __m128i _mm_shuffle_epi_2301(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vrev64_s32(vget_low_s32(a)), vrev64_s32(vget_high_s32(b)));\n}\n\n// shift a right by 32 bits, and put the lower 32 bits of a into the upper 32 bits of b\n// when a and b are the same, rotates the least significant 32 bits into the most signficant 32 bits, and shifts the rest down\nFORCE_INLINE __m128i _mm_shuffle_epi_0321(__m128i a, __m128i b)\n{\n\treturn vextq_s32(a, b, 1);\n}\n\n// shift a left by 32 bits, and put the upper 32 bits of b into the lower 32 bits of a\n// when a and b are the same, rotates the most significant 32 bits into the least signficant 32 bits, and shifts the rest up\nFORCE_INLINE __m128i _mm_shuffle_epi_2103(__m128i a, __m128i b)\n{\n\treturn vextq_s32(a, b, 3);\t\t\n}\n\n// gets the lower 64 bits of a, and places it in the upper 64 bits\n// gets the lower 64 bits of b and places it in the lower 64 bits\nFORCE_INLINE __m128i _mm_shuffle_epi_1010(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vget_low_s32(a), vget_low_s32(a));\n}\n\n// gets the lower 64 bits of a, and places it in the upper 64 bits\n// gets the lower 64 bits of b, swaps the 0 and 1 elements, and places it in the lower 64 bits\nFORCE_INLINE __m128i _mm_shuffle_epi_1001(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vrev64_s32(vget_low_s32(a)), vget_low_s32(b));\n}\n\n// gets the lower 64 bits of a, swaps the 0 and 1 elements and places it in the upper 64 bits\n// gets the lower 64 bits of b, swaps the 0 and 1 elements, and places it in the lower 64 bits\nFORCE_INLINE __m128i _mm_shuffle_epi_0101(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vrev64_s32(vget_low_s32(a)), vrev64_s32(vget_low_s32(b)));\n}\n\nFORCE_INLINE __m128i _mm_shuffle_epi_2211(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vdup_n_s32(vgetq_lane_s32(a, 1)), vdup_n_s32(vgetq_lane_s32(b, 2)));\n}\n\nFORCE_INLINE __m128i _mm_shuffle_epi_0122(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vdup_n_s32(vgetq_lane_s32(a, 2)), vrev64_s32(vget_low_s32(b)));\n}\n\nFORCE_INLINE __m128i _mm_shuffle_epi_3332(__m128i a, __m128i b)\n{\n\treturn vcombine_s32(vget_high_s32(a), vdup_n_s32(vgetq_lane_s32(b, 3)));\n}\n\ntemplate <int i >\nFORCE_INLINE __m128i _mm_shuffle_epi32_default(__m128i a, __m128i b)\n{\n#if ENABLE_CPP_VERSION\n\t__m128i ret;\n\tret[0] = a[i & 0x3];\n\tret[1] = a[(i >> 2) & 0x3];\n\tret[2] = b[(i >> 4) & 0x03];\n\tret[3] = b[(i >> 6) & 0x03];\n\treturn ret;\n#else\n\t__m128i ret = vmovq_n_s32(vgetq_lane_s32(a, i & 0x3));\n\tret = vsetq_lane_s32(vgetq_lane_s32(a, (i >> 2) & 0x3), ret, 1);\n\tret = vsetq_lane_s32(vgetq_lane_s32(b, (i >> 4) & 0x3), ret, 2);\n\tret = vsetq_lane_s32(vgetq_lane_s32(b, (i >> 6) & 0x3), ret, 3);\n\treturn ret;\n#endif\n}\n\ntemplate <int i >\nFORCE_INLINE __m128i _mm_shuffle_epi32_function(__m128i a, __m128i b)\n{\n\tswitch (i)\n\t{\n\t\tcase _MM_SHUFFLE(1, 0, 3, 2): return _mm_shuffle_epi_1032(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 3, 0, 1): return _mm_shuffle_epi_2301(a, b); break;\n\t\tcase _MM_SHUFFLE(0, 3, 2, 1): return _mm_shuffle_epi_0321(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 1, 0, 3): return _mm_shuffle_epi_2103(a, b); break;\n\t\tcase _MM_SHUFFLE(1, 0, 1, 0): return _mm_shuffle_epi_1010(a, b); break;\n\t\tcase _MM_SHUFFLE(1, 0, 0, 1): return _mm_shuffle_epi_1001(a, b); break;\n\t\tcase _MM_SHUFFLE(0, 1, 0, 1): return _mm_shuffle_epi_0101(a, b); break;\n\t\tcase _MM_SHUFFLE(2, 2, 1, 1): return _mm_shuffle_epi_2211(a, b); break;\n\t\tcase _MM_SHUFFLE(0, 1, 2, 2): return _mm_shuffle_epi_0122(a, b); break;\n\t\tcase _MM_SHUFFLE(3, 3, 3, 2): return _mm_shuffle_epi_3332(a, b); break;\n\t\tdefault: return _mm_shuffle_epi32_default<i>(a, b);\n\t}\n}\n\ntemplate <int i >\nFORCE_INLINE __m128i _mm_shuffle_epi32_splat(__m128i a)\n{\n\treturn vdupq_n_s32(vgetq_lane_s32(a, i));\n}\n\ntemplate <int i>\nFORCE_INLINE __m128i _mm_shuffle_epi32_single(__m128i a)\n{\n\tswitch (i)\n\t{\n\t\tcase _MM_SHUFFLE(0, 0, 0, 0): return _mm_shuffle_epi32_splat<0>(a); break;\n\t\tcase _MM_SHUFFLE(1, 1, 1, 1): return _mm_shuffle_epi32_splat<1>(a); break;\n\t\tcase _MM_SHUFFLE(2, 2, 2, 2): return _mm_shuffle_epi32_splat<2>(a); break;\n\t\tcase _MM_SHUFFLE(3, 3, 3, 3): return _mm_shuffle_epi32_splat<3>(a); break;\t\t\t\n\t\tdefault: return _mm_shuffle_epi32_function<i>(a, a); \n\t}\n}\n\n// Shuffles the 4 signed or unsigned 32-bit integers in a as specified by imm.\thttps://msdn.microsoft.com/en-us/library/56f67xbk%28v=vs.90%29.aspx\n#define _mm_shuffle_epi32(a,i) _mm_shuffle_epi32_single<i>(a)\n\ntemplate <int i>\nFORCE_INLINE __m128i _mm_shufflehi_epi16_function(__m128i a)\n{\n\tint16x8_t ret = (int16x8_t)a;\n\tint16x4_t highBits = vget_high_s16(ret);\n\tret = vsetq_lane_s16(vget_lane_s16(highBits, i & 0x3), ret, 4);\n\tret = vsetq_lane_s16(vget_lane_s16(highBits, (i >> 2) & 0x3), ret, 5);\n\tret = vsetq_lane_s16(vget_lane_s16(highBits, (i >> 4) & 0x3), ret, 6);\n\tret = vsetq_lane_s16(vget_lane_s16(highBits, (i >> 6) & 0x3), ret, 7);\n\treturn (__m128i)ret;\n}\n\n// Shuffles the upper 4 signed or unsigned 16 - bit integers in a as specified by imm.  https://msdn.microsoft.com/en-us/library/13ywktbs(v=vs.100).aspx\n#define _mm_shufflehi_epi16(a,i) _mm_shufflehi_epi16_function<i>(a)\n\n// Shifts the 4 signed or unsigned 32-bit integers in a left by count bits while shifting in zeros. : https://msdn.microsoft.com/en-us/library/z2k3bbtb%28v=vs.90%29.aspx\n#define _mm_slli_epi32(a, imm) (__m128i)vshlq_n_s32(a,imm)\n\n//Shifts the 4 signed or unsigned 32-bit integers in a right by count bits while shifting in zeros.  https://msdn.microsoft.com/en-us/library/w486zcfa(v=vs.100).aspx\n#define _mm_srli_epi32( a, imm ) (__m128i)vshrq_n_u32((uint32x4_t)a, imm)\n\n// Shifts the 4 signed 32 - bit integers in a right by count bits while shifting in the sign bit.  https://msdn.microsoft.com/en-us/library/z1939387(v=vs.100).aspx\n#define _mm_srai_epi32( a, imm ) vshrq_n_s32(a, imm)\n\n// Shifts the 128 - bit value in a right by imm bytes while shifting in zeros.imm must be an immediate. https://msdn.microsoft.com/en-us/library/305w28yz(v=vs.100).aspx\n//#define _mm_srli_si128( a, imm ) (__m128i)vmaxq_s8((int8x16_t)a, vextq_s8((int8x16_t)a, vdupq_n_s8(0), imm))\n#define _mm_srli_si128( a, imm ) (__m128i)vextq_s8((int8x16_t)a, vdupq_n_s8(0), (imm))\n\n// Shifts the 128-bit value in a left by imm bytes while shifting in zeros. imm must be an immediate.  https://msdn.microsoft.com/en-us/library/34d3k2kt(v=vs.100).aspx\n#define _mm_slli_si128( a, imm ) (__m128i)vextq_s8(vdupq_n_s8(0), (int8x16_t)a, 16 - (imm))\n\n// NEON does not provide a version of this function, here is an article about some ways to repro the results.\n// http://stackoverflow.com/questions/11870910/sse-mm-movemask-epi8-equivalent-method-for-arm-neon\n// Creates a 16-bit mask from the most significant bits of the 16 signed or unsigned 8-bit integers in a and zero extends the upper bits. https://msdn.microsoft.com/en-us/library/vstudio/s090c8fk(v=vs.100).aspx\nFORCE_INLINE int _mm_movemask_epi8(__m128i _a)\n{\n\tuint8x16_t input = (uint8x16_t)_a;\n\tconst int8_t __attribute__((aligned(16))) xr[8] = { -7, -6, -5, -4, -3, -2, -1, 0 };\n\tuint8x8_t mask_and = vdup_n_u8(0x80);\n\tint8x8_t mask_shift = vld1_s8(xr);\n\n\tuint8x8_t lo = vget_low_u8(input);\n\tuint8x8_t hi = vget_high_u8(input);\n\n\tlo = vand_u8(lo, mask_and);\n\tlo = vshl_u8(lo, mask_shift);\n\n\thi = vand_u8(hi, mask_and);\n\thi = vshl_u8(hi, mask_shift);\n\n\tlo = vpadd_u8(lo, lo);\n\tlo = vpadd_u8(lo, lo);\n\tlo = vpadd_u8(lo, lo);\n\n\thi = vpadd_u8(hi, hi);\n\thi = vpadd_u8(hi, hi);\n\thi = vpadd_u8(hi, hi);\n\n\treturn ((hi[0] << 8) | (lo[0] & 0xFF));\n}\n\n\n// ******************************************\n// Math operations\n// ******************************************\n\n// Subtracts the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/1zad2k61(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_sub_ps(__m128 a, __m128 b)\n{\n\treturn vsubq_f32(a, b);\n}\n\n// Subtracts the 4 signed or unsigned 32-bit integers of b from the 4 signed or unsigned 32-bit integers of a. https://msdn.microsoft.com/en-us/library/vstudio/fhh866h0(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_sub_epi32(__m128i a, __m128i b)\n{\n\treturn vsubq_s32(a, b);\n}\n\n// Adds the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/c9848chc(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_add_ps(__m128 a, __m128 b)\n{\n\treturn vaddq_f32(a, b);\n}\n\n// Adds the 4 signed or unsigned 32-bit integers in a to the 4 signed or unsigned 32-bit integers in b. https://msdn.microsoft.com/en-us/library/vstudio/09xs4fkk(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_add_epi32(__m128i a, __m128i b)\n{\n\treturn vaddq_s32(a, b);\n}\n\n// Adds the 8 signed or unsigned 16-bit integers in a to the 8 signed or unsigned 16-bit integers in b. https://msdn.microsoft.com/en-us/library/fceha5k4(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_add_epi16(__m128i a, __m128i b)\n{\n\treturn (__m128i)vaddq_s16((int16x8_t)a, (int16x8_t)b);\n}\n\n// Multiplies the 8 signed or unsigned 16-bit integers from a by the 8 signed or unsigned 16-bit integers from b. https://msdn.microsoft.com/en-us/library/vstudio/9ks1472s(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_mullo_epi16(__m128i a, __m128i b)\n{\n\treturn (__m128i)vmulq_s16((int16x8_t)a, (int16x8_t)b);\n}\n\n// Multiplies the 4 signed or unsigned 32-bit integers from a by the 4 signed or unsigned 32-bit integers from b. https://msdn.microsoft.com/en-us/library/vstudio/bb531409(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_mullo_epi32 (__m128i a, __m128i b)\n{\n\treturn (__m128i)vmulq_s32((int32x4_t)a,(int32x4_t)b);\n}\n\n// Multiplies the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/22kbk6t9(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_mul_ps(__m128 a, __m128 b)\n{\n\treturn vmulq_f32(a, b);\n}\n\n// This version does additional iterations to improve accuracy.  Between 1 and 4 recommended.\n// Computes the approximations of reciprocals of the four single-precision, floating-point values of a. https://msdn.microsoft.com/en-us/library/vstudio/796k1tty(v=vs.100).aspx\nFORCE_INLINE __m128 recipq_newton(__m128 in, int n)\n{\n\t__m128 recip = vrecpeq_f32(in);\n\tfor (int i = 0; i<n; ++i)\n\t{\n\t\trecip = vmulq_f32(recip, vrecpsq_f32(recip, in));\n\t}\n\treturn recip;\n}\n\n// Computes the approximations of reciprocals of the four single-precision, floating-point values of a. https://msdn.microsoft.com/en-us/library/vstudio/796k1tty(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_rcp_ps(__m128 in)\n{\n\t__m128 recip = vrecpeq_f32(in);\n\trecip = vmulq_f32(recip, vrecpsq_f32(recip, in));\n\treturn recip;\n}\n\n\n// Computes the approximations of square roots of the four single-precision, floating-point values of a. First computes reciprocal square roots and then reciprocals of the four values. https://msdn.microsoft.com/en-us/library/vstudio/8z67bwwk(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_sqrt_ps(__m128 in)\n{\n\t__m128 recipsq = vrsqrteq_f32(in);\n\t__m128 sq = vrecpeq_f32(recipsq);\n\t// ??? use step versions of both sqrt and recip for better accuracy?\n\treturn sq;\n}\n\n\n// Computes the maximums of the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/ff5d607a(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_max_ps(__m128 a, __m128 b)\n{\n\treturn vmaxq_f32(a, b);\n}\n\n// Computes the minima of the four single-precision, floating-point values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/wh13kadz(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_min_ps(__m128 a, __m128 b)\n{\n\treturn vminq_f32(a, b);\n}\n\n// Computes the pairwise minima of the 8 signed 16-bit integers from a and the 8 signed 16-bit integers from b. https://msdn.microsoft.com/en-us/library/vstudio/6te997ew(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_min_epi16(__m128i a, __m128i b)\n{\n\treturn (__m128i)vminq_s16((int16x8_t)a, (int16x8_t)b);\n}\n\n// epi versions of min/max\n// Computes the pariwise maximums of the four signed 32-bit integer values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/bb514055(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_max_epi32(__m128i a, __m128i b ) \n{\n\treturn vmaxq_s32(a,b);\n}\n\n// Computes the pariwise minima of the four signed 32-bit integer values of a and b. https://msdn.microsoft.com/en-us/library/vstudio/bb531476(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_min_epi32(__m128i a, __m128i b ) \n{\n\treturn vminq_s32(a,b);\n}\n\n// Multiplies the 8 signed 16-bit integers from a by the 8 signed 16-bit integers from b. https://msdn.microsoft.com/en-us/library/vstudio/59hddw1d(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_mulhi_epi16(__m128i a, __m128i b)\n{\n\tint16x8_t ret = vqdmulhq_s16((int16x8_t)a, (int16x8_t)b);\n\tret = vshrq_n_s16(ret, 1);\n\treturn (__m128i)ret;\n}\n\n// Computes pairwise add of each argument as single-precision, floating-point values a and b. \n//https://msdn.microsoft.com/en-us/library/yd9wecaa.aspx\nFORCE_INLINE __m128 _mm_hadd_ps(__m128 a, __m128 b ) \n{\n// This does not work, no vpaddq...\n//\treturn (__m128) vpaddq_f32(a,b);\n        //\n        // get two f32x2_t values from a\n        // do vpadd\n        // put result in low half of f32x4 result\n        //\n        // get two f32x2_t values from b\n        // do vpadd\n        // put result in high half of f32x4 result\n        //\n        // combine\n        return vcombine_f32( vpadd_f32( vget_low_f32(a), vget_high_f32(a) ), vpadd_f32( vget_low_f32(b), vget_high_f32(b) ) );\n}\n\n// ******************************************\n// Compare operations\n// ******************************************\n\n// Compares for less than https://msdn.microsoft.com/en-us/library/vstudio/f330yhc8(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cmplt_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vcltq_f32(a, b);\n}\n\n// Compares for greater than. https://msdn.microsoft.com/en-us/library/vstudio/11dy102s(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cmpgt_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vcgtq_f32(a, b);\n}\n\n// Compares for greater than or equal. https://msdn.microsoft.com/en-us/library/vstudio/fs813y2t(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cmpge_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vcgeq_f32(a, b);\n}\n\n// Compares for less than or equal. https://msdn.microsoft.com/en-us/library/vstudio/1s75w83z(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cmple_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vcleq_f32(a, b);\n}\n\n// Compares for equality. https://msdn.microsoft.com/en-us/library/vstudio/36aectz5(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cmpeq_ps(__m128 a, __m128 b)\n{\n\treturn (__m128)vceqq_f32(a, b);\n}\n\n// Compares the 4 signed 32-bit integers in a and the 4 signed 32-bit integers in b for less than. https://msdn.microsoft.com/en-us/library/vstudio/4ak0bf5d(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_cmplt_epi32(__m128i a, __m128i b)\n{\n\treturn (__m128i)vcltq_s32(a, b);\n}\n\n// Compares the 4 signed 32-bit integers in a and the 4 signed 32-bit integers in b for greater than. https://msdn.microsoft.com/en-us/library/vstudio/1s9f2z0y(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_cmpgt_epi32(__m128i a, __m128i b)\n{\n\treturn (__m128i)vcgtq_s32(a, b);\n}\n\n// Compares the four 32-bit floats in a and b to check if any values are NaN. Ordered compare between each value returns true for \"orderable\" and false for \"not orderable\" (NaN). https://msdn.microsoft.com/en-us/library/vstudio/0h9w00fx(v=vs.100).aspx\n// see also:\n// http://stackoverflow.com/questions/8627331/what-does-ordered-unordered-comparison-mean\n// http://stackoverflow.com/questions/29349621/neon-isnanval-intrinsics\nFORCE_INLINE __m128 _mm_cmpord_ps(__m128 a, __m128 b ) \n{\n        // Note: NEON does not have ordered compare builtin\n        // Need to compare a eq a and b eq b to check for NaN\n        // Do AND of results to get final\n\treturn (__m128) vreinterpretq_f32_u32( vandq_u32( vceqq_f32(a,a), vceqq_f32(b,b) ) );\n}\n\n// ******************************************\n// Conversions\n// ******************************************\n\n// Converts the four single-precision, floating-point values of a to signed 32-bit integer values using truncate. https://msdn.microsoft.com/en-us/library/vstudio/1h005y6x(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_cvttps_epi32(__m128 a)\n{\n\treturn vcvtq_s32_f32(a);\n}\n\n// Converts the four signed 32-bit integer values of a to single-precision, floating-point values https://msdn.microsoft.com/en-us/library/vstudio/36bwxcx5(v=vs.100).aspx\nFORCE_INLINE __m128 _mm_cvtepi32_ps(__m128i a)\n{\n\treturn vcvtq_f32_s32(a);\n}\n\n// Converts the four single-precision, floating-point values of a to signed 32-bit integer values. https://msdn.microsoft.com/en-us/library/vstudio/xdc42k5e(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_cvtps_epi32(__m128 a)\n{\n#if __aarch64__\n\treturn vcvtaq_s32_f32(a);\n#else\n\t__m128 half = vdupq_n_f32(0.5f);\n\tconst __m128 sign = vcvtq_f32_u32((vshrq_n_u32(vreinterpretq_u32_f32(a), 31)));\n\tconst __m128 aPlusHalf = vaddq_f32(a, half);\n\tconst __m128 aRound = vsubq_f32(aPlusHalf, sign);\n\treturn vcvtq_s32_f32(aRound);\n#endif\n}\n\n// Moves the least significant 32 bits of a to a 32-bit integer. https://msdn.microsoft.com/en-us/library/5z7a9642%28v=vs.90%29.aspx\nFORCE_INLINE int _mm_cvtsi128_si32(__m128i a)\n{\n\treturn vgetq_lane_s32(a, 0);\n}\n\n// Moves 32-bit integer a to the least significant 32 bits of an __m128 object, zero extending the upper bits. https://msdn.microsoft.com/en-us/library/ct3539ha%28v=vs.90%29.aspx\nFORCE_INLINE __m128i _mm_cvtsi32_si128(int a)\n{\n\t__m128i result = vdupq_n_s32(0);\n\treturn vsetq_lane_s32(a, result, 0);\n}\n\n\n// Applies a type cast to reinterpret four 32-bit floating point values passed in as a 128-bit parameter as packed 32-bit integers. https://msdn.microsoft.com/en-us/library/bb514099.aspx\nFORCE_INLINE __m128i _mm_castps_si128(__m128 a)\n{\n\treturn *(const __m128i *)&a;\n}\n\n// Applies a type cast to reinterpret four 32-bit integers passed in as a 128-bit parameter as packed 32-bit floating point values. https://msdn.microsoft.com/en-us/library/bb514029.aspx\nFORCE_INLINE __m128 _mm_castsi128_ps(__m128i a)\n{\n\treturn *(const __m128 *)&a;\n}\n\n// Loads 128-bit value. : https://msdn.microsoft.com/en-us/library/atzzad1h(v=vs.80).aspx\nFORCE_INLINE __m128i _mm_load_si128(const __m128i *p)\n{\n\treturn vld1q_s32((int32_t *)p);\n}\n\n// ******************************************\n// Miscellaneous Operations\n// ******************************************\n\n// Packs the 16 signed 16-bit integers from a and b into 8-bit integers and saturates. https://msdn.microsoft.com/en-us/library/k4y4f7w5%28v=vs.90%29.aspx\nFORCE_INLINE __m128i _mm_packs_epi16(__m128i a, __m128i b)\n{\n\treturn (__m128i)vcombine_s8(vqmovn_s16((int16x8_t)a), vqmovn_s16((int16x8_t)b));\n}\n\n// Packs the 16 signed 16 - bit integers from a and b into 8 - bit unsigned integers and saturates. https://msdn.microsoft.com/en-us/library/07ad1wx4(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_packus_epi16(const __m128i a, const __m128i b)\n{\n\treturn (__m128i)vcombine_u8(vqmovun_s16((int16x8_t)a), vqmovun_s16((int16x8_t)b));\n}\n\n// Packs the 8 signed 32-bit integers from a and b into signed 16-bit integers and saturates. https://msdn.microsoft.com/en-us/library/393t56f9%28v=vs.90%29.aspx\nFORCE_INLINE __m128i _mm_packs_epi32(__m128i a, __m128i b)\n{\n\treturn (__m128i)vcombine_s16(vqmovn_s32(a), vqmovn_s32(b));\n}\n\n// Interleaves the lower 8 signed or unsigned 8-bit integers in a with the lower 8 signed or unsigned 8-bit integers in b.  https://msdn.microsoft.com/en-us/library/xf7k860c%28v=vs.90%29.aspx\nFORCE_INLINE __m128i _mm_unpacklo_epi8(__m128i a, __m128i b)\n{\n\tint8x8_t a1 = (int8x8_t)vget_low_s16((int16x8_t)a);\n\tint8x8_t b1 = (int8x8_t)vget_low_s16((int16x8_t)b);\n\n\tint8x8x2_t result = vzip_s8(a1, b1);\n\n\treturn (__m128i)vcombine_s8(result.val[0], result.val[1]);\n}\n\n// Interleaves the lower 4 signed or unsigned 16-bit integers in a with the lower 4 signed or unsigned 16-bit integers in b.  https://msdn.microsoft.com/en-us/library/btxb17bw%28v=vs.90%29.aspx\nFORCE_INLINE __m128i _mm_unpacklo_epi16(__m128i a, __m128i b)\n{\n\tint16x4_t a1 = vget_low_s16((int16x8_t)a);\n\tint16x4_t b1 = vget_low_s16((int16x8_t)b);\n\n\tint16x4x2_t result = vzip_s16(a1, b1);\n\n\treturn (__m128i)vcombine_s16(result.val[0], result.val[1]);\n}\n\n// Interleaves the lower 2 signed or unsigned 32 - bit integers in a with the lower 2 signed or unsigned 32 - bit integers in b.  https://msdn.microsoft.com/en-us/library/x8atst9d(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_unpacklo_epi32(__m128i a, __m128i b)\n{\n\tint32x2_t a1 = vget_low_s32(a);\n\tint32x2_t b1 = vget_low_s32(b);\n\n\tint32x2x2_t result = vzip_s32(a1, b1);\n\n\treturn vcombine_s32(result.val[0], result.val[1]);\n}\n\n// Selects and interleaves the lower two single-precision, floating-point values from a and b. https://msdn.microsoft.com/en-us/library/25st103b%28v=vs.90%29.aspx\nFORCE_INLINE __m128 _mm_unpacklo_ps(__m128 a, __m128 b)\n{\n\tfloat32x2x2_t result = vzip_f32(vget_low_f32(a), vget_low_f32(b));\n\treturn vcombine_f32(result.val[0], result.val[1]);\n}\n\n// Selects and interleaves the upper two single-precision, floating-point values from a and b. https://msdn.microsoft.com/en-us/library/skccxx7d%28v=vs.90%29.aspx\nFORCE_INLINE __m128 _mm_unpackhi_ps(__m128 a, __m128 b)\n{\n\tfloat32x2x2_t result = vzip_f32(vget_high_f32(a), vget_high_f32(b));\n\treturn vcombine_f32(result.val[0], result.val[1]);\n}\n\n// Interleaves the upper 2 signed or unsigned 32-bit integers in a with the upper 2 signed or unsigned 32-bit integers in b.  https://msdn.microsoft.com/en-us/library/65sa7cbs(v=vs.100).aspx\nFORCE_INLINE __m128i _mm_unpackhi_epi32(__m128i a, __m128i b)\n{\n\tint32x2_t a1 = vget_high_s32(a);\n\tint32x2_t b1 = vget_high_s32(b);\n\n\tint32x2x2_t result = vzip_s32(a1, b1);\n\n\treturn vcombine_s32(result.val[0], result.val[1]);\n}\n\n// Extracts the selected signed or unsigned 16-bit integer from a and zero extends.  https://msdn.microsoft.com/en-us/library/6dceta0c(v=vs.100).aspx\n#define _mm_extract_epi16( a, imm ) vgetq_lane_s16((int16x8_t)a, imm)\n\n// ******************************************\n// Streaming Extensions\n// ******************************************\n\n// Guarantees that every preceding store is globally visible before any subsequent store.  https://msdn.microsoft.com/en-us/library/5h2w73d1%28v=vs.90%29.aspx\nFORCE_INLINE void _mm_sfence(void)\n{\n\t__sync_synchronize();\n}\n\n// Stores the data in a to the address p without polluting the caches.  If the cache line containing address p is already in the cache, the cache will be updated.Address p must be 16 - byte aligned.  https://msdn.microsoft.com/en-us/library/ba08y07y%28v=vs.90%29.aspx\nFORCE_INLINE void _mm_stream_si128(__m128i *p, __m128i a)\n{\n\t*p = a;\n}\n\n// Cache line containing p is flushed and invalidated from all caches in the coherency domain.\nFORCE_INLINE void _mm_clflush(void const*p) {\n\t// no corollary for Neon?\n}\n\n#endif\n"
  },
  {
    "path": "fdsst/fdssttracker.cpp",
    "content": "/*\n\nTracker based on Kernelized Correlation Filter (KCF) [1] and Circulant Structure with Kernels (CSK) [2].\nCSK is implemented by using raw gray level features, since it is a single-channel filter.\nKCF is implemented by using HOG features (the default), since it extends CSK to multiple channels.\n\n[1] J. F. Henriques, R. Caseiro, P. Martins, J. Batista,\n\"High-Speed Tracking with Kernelized Correlation Filters\", TPAMI 2015.\n\n[2] J. F. Henriques, R. Caseiro, P. Martins, J. Batista,\n\"Exploiting the Circulant Structure of Tracking-by-detection with Kernels\", ECCV 2012.\n\nAuthors: Joao Faro, Christian Bailer, Joao F. Henriques\nContacts: joaopfaro@gmail.com, Christian.Bailer@dfki.de, henriques@isr.uc.pt\nInstitute of Systems and Robotics - University of Coimbra / Department Augmented Vision DFKI\n\n\nConstructor parameters, all boolean:\n    hog: use HOG features (default), otherwise use raw pixels\n    fixed_window: fix window size (default), otherwise use ROI size (slower but more accurate)\n    multiscale: use multi-scale tracking (default; cannot be used with fixed_window = true)\n\nDefault values are set for all properties of the tracker depending on the above choices.\nTheir values can be customized further before calling init():\n    interp_factor: linear interpolation factor for adaptation\n    sigma: gaussian kernel bandwidth\n    lambda: regularization\n    cell_size: HOG cell size\n    padding: area surrounding the target, relative to its size\n    output_sigma_factor: bandwidth of gaussian target\n    template_size: template size in pixels, 0 to use ROI size\n    scale_step: scale step for multi-scale estimation, 1 to disable it\n    scale_weight: to downweight detection scores of other scales for added stability\n\nFor speed, the value (template_size/cell_size) should be a power of 2 or a product of small prime numbers.\n\nInputs to init():\n   image is the initial frame.\n   roi is a cv::Rect with the target positions in the initial frame\n\nInputs to update():\n   image is the current frame.\n\nOutputs of update():\n   cv::Rect with target positions for the current frame\n\n\nBy downloading, copying, installing or using the software you agree to this license.\nIf you do not agree to this license, do not download, install,\ncopy or use the software.\n\n\n                          License Agreement\n               For Open Source Computer Vision Library\n                       (3-clause BSD License)\n\nRedistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:\n\n  * Redistributions of source code must retain the above copyright notice,\n    this list of conditions and the following disclaimer.\n\n  * Redistributions in binary form must reproduce the above copyright notice,\n    this list of conditions and the following disclaimer in the documentation\n    and/or other materials provided with the distribution.\n\n  * Neither the names of the copyright holders nor the names of the contributors\n    may be used to endorse or promote products derived from this software\n    without specific prior written permission.\n\nThis software is provided by the copyright holders and contributors \"as is\" and\nany express or implied warranties, including, but not limited to, the implied\nwarranties of merchantability and fitness for a particular purpose are disclaimed.\nIn no event shall copyright holders or contributors be liable for any direct,\nindirect, incidental, special, exemplary, or consequential damages\n(including, but not limited to, procurement of substitute goods or services;\nloss of use, data, or profits; or business interruption) however caused\nand on any theory of liability, whether in contract, strict liability,\nor tort (including negligence or otherwise) arising in any way out of\nthe use of this software, even if advised of the possibility of such damage.\n */\n\n#if 1\n\n#include <time.h>\n\n#include \"fdssttracker.hpp\"\n#include \"ffttools.hpp\"\n#include \"recttools.hpp\"\n\n#include \"fhog.h\"\n\n#include \"labdata.hpp\"\n#include <glog/logging.h>\n\n// #define PFS_DEBUG\n\nstatic double t_start, t_end;\n\n\ntemplate <typename T>\ncv::Mat rangeToColVector(int begin, int end, int n)\n{\n\tcv::Mat_<T> colVec(1, n);\n\n\tfor (int i = begin, j = 0; i <= end; ++i, j++)\n\t\tcolVec.template at<T>(0, j) = static_cast<T>(i);\n\n\treturn colVec;\n}\n\n\ntemplate <typename BT, typename ET>\ncv::Mat pow(BT base_, const cv::Mat_<ET>& exponent)\n{\n\tcv::Mat dst = cv::Mat(exponent.rows, exponent.cols, exponent.type());\n\tint widthChannels = exponent.cols * exponent.channels();\n\tint height = exponent.rows;\n\n\t// http://docs.opencv.org/doc/tutorials/core/how_to_scan_images/how_to_scan_images.html#the-efficient-way\n\tif (exponent.isContinuous())\n\t{\n\t\twidthChannels *= height;\n\t\theight = 1;\n\t}\n\n\tint row = 0, col = 0;\n\tconst ET* exponentd = 0;\n\tET* dstd = 0;\n\n\tfor (row = 0; row < height; ++row)\n\t{\n\t\texponentd = exponent.template ptr<ET>(row);\n\t\tdstd = dst.template ptr<ET>(row);\n\n\t\tfor (col = 0; col < widthChannels; ++col)\n\t\t{\n\t\t\tdstd[col] = std::pow(base_, exponentd[col]);\n\t\t}\n\t}\n\n\treturn dst;\n}\n\nvoid shift(const cv::Mat& src, cv::Mat& dst, cv::Point2f delta, int fill, cv::Scalar value = cv::Scalar(0, 0, 0, 0)) {\n\t// error checking\n\tCV_Assert(fabs(delta.x) < src.cols && fabs(delta.y) < src.rows);\n\n\t// split the shift into integer and subpixel components\n\tcv::Point2i deltai(static_cast<int>(ceil(delta.x)), static_cast<int>(ceil(delta.y)));\n\tcv::Point2f deltasub(fabs(delta.x - deltai.x), fabs(delta.y - deltai.y));\n\n\t// INTEGER SHIFT\n\t// first create a border around the parts of the Mat that will be exposed\n\tint t = 0, b = 0, l = 0, r = 0;\n\tif (deltai.x > 0) l = deltai.x;\n\tif (deltai.x < 0) r = -deltai.x;\n\tif (deltai.y > 0) t = deltai.y;\n\tif (deltai.y < 0) b = -deltai.y;\n\tcv::Mat padded;\n\tcv::copyMakeBorder(src, padded, t, b, l, r, fill, value);\n\n\t// SUBPIXEL SHIFT\n\tfloat eps = std::numeric_limits<float>::epsilon();\n\tif (deltasub.x > eps || deltasub.y > eps) {\n\t\tswitch (src.depth()) {\n\t\tcase CV_32F:\n\t\t{\n\t\t\tcv::Matx<float, 1, 2> dx(1 - deltasub.x, deltasub.x);\n\t\t\tcv::Matx<float, 2, 1> dy(1 - deltasub.y, deltasub.y);\n\t\t\tsepFilter2D(padded, padded, -1, dx, dy, cv::Point(0, 0), 0, cv::BORDER_CONSTANT);\n\t\t\tbreak;\n\t\t}\n\t\tcase CV_64F:\n\t\t{\n\t\t\tcv::Matx<double, 1, 2> dx(1 - deltasub.x, deltasub.x);\n\t\t\tcv::Matx<double, 2, 1> dy(1 - deltasub.y, deltasub.y);\n\t\t\tsepFilter2D(padded, padded, -1, dx, dy, cv::Point(0, 0), 0, cv::BORDER_CONSTANT);\n\t\t\tbreak;\n\t\t}\n\t\tdefault:\n\t\t{\n\t\t\tcv::Matx<float, 1, 2> dx(1 - deltasub.x, deltasub.x);\n\t\t\tcv::Matx<float, 2, 1> dy(1 - deltasub.y, deltasub.y);\n\t\t\tpadded.convertTo(padded, CV_32F);\n\t\t\tsepFilter2D(padded, padded, CV_32F, dx, dy, cv::Point(0, 0), 0, cv::BORDER_CONSTANT);\n\t\t\tbreak;\n\t\t}\n\t\t}\n\t}\n\n\t// construct the region of interest around the new matrix\n\tcv::Rect roi = cv::Rect(std::max(-deltai.x, 0), std::max(-deltai.y, 0), 0, 0) + src.size();\n\t//xyz2017.06.17 cv::Rect roi = cv::Rect(max(-deltai.x, 0), max(-deltai.y, 0), 0, 0) + src.size();\n\tdst = padded(roi);\n}\n\n\n\n\n\n// Constructor\nFDSSTTracker::FDSSTTracker(bool hog, bool fixed_window, bool multiscale, bool lab)\n{\n\tReset();\n    // Parameters equal in all cases\n    lambda = 0.0001;\n    padding = 2.5;\n    //output_sigma_factor = 0.1;\n    output_sigma_factor = 0.125;\n\n    if (hog) {    // HOG\n        // VOT\n        interp_factor = 0.015;\n        sigma = 0.6;\n        // TPAMI\n        //interp_factor = 0.02;\n        //sigma = 0.5;\n        cell_size = 4;\n        _hogfeatures = true;\n\n\t\tnum_compressed_dim = 13;\n\n        if (lab) {\n            interp_factor = 0.005;\n            sigma = 0.4;\n            //output_sigma_factor = 0.025;\n            output_sigma_factor = 0.1;\n\n            _labfeatures = true;\n            _labCentroids = cv::Mat(nClusters, 3, CV_32FC1, &data);\n            cell_sizeQ = cell_size*cell_size;\n        }\n        else{\n            _labfeatures = false;\n        }\n    }\n    else {   // RAW\n        interp_factor = 0.075;\n        sigma = 0.2;\n        cell_size = 1;\n        _hogfeatures = false;\n\n        if (lab) {\n            LOG(ERROR) << \"Lab features are only used with HOG features.\\n\";\n            _labfeatures = false;\n        }\n    }\n\n\n\n\n    if (multiscale) { // multiscale\n        template_size = 96;\n        //scale parameters initial\n        scale_padding = 1.0;\n        scale_step = 1.05;\n        scale_sigma_factor = 1.0 / 16;\n\n\t\tn_scales = 9;\n        n_interp_scales = 33;\n\n        scale_lr = 0.025;\n        scale_max_area = 512;\n        currentScaleFactor = 1;\n        scale_lambda = 0.01;\n\n        if (!fixed_window) {\n            fixed_window = true;\n        }\n    }\n    else if (fixed_window) {  // fit correction without multiscale\n        template_size = 96;\n        //template_size = 100;\n        scale_step = 1;\n\t\t// begin xyz add ==================\n\t\ttemplate_size = 64;\n\t\tcurrentScaleFactor = 1;\n\t\tn_scales = 3;\n\t\tn_interp_scales = 1;\n        \tscale_max_area = 256;\n\t\tcell_size = 8;\n\t\t// end xyz add ==================\n    }\n    else {\n        template_size = 1;\n        scale_step = 1;\n    }\n    success_ = true;\n}\n\n// Initialize tracker\n// Initialize tracker\nvoid FDSSTTracker::init(const cv::Rect &roi, cv::Mat image)\n{\n\t_roi = roi;\n\tassert(roi.width >= 0 && roi.height >= 0);\n\t_tmpl = getFeatures(image, 1);\n\tif(!success_){\n\t\treturn;\n\t}\n\t_prob = createGaussianPeak(size_patch[0], size_patch[1]);\n\t_alphaf = cv::Mat(size_patch[0], size_patch[1], CV_32FC2, float(0));\n\n\tdsstInit(roi, image);\n\t//_num = cv::Mat(size_patch[0], size_patch[1], CV_32FC2, float(0));\n\t//_den = cv::Mat(size_patch[0], size_patch[1], CV_32FC2, float(0));\n\ttrain(_tmpl, 1.0); // train with initial frame\n}\n\n// Update position based on the new frame\ncv::Rect FDSSTTracker::update(cv::Mat image)\n{\n    if(!success_){\n\treturn cv::Rect(0, 0, 0, 0);\n    }\n    if (_roi.x + _roi.width <= 0) _roi.x = -_roi.width + 1;\n    if (_roi.y + _roi.height <= 0) _roi.y = -_roi.height + 1;\n    if (_roi.x >= image.cols - 1) _roi.x = image.cols - 2;\n    if (_roi.y >= image.rows - 1) _roi.y = image.rows - 2;\n\n    float cx = _roi.x + _roi.width / 2.0f;\n    float cy = _roi.y + _roi.height / 2.0f;\n\n    float peak_value;\n\n#ifdef PFS_DEBUG\n\tt_start = clock();\n#endif\n    cv::Point2f res = detect(getFeatures(image, 0, 1.0f), peak_value);\n    if(!success_){\n\treturn cv::Rect(0, 0, 0, 0);\n    }\n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"translation detction duration: \" << (t_end - t_start) / CLOCKS_PER_SEC << \"\\n\";\n#endif\n    // Adjust by cell size and _scale\n    _roi.x = cx - _roi.width / 2.0f + ((float) res.x * cell_size * _scale * currentScaleFactor);\n    _roi.y = cy - _roi.height / 2.0f + ((float) res.y * cell_size * _scale * currentScaleFactor);\n\n    if (_roi.x >= image.cols - 1) _roi.x = image.cols - 1;\n    if (_roi.y >= image.rows - 1) _roi.y = image.rows - 1;\n    if (_roi.x + _roi.width <= 0) _roi.x = -_roi.width + 2;\n    if (_roi.y + _roi.height <= 0) _roi.y = -_roi.height + 2;\n\n    // Update scale\n\n#ifdef PFS_DEBUG\n\tt_start = clock();\n#endif\n    cv::Point2i scale_pi = detect_scale(image);\n    if(!success_){\n        return cv::Rect(0, 0, 0, 0);\n    }\n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"scale detction duration: \" << (t_end - t_start) / CLOCKS_PER_SEC << \"\\n\";\n#endif  \n\tcurrentScaleFactor = currentScaleFactor * interp_scaleFactors[scale_pi.x];\n//\tstd::cout << currentScaleFactor<<\"\\n\";\n    if(currentScaleFactor < min_scale_factor)\n      currentScaleFactor = min_scale_factor;\n    // else if(currentScaleFactor > max_scale_factor)\n    //   currentScaleFactor = max_scale_factor;\n\n\tupdate_roi();\n\n    train_scale(image);\n\n    if (_roi.x >= image.cols - 1) _roi.x = image.cols - 1;\n    if (_roi.y >= image.rows - 1) _roi.y = image.rows - 1;\n    if (_roi.x + _roi.width <= 0) _roi.x = -_roi.width + 2;\n    if (_roi.y + _roi.height <= 0) _roi.y = -_roi.height + 2;\n\n\n    assert(_roi.width >= 0 && _roi.height >= 0);\n    cv::Mat x = getFeatures(image, 0);\n    if(!success_){\n\treturn cv::Rect(0, 0, 0, 0);\n    }\n    train(x, interp_factor);\n\n\n    return _roi;\n}\n\n// Detect the new scaling rate\ncv::Point2i FDSSTTracker::detect_scale(cv::Mat image)\n{\n  cv::Mat xsf = FDSSTTracker::get_scale_sample(image);\n  if(!success_){\n    return cv::Point2i(0, 0);\n  }\n\n  // Compute AZ in the paper\n  cv::Mat add_temp;\n  cv::reduce(FFTTools::complexMultiplication(sf_num, xsf), add_temp, 0, CV_REDUCE_SUM);\n\n  // compute the final y\n  cv::Mat scale_responsef = FFTTools::complexDivisionReal(add_temp, (sf_den + scale_lambda));\n\n  cv::Mat interp_scale_responsef = resizeDFT(scale_responsef, n_interp_scales);\n\n  cv::Mat interp_scale_response;\n  cv::idft(interp_scale_responsef, interp_scale_response);\n\n  interp_scale_response = FFTTools::real(interp_scale_response);\n\n  // Get the max point as the final scaling rate\n  cv::Point2i pi;\n  double pv;\n  cv::minMaxLoc(interp_scale_response, NULL, &pv, NULL, &pi);\n\n  return pi;\n}\n\n// Detect object in the current frame.\ncv::Point2f FDSSTTracker::detect(cv::Mat x, float &peak_value)\n{\n\tif(x.empty()){\n\t\treturn cv::Point2f(0, 0);\n\t}\n\tusing namespace FFTTools;\n\n\tx = features_projection(x);\n\n\tcv::Mat z = features_projection(_tmpl);\n#ifdef PFS_DEBUG\n\tdouble t_start1 = clock();\n#endif\n\tcv::Mat k = gaussianCorrelation(x, z);\n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"**************gaussianCorrelation duration: \" << (t_end - t_start1) / CLOCKS_PER_SEC << \"\\n\";\n#endif \n\n#ifdef PFS_DEBUG\n\tt_start = clock();\n#endif\n\n\tcv::Mat res = (real(fftd(complexMultiplication(_alphaf, fftd(k)), true)));\n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"complexMultiplication *******************: \" << (t_end - t_start) / CLOCKS_PER_SEC << \"\\n\";\n#endif \n\t//minMaxLoc only accepts doubles for the peak, and integer points for the coordinates\n\tcv::Point2i pi;\n\tdouble pv;\n\n\tcv::minMaxLoc(res, NULL, &pv, NULL, &pi);\n\n\tpeak_value = (float)pv;\n\n\t//subpixel peak estimation, coordinates will be non-integer\n\tcv::Point2f p((float)pi.x, (float)pi.y);\n\n\tif (pi.x > 0 && pi.x < res.cols - 1) {\n\t\tp.x += subPixelPeak(res.at<float>(pi.y, pi.x - 1), peak_value, res.at<float>(pi.y, pi.x + 1));\n\t}\n\n\tif (pi.y > 0 && pi.y < res.rows - 1) {\n\t\tp.y += subPixelPeak(res.at<float>(pi.y - 1, pi.x), peak_value, res.at<float>(pi.y + 1, pi.x));\n\t}\n\n\n\n\tp.x -= (res.cols) / 2;\n\tp.y -= (res.rows) / 2;\n\n\treturn p;\n}\n\n\n// train tracker with a single image\nvoid FDSSTTracker::train(cv::Mat x, float train_interp_factor)\n{\n\tusing namespace FFTTools;\n\n\t_tmpl = (1 - train_interp_factor) * _tmpl + (train_interp_factor)* x;\n\n\tcv::Mat W, U, VT, X, out;\n\n\tX = _tmpl * _tmpl.t();\n\tcv::SVD::compute(X, W, U, VT);\n\n\tVT.rowRange(0, num_compressed_dim).copyTo(proj_matrix);\n\n\tx = features_projection(x);\n\t\n\tcv::Mat k = gaussianCorrelation(x, x);\n\tcv::Mat alphaf = complexDivision(_prob, (fftd(k) + lambda));\n\n\t_alphaf = (1 - train_interp_factor) * _alphaf + (train_interp_factor)* alphaf;\n\n\n}\n\n// Evaluates a Gaussian kernel with bandwidth SIGMA for all relative shifts between input images X and Y, which must both be MxN. They must    also be periodic (ie., pre-processed with a cosine window).\ncv::Mat FDSSTTracker::gaussianCorrelation(cv::Mat x1, cv::Mat x2)\n{\n    using namespace FFTTools;\n   \n#ifdef PFS_DEBUG\n\tdouble t_start1 = clock();\n#endif\t\t\t\n\t\n\tcv::Mat c = cv::Mat( cv::Size(size_patch[1], size_patch[0]), CV_32F, cv::Scalar(0) );\n    // HOG features\n\n\n    if (_hogfeatures) {\n        cv::Mat caux;\n        cv::Mat x1aux;\n        cv::Mat x2aux;\n        for (int i = 0; i < size_patch[2]; i++) {\n            x1aux = x1.row(i);   // Procedure do deal with cv::Mat multichannel bug\n            x1aux = x1aux.reshape(1, size_patch[0]);\n            x2aux = x2.row(i).reshape(1, size_patch[0]);\n            \n\n\t\t\tcv::mulSpectrums(fftd(x1aux), fftd(x2aux), caux, 0, true);\n            caux = fftd(caux, true);\n\n            rearrange(caux);\n            caux.convertTo(caux,CV_32F);\n            c = c + real(caux);\n\n        }\n    }\n    // Gray features\n    else {\n        cv::mulSpectrums(fftd(x1), fftd(x2), c, 0, true);\n        c = fftd(c, true);\n        rearrange(c);\n        c = real(c);\n    }\n\n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"gaussianCorrelation computation A duration: \" << (t_end - t_start1) / CLOCKS_PER_SEC << \"\\n\";\n#endif\n\n    cv::Mat d;\n\tcv::max(( (cv::sum(x1.mul(x1))[0] + cv::sum(x2.mul(x2))[0])- 2. * c) / (size_patch[0]*size_patch[1]*size_patch[2]) , \n\t\t0, \n\t\td);\n\t//xyz2017.06.17 cvmax(((cv::sum(x1.mul(x1))[0] + cv::sum(x2.mul(x2))[0]) - 2. * c) / (size_patch[0] * size_patch[1] * size_patch[2]),\n\t//\t0, d);\n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"gaussianCorrelation computation B duration: \" << (t_end - t_start1) / CLOCKS_PER_SEC << \"\\n\";\n#endif \n    cv::Mat k;\n    cv::exp((-d / (sigma * sigma)), k);\n   \n#ifdef PFS_DEBUG\n\tt_end = clock();\n\tstd::cout << \"gaussianCorrelation computation ALL duration: \" << (t_end - t_start1) / CLOCKS_PER_SEC << \"\\n\";\n#endif \n\t\n\treturn k;\n}\n\n\n// Create Gaussian Peak. Function called only in the first frame.\ncv::Mat FDSSTTracker::createGaussianPeak(int sizey, int sizex)\n{\n\tcv::Mat_<float> res(sizey, sizex);\n\n\tint syh = (sizey) / 2;\n\tint sxh = (sizex) / 2;\n\n\tfloat output_sigma = std::sqrt((float)sizex * sizey) / padding * output_sigma_factor;\n\tfloat mult = -0.5 / (output_sigma * output_sigma);\n\n\tfor (int i = 0; i < sizey; i++)\n\t\tfor (int j = 0; j < sizex; j++)\n\t\t{\n\t\t\tint ih = i - syh;\n\t\t\tint jh = j - sxh;\n\t\t\tres(i, j) = std::exp(mult * (float)(ih * ih + jh * jh));\n\t\t}\n\treturn FFTTools::fftd(res);\n}\n\n// Obtain sub-window from image, with replication-padding and extract features\ncv::Mat FDSSTTracker::getFeatures(const cv::Mat & image, bool inithann, float scale_adjust)\n{\n    cv::Rect extracted_roi;\n\n    float cx = _roi.x + _roi.width / 2;\n    float cy = _roi.y + _roi.height / 2;\n\n    if (inithann) {\n        int padded_w = _roi.width * padding;\n        int padded_h = _roi.height * padding;\n\n        if (template_size > 1) {  // Fit largest dimension to the given template size\n            if (padded_w >= padded_h)  //fit to width\n                _scale = padded_w / (float) template_size;\n            else\n                _scale = padded_h / (float) template_size;\n\n            _tmpl_sz.width = padded_w / _scale;\n            _tmpl_sz.height = padded_h / _scale;\n        }\n        else {  //No template size given, use ROI size\n            _tmpl_sz.width = padded_w;\n            _tmpl_sz.height = padded_h;\n            _scale = 1;\n            // original code from paper:\n            /*if (sqrt(padded_w * padded_h) >= 100) {   //Normal size\n                _tmpl_sz.width = padded_w;\n                _tmpl_sz.height = padded_h;\n                _scale = 1;\n            }\n            else {   //ROI is too big, track at half size\n                _tmpl_sz.width = padded_w / 2;\n                _tmpl_sz.height = padded_h / 2;\n                _scale = 2;\n            }*/\n        }\n\n        if (_hogfeatures) {\n            // Round to cell size and also make it even\n            _tmpl_sz.width = ( ( (int)(_tmpl_sz.width / (2 * cell_size)) ) * 2 * cell_size ) + cell_size*2;\n            _tmpl_sz.height = ( ( (int)(_tmpl_sz.height / (2 * cell_size)) ) * 2 * cell_size ) + cell_size*2;\n        }\n        else {  //Make number of pixels even (helps with some logic involving half-dimensions)\n            _tmpl_sz.width = (_tmpl_sz.width / 2) * 2;\n            _tmpl_sz.height = (_tmpl_sz.height / 2) * 2;\n        }\n    }\n\n    extracted_roi.width = scale_adjust * _scale * _tmpl_sz.width * currentScaleFactor;\n    extracted_roi.height = scale_adjust * _scale * _tmpl_sz.height * currentScaleFactor;\n\n    // center roi with new size\n    extracted_roi.x = cx - extracted_roi.width / 2;\n    extracted_roi.y = cy - extracted_roi.height / 2;\n\n    cv::Mat FeaturesMap;\n    cv::Mat z = RectTools::subwindow(image, extracted_roi, cv::BORDER_REPLICATE);\n\n    if (z.cols != _tmpl_sz.width || z.rows != _tmpl_sz.height) {\n        cv::resize(z, z, _tmpl_sz);\n    }\n\n    // HOG features   \n\tFeaturesMap = fhog(z,cell_size );\n\tif(FeaturesMap.empty()){\n\t\tsuccess_ = false;\n\t\treturn FeaturesMap;\n\t}\n\n\tFeaturesMap = FeaturesMap.reshape(1, z.cols * z.rows / (cell_size * cell_size));\n\n\tFeaturesMap = FeaturesMap.t();\n\n    if (inithann) {\n\t\tsize_patch[0] = z.rows / cell_size;\n\t\tsize_patch[1] = z.cols / cell_size;\n\t\tsize_patch[2] = num_compressed_dim;\n        createHanningMats();\n    }\n\n\n    return FeaturesMap;\n}\n\n\ncv::Mat FDSSTTracker::features_projection(const cv::Mat &FeaturesMap)\n{\n\n\tcv::Mat out;\n\tout = proj_matrix * FeaturesMap;\n\n\tout = hann.mul(out);\n\n\treturn out;\n}\n\n// Initialize Hanning window. Function called only in the first frame.\nvoid FDSSTTracker::createHanningMats()\n{\n    cv::Mat hann1t = cv::Mat(cv::Size(size_patch[1],1), CV_32F, cv::Scalar(0));\n    cv::Mat hann2t = cv::Mat(cv::Size(1,size_patch[0]), CV_32F, cv::Scalar(0));\n\n    for (int i = 0; i < hann1t.cols; i++)\n        hann1t.at<float > (0, i) = 0.5 * (1 - std::cos(2 * 3.14159265358979323846 * i / (hann1t.cols - 1)));\n    for (int i = 0; i < hann2t.rows; i++)\n        hann2t.at<float > (i, 0) = 0.5 * (1 - std::cos(2 * 3.14159265358979323846 * i / (hann2t.rows - 1)));\n\n    cv::Mat hann2d = hann2t * hann1t;\n\t// HOG features\n\tif (_hogfeatures) {\n\t\tcv::Mat hann1d = hann2d.reshape(1, 1); // Procedure do deal with cv::Mat multichannel bug\n\n\t\thann = cv::Mat(cv::Size(size_patch[0] * size_patch[1], size_patch[2]), CV_32F, cv::Scalar(0));\n\t\tfor (int i = 0; i < size_patch[2]; i++) {\n\t\t\tfor (int j = 0; j<size_patch[0] * size_patch[1]; j++) {\n\t\t\t\thann.at<float>(i, j) = hann1d.at<float>(0, j);\n\t\t\t}\n\t\t}\n\t}\n\t// Gray features\n\telse {\n\t\thann = hann2d;\n\t}\n}\n\n// Calculate sub-pixel peak for one dimension\nfloat FDSSTTracker::subPixelPeak(float left, float center, float right)\n{\n    float divisor = 2 * center - right - left;\n\n    if (divisor == 0)\n        return 0;\n\n    return 0.5 * (right - left) / divisor;\n}\n\n// Initialization for scales\nvoid FDSSTTracker::dsstInit(const cv::Rect &roi, cv::Mat image)\n{\n  // The initial size for adjusting\n  base_width = roi.width;\n  base_height = roi.height;\n\n  // Guassian peak for scales (after fft)\n\n  // ֵǰĳ߶УҪȡ߶һֵ\n  cv::Mat colScales =\n\t  rangeToColVector<float>(-floor((n_scales - 1) / 2),\n\t  ceil((n_scales - 1) / 2), n_scales);\n\n  colScales *= (float)n_interp_scales / (float)n_scales;\n\n  cv::Mat ss;\n  shift(colScales, ss,\n\t  cv::Point(-floor(((float)n_scales - 1) / 2), 0),\n\t  cv::BORDER_WRAP, cv::Scalar(0, 0, 0, 0));\n\n  cv::Mat ys;\n\n  float scale_sigma = scale_sigma_factor * n_interp_scales;\n\n  exp(-0.5 * ss.mul(ss) / (scale_sigma * scale_sigma), ys);\n\n\n  ysf = FFTTools::fftd(ys);\n\n  s_hann = createHanningMatsForScale();\n\n  // Get all scale changing rate\n  scaleFactors = pow<float, float>(scale_step, colScales);\n  \n\n  // ֵĳ߶\n  cv::Mat interp_colScales =\n\t  rangeToColVector<float>(-floor((n_interp_scales - 1) / 2),\n\t  ceil((n_interp_scales - 1) / 2), n_interp_scales);\n\n  cv::Mat ss_interp;\n  shift(interp_colScales, ss_interp,\n\t  cv::Point(-floor(((float)n_interp_scales - 1) / 2), 0),\n\t  cv::BORDER_WRAP, cv::Scalar(0, 0, 0, 0));\n\n  interp_scaleFactors = pow<float, float>(scale_step, ss_interp);\n\n\n\n\n  // Get the scaling rate for compressing to the model size\n  float scale_model_factor = 1;\n  if(base_width * base_height > scale_max_area)\n  {\n    scale_model_factor = std::sqrt(scale_max_area / (float)(base_width * base_height));\n  }\n  scale_model_width = (int)(base_width * scale_model_factor);\n  scale_model_height = (int)(base_height * scale_model_factor);\n\n  // Compute min and max scaling rate\n  min_scale_factor = std::pow(scale_step,\n    std::ceil(std::log((std::fmax(5 / (float) base_width, 5 / (float) base_height) * (1 + scale_padding))) / 0.0086));\n  max_scale_factor = std::pow(scale_step,\n    std::floor(std::log(std::fmin(image.rows / (float) base_height, image.cols / (float) base_width)) / 0.0086));\n\n  train_scale(image, true);\n\n}\n\n// Train method for scaling\nvoid FDSSTTracker::train_scale(cv::Mat image, bool ini)\n{\n  cv::Mat xsf = get_scale_sample(image);\n  if(!success_){\n\treturn;\n  }\n  // Adjust ysf to the same size as xsf in the first time\n  if(ini)\n  {\n    int totalSize = xsf.rows;\n    ysf = cv::repeat(ysf, totalSize, 1);\n  }\n\n  // Get new GF in the paper (delta A)\n  cv::Mat new_sf_num;\n  cv::mulSpectrums(ysf, xsf, new_sf_num, 0, true);\n\n  // Get Sigma{FF} in the paper (delta B)\n  cv::Mat new_sf_den;\n  cv::mulSpectrums(xsf, xsf, new_sf_den, 0, true);\n  cv::reduce(FFTTools::real(new_sf_den), new_sf_den, 0, CV_REDUCE_SUM);\n\n  if(ini)\n  {\n    sf_den = new_sf_den;\n    sf_num = new_sf_num;\n  }else\n  {\n    // Get new A and new B\n    cv::addWeighted(sf_den, (1 - scale_lr), new_sf_den, scale_lr, 0, sf_den);\n    cv::addWeighted(sf_num, (1 - scale_lr), new_sf_num, scale_lr, 0, sf_num);\n  }\n\n  update_roi();\n\n}\n\n// Update the ROI size after training\nvoid FDSSTTracker::update_roi()\n{\n  // Compute new center\n  float cx = _roi.x + _roi.width / 2.0f;\n  float cy = _roi.y + _roi.height / 2.0f;\n\n\n  // Recompute the ROI left-upper point and size\n  _roi.width = base_width * currentScaleFactor;\n  _roi.height = base_height * currentScaleFactor;\n\n  _roi.x = cx - _roi.width / 2.0f;\n  _roi.y = cy - _roi.height / 2.0f;\n\n}\n\n// Compute the F^l in the paper\ncv::Mat FDSSTTracker::get_scale_sample(const cv::Mat & image)\n{\n  \n  cv::Mat xsf; // output\n  int totalSize; // # of features\n\n  for(int i = 0; i < n_scales; i++)\n  {\n    // Size of subwindow waiting to be detect\n    float patch_width = base_width * scaleFactors[i] * currentScaleFactor;\n    float patch_height = base_height * scaleFactors[i] * currentScaleFactor;\n\n    float cx = _roi.x + _roi.width / 2.0f;\n    float cy = _roi.y + _roi.height / 2.0f;\n\n    // Get the subwindow\n    cv::Mat im_patch = RectTools::extractImage(image, cx, cy, patch_width, patch_height);\n    cv::Mat im_patch_resized;\n\n    // Scaling the subwindow\n\tif(im_patch.cols<=0 || im_patch.rows<=0 || scale_model_width<=0 || scale_model_height<=0){\n\t\tsuccess_ = false;\n\t\treturn xsf;\n\t}\n    if(scale_model_width > im_patch.cols)\n\t\tresize(im_patch, im_patch_resized, cv::Size(scale_model_width, scale_model_height), 0, 0, cv::INTER_NEAREST);\n    else{\n      resize(im_patch, im_patch_resized, cv::Size(scale_model_width, scale_model_height), 0, 0, cv::INTER_NEAREST);\n      //resize(im_patch, im_patch_resized, cv::Size(im_patch.cols, im_patch.rows), 0, 0, cv::INTER_LINEAR);\n    }\n    // Compute the FHOG features for the subwindow\n\tcv::Mat hogs = fhog(im_patch_resized, cell_size);\n\tif(hogs.empty()){\n\t\tsuccess_ = false;\n\t\treturn xsf;\n\t}\n    if(i == 0)\n    {\n\t\ttotalSize = hogs.cols * hogs.rows * 32;\n      xsf = cv::Mat(cv::Size(n_scales,totalSize), CV_32F, float(0));\n    }\n\n    // Multiply the FHOG results by hanning window and copy to the output\n\tcv::Mat FeaturesMap = hogs.reshape(1, totalSize);\n    float mul = s_hann.at<float > (0, i);\n    FeaturesMap = mul * FeaturesMap;\n    FeaturesMap.copyTo(xsf.col(i));\n\n  }\n\n \n  // Do fft to the FHOG features row by row\n  xsf = FFTTools::fftd(xsf, 0, 1);\n\n  return xsf;\n}\n\n// Compute the FFT Guassian Peak for scaling\ncv::Mat FDSSTTracker::computeYsf()\n{\n    float scale_sigma2 = n_scales / std::sqrt(n_scales) * scale_sigma_factor;\n    scale_sigma2 = scale_sigma2 * scale_sigma2;\n    cv::Mat res(cv::Size(n_scales, 1), CV_32F, float(0));\n    float ceilS = std::ceil(n_scales / 2.0f);\n\n    for(int i = 0; i < n_scales; i++)\n    {\n      res.at<float>(0,i) = std::exp(- 0.5 * std::pow(i + 1- ceilS, 2) / scale_sigma2);\n    }\n\n    return FFTTools::fftd(res);\n\n}\n\n// Compute the hanning window for scaling\ncv::Mat FDSSTTracker::createHanningMatsForScale()\n{\n  cv::Mat hann_s = cv::Mat(cv::Size(n_scales, 1), CV_32F, cv::Scalar(0));\n  for (int i = 0; i < hann_s.cols; i++)\n      hann_s.at<float > (0, i) = 0.5 * (1 - std::cos(2 * 3.14159265358979323846 * i / (hann_s.cols - 1)));\n\n  return hann_s;\n}\n\n\ncv::Mat FDSSTTracker::resizeDFT(const cv::Mat &A, int real_scales)\n{\n\tfloat scaling = (float)real_scales / n_scales;\n\n\tcv::Mat M = cv::Mat(cv::Size(real_scales, 1), CV_32FC2, cv::Scalar(0));\n\n\tint mids = ceil(n_scales / 2);\n\tint mide = floor((n_scales - 1) / 2) - 1;\n\n\tA *= scaling;\n\n\tA(cv::Range::all(), cv::Range(0, mids)).copyTo(M(cv::Range::all(), cv::Range(0, mids)));\n\n\tA(cv::Range::all(), cv::Range(n_scales - mide - 1, n_scales)).copyTo(M(cv::Range::all(), cv::Range(real_scales - mide - 1, real_scales)));\n\n\treturn M;\n}\n#endif\n"
  },
  {
    "path": "fdsst/fdssttracker.hpp",
    "content": "/*\n\nTracker based on Kernelized Correlation Filter (KCF) [1] and Circulant Structure with Kernels (CSK) [2].\nCSK is implemented by using raw gray level features, since it is a single-channel filter.\nKCF is implemented by using HOG features (the default), since it extends CSK to multiple channels.\n\n[1] J. F. Henriques, R. Caseiro, P. Martins, J. Batista,\n\"High-Speed Tracking with Kernelized Correlation Filters\", TPAMI 2015.\n\n[2] J. F. Henriques, R. Caseiro, P. Martins, J. Batista,\n\"Exploiting the Circulant Structure of Tracking-by-detection with Kernels\", ECCV 2012.\n\nAuthors: Joao Faro, Christian Bailer, Joao F. Henriques\nContacts: joaopfaro@gmail.com, Christian.Bailer@dfki.de, henriques@isr.uc.pt\nInstitute of Systems and Robotics - University of Coimbra / Department Augmented Vision DFKI\n\n\nConstructor parameters, all boolean:\n    hog: use HOG features (default), otherwise use raw pixels\n    fixed_window: fix window size (default), otherwise use ROI size (slower but more accurate)\n    multiscale: use multi-scale tracking (default; cannot be used with fixed_window = true)\n\nDefault values are set for all properties of the tracker depending on the above choices.\nTheir values can be customized further before calling init():\n    interp_factor: linear interpolation factor for adaptation\n    sigma: gaussian kernel bandwidth\n    lambda: regularization\n    cell_size: HOG cell size\n    padding: horizontal area surrounding the target, relative to its size\n    output_sigma_factor: bandwidth of gaussian target\n    template_size: template size in pixels, 0 to use ROI size\n    scale_step: scale step for multi-scale estimation, 1 to disable it\n    scale_weight: to downweight detection scores of other scales for added stability\n\nFor speed, the value (template_size/cell_size) should be a power of 2 or a product of small prime numbers.\n\nInputs to init():\n   image is the initial frame.\n   roi is a cv::Rect with the target positions in the initial frame\n\nInputs to update():\n   image is the current frame.\n\nOutputs of update():\n   cv::Rect with target positions for the current frame\n\n\nBy downloading, copying, installing or using the software you agree to this license.\nIf you do not agree to this license, do not download, install,\ncopy or use the software.\n\n\n                          License Agreement\n               For Open Source Computer Vision Library\n                       (3-clause BSD License)\n\nRedistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:\n\n  * Redistributions of source code must retain the above copyright notice,\n    this list of conditions and the following disclaimer.\n\n  * Redistributions in binary form must reproduce the above copyright notice,\n    this list of conditions and the following disclaimer in the documentation\n    and/or other materials provided with the distribution.\n\n  * Neither the names of the copyright holders nor the names of the contributors\n    may be used to endorse or promote products derived from this software\n    without specific prior written permission.\n\nThis software is provided by the copyright holders and contributors \"as is\" and\nany express or implied warranties, including, but not limited to, the implied\nwarranties of merchantability and fitness for a particular purpose are disclaimed.\nIn no event shall copyright holders or contributors be liable for any direct,\nindirect, incidental, special, exemplary, or consequential damages\n(including, but not limited to, procurement of substitute goods or services;\nloss of use, data, or profits; or business interruption) however caused\nand on any theory of liability, whether in contract, strict liability,\nor tort (including negligence or otherwise) arising in any way out of\nthe use of this software, even if advised of the possibility of such damage.\n */\n\n#pragma once\n\n#include \"tracker.h\"\n\n\n\n#if 0\nclass FDSSTTracker {\npublic:\n\tFDSSTTracker(bool hog = true, bool fixed_window = true, bool multiscale = true, bool lab = true) {\n\n\t}\n\n\t// Initialize tracker\n\tvirtual void init(const cv::Rect &roi, cv::Mat image) {\n\t\trc_ = roi;\n\t}\n\n\t// Update position based on the new frame\n\tvirtual cv::Rect update(cv::Mat image) {\n\t\treturn rc_;\n\t}\nprivate:\n\tcv::Rect rc_;\n};\n#else\n\n\nclass FDSSTTracker : public Tracker\n{\npublic:\n\n\n    // Constructor\n    FDSSTTracker(bool hog = true, bool fixed_window = true, bool multiscale = true, bool lab = true);\n\n    // Initialize tracker\n    virtual void init(const cv::Rect &roi, cv::Mat image);\n\n    // Update position based on the new frame\n    virtual cv::Rect update(cv::Mat image);\n\n    float interp_factor; // linear interpolation factor for adaptation\n    float sigma; // gaussian kernel bandwidth\n    float lambda; // regularization\n    int cell_size; // HOG cell size\n    int cell_sizeQ; // cell size^2, to avoid repeated operations\n    float padding; // extra area surrounding the target\n    float output_sigma_factor; // bandwidth of gaussian target\n    int template_size; // template size\n\n    int base_width; // initial ROI widt\n    int base_height; // initial ROI height\n    int scale_max_area; // max ROI size before compressing\n    float scale_padding; // extra area surrounding the target for scaling\n    float scale_step; // scale step for multi-scale estimation\n    float scale_sigma_factor; // bandwidth of gaussian target\n    \n\tint n_scales; // # of scaling windows\n\tint n_interp_scales; // of interpolation scales\n    \n\tint num_compressed_dim;\n\n\tfloat scale_lr; // scale learning rate\n    \n\tstd::vector<float> scaleFactors; // all scale changing rate, from larger to smaller with 1 to be the middle\n\tstd::vector<float> interp_scaleFactors;\n\n    int scale_model_width; // the model width for scaling\n    int scale_model_height; // the model height for scaling\n    float currentScaleFactor; // scaling rate\n    float min_scale_factor; // min scaling rate\n    float max_scale_factor; // max scaling rate\n    float scale_lambda; // regularization\n\nprivate:\n\tvoid Reset() {\n\t\tinterp_factor = 0;\n\t\tsigma = 0;\n\t\tlambda = 0;\n\t\tcell_size = 0;\n\t\tcell_sizeQ = 0;\n\t\tpadding = 0;\n\t\toutput_sigma_factor = 0;\n\t\ttemplate_size = 0;\n\n\t\tbase_width = 0;\n\t\tbase_height = 0;\n\t\tscale_max_area = 0;\n\t\tscale_padding = 0;\n\t\tscale_step = 0;\n\t\tscale_sigma_factor = 0;\n\n\t\tn_scales = 0;\n\t\tn_interp_scales = 0;\n\n\t\tnum_compressed_dim = 0;\n\n\t\tscale_lr = 0;\n\n\n\t\tscale_model_width = 0;\n\t\tscale_model_height = 0;\n\t\tcurrentScaleFactor = 0;\n\t\tmin_scale_factor = 0;\n\t\tmax_scale_factor = 0;\n\t\tscale_lambda = 0;\n\t}\nprotected:\n    // Detect object in the current frame.\n    cv::Point2f detect(cv::Mat x, float &peak_value);\n\n    // train tracker with a single image\n    void train(cv::Mat x, float train_interp_factor);\n\n    // Evaluates a Gaussian kernel with bandwidth SIGMA for all relative shifts between input images X and Y, which must both be MxN. They must    also be periodic (ie., pre-processed with a cosine window).\n    cv::Mat gaussianCorrelation(cv::Mat x1, cv::Mat x2);\n\n    // Obtain sub-window from image, with replication-padding and extract features\n    cv::Mat getFeatures(const cv::Mat & image, bool inithann, float scale_adjust = 1.0f);\n\n    // Initialize Hanning window. Function called only in the first frame.\n    void createHanningMats();\n\n\t// Create Gaussian Peak. Function called only in the first frame.\n\tcv::Mat createGaussianPeak(int sizey, int sizex);\n\n    // Calculate sub-pixel peak for one dimension\n    float subPixelPeak(float left, float center, float right);\n\n    // Compute the FFT Guassian Peak for scaling\n    cv::Mat computeYsf();\n\n    // Compute the hanning window for scaling\n    cv::Mat createHanningMatsForScale();\n\n    // Initialization for scales\n    void dsstInit(const cv::Rect &roi, cv::Mat image);\n\n    // Compute the F^l in the paper\n    cv::Mat get_scale_sample(const cv::Mat & image);\n\n    // Update the ROI size after training\n    void update_roi();\n\n    // Train method for scaling\n    void train_scale(cv::Mat image, bool ini = false);\n\n\tcv::Mat resizeDFT(const cv::Mat &A, int real_scales);\n\n    // Detect the new scaling rate\n    cv::Point2i detect_scale(cv::Mat image);\n\n\tcv::Mat features_projection(const cv::Mat &src);\n\n    \n\n    cv::Mat _labCentroids;\n\t\n\tcv::Mat _alphaf;\n\tcv::Mat _prob;\n\tcv::Mat _tmpl;\n\n\tcv::Mat _proj_tmpl;\n\n\tcv::Mat _num;\n\tcv::Mat _den;\n\n    cv::Mat sf_den;\n    cv::Mat sf_num;\n\n\tcv::Mat proj_matrix;\n\nprivate:\n    int size_patch[3];\n    cv::Mat hann;\n    cv::Size _tmpl_sz;\n    float _scale;\n    int _gaussian_size;\n    bool _hogfeatures;\n    bool _labfeatures;\n\n    cv::Mat s_hann;\n    cv::Mat ysf;\n    bool success_;\n\n};\n#endif\n"
  },
  {
    "path": "fdsst/ffttools.hpp",
    "content": "/*\nAuthor: Christian Bailer\nContact address: Christian.Bailer@dfki.de\nDepartment Augmented Vision DFKI\n\n                          License Agreement\n               For Open Source Computer Vision Library\n                       (3-clause BSD License)\n\nRedistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:\n\n  * Redistributions of source code must retain the above copyright notice,\n    this list of conditions and the following disclaimer.\n\n  * Redistributions in binary form must reproduce the above copyright notice,\n    this list of conditions and the following disclaimer in the documentation\n    and/or other materials provided with the distribution.\n\n  * Neither the names of the copyright holders nor the names of the contributors\n    may be used to endorse or promote products derived from this software\n    without specific prior written permission.\n\nThis software is provided by the copyright holders and contributors \"as is\" and\nany express or implied warranties, including, but not limited to, the implied\nwarranties of merchantability and fitness for a particular purpose are disclaimed.\nIn no event shall copyright holders or contributors be liable for any direct,\nindirect, incidental, special, exemplary, or consequential damages\n(including, but not limited to, procurement of substitute goods or services;\nloss of use, data, or profits; or business interruption) however caused\nand on any theory of liability, whether in contract, strict liability,\nor tort (including negligence or otherwise) arising in any way out of\nthe use of this software, even if advised of the possibility of such damage.\n*/\n\n#pragma once\n\n//#include <cv.h>\n\n#ifndef _OPENCV_FFTTOOLS_HPP_\n#define _OPENCV_FFTTOOLS_HPP_\n#endif\n//NOTE: FFTW support is still shaky, disabled for now.\n/*#ifdef USE_FFTW\n#include <fftw3.h>\n#endif*/\n\nnamespace FFTTools\n{\n\n\n\n\tcv::Mat fftd(cv::Mat img, bool backwards = false, bool byRow = false)\n{\n\n    if (img.channels() == 1)\n    {\n        cv::Mat planes[] = {cv::Mat_<float> (img), cv::Mat_<float>::zeros(img.size())};\n        //cv::Mat planes[] = {cv::Mat_<double> (img), cv::Mat_<double>::zeros(img.size())};\n        cv::merge(planes, 2, img);\n    }\n    if(byRow)\n      cv::dft(img, img, (cv::DFT_ROWS | cv::DFT_COMPLEX_OUTPUT));\n    else\n      cv::dft(img, img, backwards ? (cv::DFT_INVERSE | cv::DFT_SCALE) : 0 );\n\n    return img;\n\n\n\n}\n\ncv::Mat real(cv::Mat img)\n{\n    std::vector<cv::Mat> planes;\n    cv::split(img, planes);\n    return planes[0];\n}\n\ncv::Mat imag(cv::Mat img)\n{\n    std::vector<cv::Mat> planes;\n    cv::split(img, planes);\n    return planes[1];\n}\n\ncv::Mat magnitude(cv::Mat img)\n{\n    cv::Mat res;\n    std::vector<cv::Mat> planes;\n    cv::split(img, planes); // planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))\n    if (planes.size() == 1) res = cv::abs(img);\n    else if (planes.size() == 2) cv::magnitude(planes[0], planes[1], res); // planes[0] = magnitude\n    else assert(0);\n    return res;\n}\n\ncv::Mat complexMultiplication(cv::Mat a, cv::Mat b, bool conj = false)\n{\n    std::vector<cv::Mat> pa;\n    std::vector<cv::Mat> pb;\n    cv::split(a, pa);\n    cv::split(b, pb);\n\n\tif (conj)\n\t\tpb[1] *= -1.0;\n\n    std::vector<cv::Mat> pres;\n    pres.push_back(pa[0].mul(pb[0]) - pa[1].mul(pb[1]));\n    pres.push_back(pa[0].mul(pb[1]) + pa[1].mul(pb[0]));\n\n    cv::Mat res;\n    cv::merge(pres, res);\n\n    return res;\n}\n\ncv::Mat complexDivisionReal(cv::Mat a, cv::Mat b)\n{\n    std::vector<cv::Mat> pa;\n    cv::split(a, pa);\n\n    std::vector<cv::Mat> pres;\n\n    cv::Mat divisor = 1. / b;\n\n    pres.push_back(pa[0].mul(divisor));\n    pres.push_back(pa[1].mul(divisor));\n\n    cv::Mat res;\n    cv::merge(pres, res);\n    return res;\n}\n\ncv::Mat complexDivision(cv::Mat a, cv::Mat b)\n{\n    std::vector<cv::Mat> pa;\n    std::vector<cv::Mat> pb;\n    cv::split(a, pa);\n    cv::split(b, pb);\n\n    cv::Mat divisor = 1. / (pb[0].mul(pb[0]) + pb[1].mul(pb[1]));\n\n    std::vector<cv::Mat> pres;\n\n    pres.push_back((pa[0].mul(pb[0]) + pa[1].mul(pb[1])).mul(divisor));\n    pres.push_back((pa[1].mul(pb[0]) + pa[0].mul(pb[1])).mul(divisor));\n\n    cv::Mat res;\n    cv::merge(pres, res);\n    return res;\n}\n\nvoid rearrange(cv::Mat &img)\n{\n    // img = img(cv::Rect(0, 0, img.cols & -2, img.rows & -2));\n    int cx = img.cols / 2;\n    int cy = img.rows / 2;\n\n    cv::Mat q0(img, cv::Rect(0, 0, cx, cy)); // Top-Left - Create a ROI per quadrant\n    cv::Mat q1(img, cv::Rect(cx, 0, cx, cy)); // Top-Right\n    cv::Mat q2(img, cv::Rect(0, cy, cx, cy)); // Bottom-Left\n    cv::Mat q3(img, cv::Rect(cx, cy, cx, cy)); // Bottom-Right\n\n    cv::Mat tmp; // swap quadrants (Top-Left with Bottom-Right)\n    q0.copyTo(tmp);\n    q3.copyTo(q0);\n    tmp.copyTo(q3);\n    q1.copyTo(tmp); // swap quadrant (Top-Right with Bottom-Left)\n    q2.copyTo(q1);\n    tmp.copyTo(q2);\n}\n/*\ntemplate < typename type>\ncv::Mat fouriertransFull(const cv::Mat & in)\n{\n    return fftd(in);\n\n    cv::Mat planes[] = {cv::Mat_<type > (in), cv::Mat_<type>::zeros(in.size())};\n    cv::Mat t;\n    assert(planes[0].depth() == planes[1].depth());\n    assert(planes[0].size == planes[1].size);\n    cv::merge(planes, 2, t);\n    cv::dft(t, t);\n\n    //cv::normalize(a, a, 0, 1, CV_MINMAX);\n    //cv::normalize(t, t, 0, 1, CV_MINMAX);\n\n    // cv::imshow(\"a\",real(a));\n    //  cv::imshow(\"b\",real(t));\n    // cv::waitKey(0);\n\n    return t;\n}*/\n\nvoid normalizedLogTransform(cv::Mat &img)\n{\n    img = cv::abs(img);\n    img += cv::Scalar::all(1);\n    cv::log(img, img);\n    // cv::normalize(img, img, 0, 1, CV_MINMAX);\n}\n\ntypedef std::vector<cv::Mat> ComplexMats;\n\nComplexMats MultiChannelsDFT(const cv::Mat &img, int flags = 0)\n{\n\tstd::vector<cv::Mat> chls;\n\tstd::vector<cv::Mat> out;\n\tcv::split(img, chls);\n\tout.resize(chls.size());\n\tfor (int i = 0; i < chls.size(); i++)\n\t{\n\t\tcv::dft(chls[i], out[i], cv::DFT_COMPLEX_OUTPUT);\n\t\t//out[i] = (out[i]);\n\t}\n\t// cv::Mat out_m;\n\t// cv::merge(out, out_m);\n\treturn out;\n}\n\nComplexMats ComplexMatsMultiMat(const ComplexMats &A, cv::Mat b)\n\t{\n\t\t\n\t\tComplexMats out;\n\t\tout.resize(A.size());\n\t\tfor (int i = 0; i < A.size(); i++)\n\t\t{\n\t\t\tout[i] = complexMultiplication(b, A[i]);\n\t\t}\n\t\treturn out;\n\t}\n\n\nComplexMats ComplexMatsMultiComplexMats(const ComplexMats &A, const ComplexMats &B)\n{\n\n\tComplexMats out;\n\tassert(A.size() == B.size());\n\tout.resize(A.size());\n\tfor (int i = 0; i < A.size(); i++)\n\t{\n\t\tout[i] = complexMultiplication(A[i], B[i]);\n\t}\n\treturn out;\n}\n\n     ComplexMats MCComplexConjMultiplication(const ComplexMats &A)\n\t{\n\n\t\tComplexMats out;\n\t\tout.resize(A.size());\n\t\tfor (int i = 0; i < A.size(); i++)\n\t\t{\n\t\t\tout[i] = (complexMultiplication(A[i], A[i], true));\n\t\t}\n\t\t//cv::Mat out_m;\n\t\t//cv::merge(out, out_m);\n\t\treturn out;\n\t}\n\n\tcv::Mat MCMulti(cv::Mat a, cv::Mat b)\n\t{\n\t\tstd::vector<cv::Mat> pa;\n\t\tcv::split(a, pa);\n\n\t\tstd::vector<cv::Mat> pres;\n\n\t\tpres.resize(pa.size());\n\n\t\tfor (int i = 0; i < pa.size(); i++)\n\t\t\tpres[i] = pa[i].mul(b);\n\t\tcv::Mat res;\n\t\tcv::merge(pres, res);\n\n\t\treturn res;\n\t}\n\n\n\tcv::Mat MCSum(const ComplexMats &a)\n\t{\n\t\t//std::vector<cv::Mat> pa;\n\t\t//cv::split(a, pa);\n\t\tassert(a.size() != 0);\n\t\tcv::Mat out;\n\t\ta[0].copyTo(out);\n\t\tfor (int i = 1; i < a.size(); i++)\n\t\t\tout = out + a[i];\n\n\t\treturn out;\n\t}\n\n\tcv::Mat MCSum(const cv::Mat &a)\n\t{\n\t\tstd::vector<cv::Mat> pa;\n\t\tcv::split(a, pa);\n\t\tassert(pa.size() != 0);\n\t\tcv::Mat out;\n\t\tpa[0].copyTo(out);\n\t\tfor (int i = 1; i < pa.size(); i++)\n\t\t\tout = out + pa[i];\n\n\t\treturn out;\n\t}\n\n}\n"
  },
  {
    "path": "fdsst/fhog.cpp",
    "content": "#include <cstring>\n#include <iostream>\n\nusing namespace std;\n\n#include \"fhog.h\"\n#undef MIN\n#ifdef WIN32\n//{\n#ifndef _CRTDBG_MAP_ALLOC\n#define _CRTDBG_MAP_ALLOC\n#endif\n#include <stdlib.h>  \n#include <crtdbg.h> \n#ifdef _DEBUG  \n\t#ifndef new\n\t#define new   new(_NORMAL_BLOCK, __FILE__, __LINE__)  \n\t#endif\n#endif\n//}\n#endif\n#define GLOG_NO_ABBREVIATED_SEVERITIES\n#include <glog/logging.h>\n// platform independent aligned memory allocation (see also alFree)\nvoid* alMalloc( size_t size, int alignment ) {\n  const size_t pSize = sizeof(void*), a = alignment-1;\n  void *raw = wrMalloc(size + a + pSize);\n  void *aligned = (void*) (((size_t) raw + pSize + a) & ~a);\n  *(void**) ((size_t) aligned-pSize) = raw;\n  return aligned;\n}\n\n// platform independent alignned memory de-allocation (see also alMalloc)\nvoid alFree(void* aligned) {\n  void* raw = *(void**)((char*)aligned-sizeof(void*));\n  wrFree(raw);\n}\n\n/*******************************************************************************\n* Piotr's Computer Vision Matlab Toolbox      Version 3.30\n* Copyright 2014 Piotr Dollar & Ron Appel.  [pdollar-at-gmail.com]\n* Licensed under the Simplified BSD License [see external/bsd.txt]\n*******************************************************************************/\n// #include \"wrappers.hpp\"\n\n#define PI 3.14159265f\n\n// compute x and y gradients for just one column (uses sse)\nvoid grad1( float *I, float *Gx, float *Gy, int h, int w, int x ) {\n  int y, y1; float *Ip, *In, r; __m128 *_Ip, *_In, *_G, _r;\n  // compute column of Gx\n  Ip=I-h; In=I+h; r=.5f;\n  if(x==0) { r=1; Ip+=h; } else if(x==w-1) { r=1; In-=h; }\n  if( h<4 || h%4>0 || (size_t(I)&15) || (size_t(Gx)&15) ) {\n    for( y=0; y<h; y++ ) *Gx++=(*In++-*Ip++)*r;\n  } else {\n    _G=(__m128*) Gx; _Ip=(__m128*) Ip; _In=(__m128*) In; _r = sse::SET(r);\n    for(y=0; y<h; y+=4) *_G++=sse::MUL(sse::SUB(*_In++,*_Ip++),_r);\n  }\n  // compute column of Gy\n  #define GRADY(r) *Gy++=(*In++-*Ip++)*r;\n  Ip=I; In=Ip+1;\n  // GRADY(1); Ip--; for(y=1; y<h-1; y++) GRADY(.5f); In--; GRADY(1);\n  y1=((~((size_t) Gy) + 1) & 15)/4; if(y1==0) y1=4; if(y1>h-1) y1=h-1;\n  GRADY(1); Ip--; for(y=1; y<y1; y++) GRADY(.5f);\n  _r = sse::SET(.5f); _G=(__m128*) Gy;\n  for(; y+4<h-1; y+=4, Ip+=4, In+=4, Gy+=4)\n    *_G++=sse::MUL(sse::SUB(sse::LDu(*In),sse::LDu(*Ip)),_r);\n  for(; y<h-1; y++) GRADY(.5f); In--; GRADY(1);\n  #undef GRADY\n}\n\n// compute x and y gradients at each location (uses sse)\nvoid grad2( float *I, float *Gx, float *Gy, int h, int w, int d ) {\n  int o, x, c, a=w*h; for(c=0; c<d; c++) for(x=0; x<w; x++) {\n    o=c*a+x*h; grad1( I+o, Gx+o, Gy+o, h, w, x );\n  }\n}\n\nstatic bool _hoglog = false;\n\nvoid hoglog(){\n\t_hoglog = true;\n}\n// build lookup table a[] s.t. a[x*n]~=acos(x) for x in [-1,1]\nfloat* acosTable() {\n  const int n=10000, b=10; \n  int i;\n  static float a[n*2+b*2]; \n  static bool init=false;\n  float *a1=a+n+b; \n  if( init ){\n\t return a1;\n  }\n  for( i=-n-b; i<-n; i++ )   a1[i]=PI;\n  for( i=-n; i<n; i++ )      a1[i]=float(acos(i/float(n)));\n  for( i=n; i<n+b; i++ )     a1[i]=0;\n  for( i=-n-b; i<n/10; i++ ) if( a1[i] > PI-1e-6f ) a1[i]=PI-1e-6f;\n  init=true; return a1;\n}\n\n// compute gradient magnitude and orientation at each location (uses sse)\nvoid gradMag( float *I, float *M, float *O, int h, int w, int d, bool full ) {\n  int x, y, y1, c, h4, s; float *Gx, *Gy, *M2; __m128 *_Gx, *_Gy, *_M2, _m;\n  float *acost = acosTable(), acMult=10000.0f;\n  // allocate memory for storing one column of output (padded so h4%4==0)\n  h4=(h%4==0) ? h : h-(h%4)+4; s=d*h4*sizeof(float);\n  //LOG(INFO) << \"gradMag----d:\" << d << \", h4:\" << h4 << \", s:\" << s;\n  M2=(float*) alMalloc(s,16); _M2=(__m128*) M2;\n  Gx=(float*) alMalloc(s,16); _Gx=(__m128*) Gx;\n  Gy=(float*) alMalloc(s,16); _Gy=(__m128*) Gy;\n  // compute gradient magnitude and orientation for each column\n  for( x=0; x<w; x++ ) {\n    // compute gradients (Gx, Gy) with maximum squared magnitude (M2)\n    for(c=0; c<d; c++) {\n      grad1( I+x*h+c*w*h, Gx+c*h4, Gy+c*h4, h, w, x );\n      for( y=0; y<h4/4; y++ ) {\n        y1=h4/4*c+y;\n        _M2[y1]=sse::ADD(sse::MUL(_Gx[y1],_Gx[y1]),sse::MUL(_Gy[y1],_Gy[y1]));\n        if( c==0 ) continue; _m = sse::CMPGT( _M2[y1], _M2[y] );\n        _M2[y] = sse::OR( sse::AND(_m,_M2[y1]), sse::ANDNOT(_m,_M2[y]) );\n        _Gx[y] = sse::OR( sse::AND(_m,_Gx[y1]), sse::ANDNOT(_m,_Gx[y]) );\n        _Gy[y] = sse::OR( sse::AND(_m,_Gy[y1]), sse::ANDNOT(_m,_Gy[y]) );\n      }\n    }\n    // compute gradient mangitude (M) and normalize Gx\n    for( y=0; y<h4/4; y++ ) {\n      _m = sse::MIN( sse::RCPSQRT(_M2[y]), sse::SET(1e10f) );\n      _M2[y] = sse::RCP(_m);\n      if(O) _Gx[y] = sse::MUL( sse::MUL(_Gx[y],_m), sse::SET(acMult) );\n      if(O) _Gx[y] = sse::XOR( _Gx[y], sse::AND(_Gy[y], sse::SET(-0.f)) );\n    };\n    memcpy( M+x*h, M2, h*sizeof(float) );\n    // compute and store gradient orientation (O) via table lookup\n    if( O!=0 ){\n\t for( y=0; y<h; y++ ){\n\t\t if(_hoglog){\n\t\t \t//priaaantf(\"gradMag-w:%d, h:%d---x*h+y:%d, (int)Gx[y]:%d\\n\", w, h, x*h+y, (int)Gx[y]);\n\t\t }\n\t\t O[x*h+y] = acost[(int)Gx[y]];\n\t }\n    }\n    if( O!=0 && full ) {\n      y1=((~size_t(O+x*h)+1)&15)/4; y=0;\n      for( ; y<y1; y++ ) O[y+x*h]+=(Gy[y]<0)*PI;\n      for( ; y<h-4; y+=4 ) sse::STRu( O[y+x*h],\n        sse::ADD( sse::LDu(O[y+x*h]), sse::AND(sse::CMPLT(sse::LDu(Gy[y]),sse::SET(0.f)),sse::SET(PI)) ) );\n      for( ; y<h; y++ ) O[y+x*h]+=(Gy[y]<0)*PI;\n    }\n  }\n  alFree((void *)Gx); \n  alFree((void *)Gy);\n  alFree((void *)M2);\n}\n\n// normalize gradient magnitude at each location (uses sse)\nvoid gradMagNorm( float *M, float *S, int h, int w, float norm ) {\n  __m128 *_M, *_S, _norm; int i=0, n=h*w, n4=n/4;\n  _S = (__m128*) S; _M = (__m128*) M; _norm = sse::SET(norm);\n  bool sse = !(size_t(M)&15) && !(size_t(S)&15);\n  if(sse) for(; i<n4; i++) { *_M=sse::MUL(*_M,sse::RCP(sse::ADD(*_S++,_norm))); _M++; }\n  if(sse) i*=4; for(; i<n; i++) M[i] /= (S[i] + norm);\n}\n\n// helper for gradHist, quantize O and M into O0, O1 and M0, M1 (uses sse)\nvoid gradQuantize( float *O, float *M, int *O0, int *O1, float *M0, float *M1,\n  int nb, int n, float norm, int nOrients, bool full, bool interpolate )\n{\n  // assumes all *OUTPUT* matrices are 4-byte aligned\n  int i, o0, o1; float o, od, m;\n  __m128i _o0, _o1, *_O0, *_O1; __m128 _o, _od, _m, *_M0, *_M1;\n  // define useful constants\n  const float oMult=(float)nOrients/(full?2*PI:PI); const int oMax=nOrients*nb;\n  const __m128 _norm=sse::SET(norm), _oMult=sse::SET(oMult), _nbf=sse::SET((float)nb);\n  const __m128i _oMax=sse::SET(oMax), _nb=sse::SET(nb);\n  // perform the majority of the work with sse\n  _O0=(__m128i*) O0; _O1=(__m128i*) O1; _M0=(__m128*) M0; _M1=(__m128*) M1;\n  if( interpolate ) for( i=0; i<=n-4; i+=4 ) {\n    _o=sse::MUL(sse::LDu(O[i]),_oMult); _o0=sse::CVT(_o); _od=sse::SUB(_o,sse::CVT(_o0));\n    _o0=sse::CVT(sse::MUL(sse::CVT(_o0),_nbf)); _o0=sse::AND(sse::CMPGT(_oMax,_o0),_o0); *_O0++=_o0;\n    _o1=sse::ADD(_o0,_nb); _o1=sse::AND(sse::CMPGT(_oMax,_o1),_o1); *_O1++=_o1;\n    _m=sse::MUL(sse::LDu(M[i]),_norm); *_M1=sse::MUL(_od,_m); *_M0++=sse::SUB(_m,*_M1); _M1++;\n  } else for( i=0; i<=n-4; i+=4 ) {\n    _o=sse::MUL(sse::LDu(O[i]),_oMult); _o0=sse::CVT(sse::ADD(_o,sse::SET(.5f)));\n    _o0=sse::CVT(sse::MUL(sse::CVT(_o0),_nbf)); _o0=sse::AND(sse::CMPGT(_oMax,_o0),_o0); *_O0++=_o0;\n    *_M0++=sse::MUL(sse::LDu(M[i]),_norm); *_M1++=sse::SET(0.f); *_O1++=sse::SET(0);\n  }\n  // compute trailing locations without sse\n  if( interpolate ) for(; i<n; i++ ) {\n    o=O[i]*oMult; o0=(int) o; od=o-o0;\n    o0*=nb; if(o0>=oMax) o0=0; O0[i]=o0;\n    o1=o0+nb; if(o1==oMax) o1=0; O1[i]=o1;\n    m=M[i]*norm; M1[i]=od*m; M0[i]=m-M1[i];\n  } else for(; i<n; i++ ) {\n    o=O[i]*oMult; o0=(int) (o+.5f);\n    o0*=nb; if(o0>=oMax) o0=0; O0[i]=o0;\n    M0[i]=M[i]*norm; M1[i]=0; O1[i]=0;\n  }\n}\n\n// compute nOrients gradient histograms per bin x bin block of pixels\nvoid gradHist( float *M, float *O, float *H, int h, int w,\n  int bin, int nOrients, int softBin, bool full )\n{\n  const int hb=h/bin, wb=w/bin, h0=hb*bin, w0=wb*bin, nb=wb*hb;\n  const float s=(float)bin, sInv=1/s, sInv2=1/s/s;\n  float *H0, *H1, *M0, *M1; int x, y; int *O0, *O1; float xb, init;\n  O0=(int*)alMalloc(h*sizeof(int),16); M0=(float*) alMalloc(h*sizeof(float),16);\n  O1=(int*)alMalloc(h*sizeof(int),16); M1=(float*) alMalloc(h*sizeof(float),16);\n  // main loop\n  for( x=0; x<w0; x++ ) {\n    // compute target orientation bins for entire column - very fast\n    gradQuantize(O+x*h,M+x*h,O0,O1,M0,M1,nb,h0,sInv2,nOrients,full,softBin>=0);\n\n    if( softBin<0 && softBin%2==0 ) {\n      // no interpolation w.r.t. either orienation or spatial bin\n      H1=H+(x/bin)*hb;\n      #define GH H1[O0[y]]+=M0[y]; y++;\n      if( bin==1 )      for(y=0; y<h0;) { GH; H1++; }\n      else if( bin==2 ) for(y=0; y<h0;) { GH; GH; H1++; }\n      else if( bin==3 ) for(y=0; y<h0;) { GH; GH; GH; H1++; }\n      else if( bin==4 ) for(y=0; y<h0;) { GH; GH; GH; GH; H1++; }\n      else for( y=0; y<h0;) { for( int y1=0; y1<bin; y1++ ) { GH; } H1++; }\n      #undef GH\n\n    } else if( softBin%2==0 || bin==1 ) {\n      // interpolate w.r.t. orientation only, not spatial bin\n      H1=H+(x/bin)*hb;\n      #define GH H1[O0[y]]+=M0[y]; H1[O1[y]]+=M1[y]; y++;\n      if( bin==1 )      for(y=0; y<h0;) { GH; H1++; }\n      else if( bin==2 ) for(y=0; y<h0;) { GH; GH; H1++; }\n      else if( bin==3 ) for(y=0; y<h0;) { GH; GH; GH; H1++; }\n      else if( bin==4 ) for(y=0; y<h0;) { GH; GH; GH; GH; H1++; }\n      else for( y=0; y<h0;) { for( int y1=0; y1<bin; y1++ ) { GH; } H1++; }\n      #undef GH\n\n    } else {\n      // interpolate using trilinear interpolation\n      float ms[4], xyd, yb, xd, yd; __m128 _m, _m0, _m1;\n      bool hasLf, hasRt; int xb0, yb0;\n      if( x==0 ) { init=(0+.5f)*sInv-0.5f; xb=init; }\n      hasLf = xb>=0; xb0 = hasLf?(int)xb:-1; hasRt = xb0 < wb-1;\n      xd=xb-xb0; xb+=sInv; yb=init; y=0;\n      // macros for code conciseness\n      #define GHinit yd=yb-yb0; yb+=sInv; H0=H+xb0*hb+yb0; xyd=xd*yd; \\\n        ms[0]=1-xd-yd+xyd; ms[1]=yd-xyd; ms[2]=xd-xyd; ms[3]=xyd;\n      #define GH(H,ma,mb) H1=H; sse::STRu(*H1,sse::ADD(sse::LDu(*H1),sse::MUL(ma,mb)));\n      // leading rows, no top bin\n      for( ; y<bin/2; y++ ) {\n        yb0=-1; GHinit;\n        if(hasLf) { H0[O0[y]+1]+=ms[1]*M0[y]; H0[O1[y]+1]+=ms[1]*M1[y]; }\n        if(hasRt) { H0[O0[y]+hb+1]+=ms[3]*M0[y]; H0[O1[y]+hb+1]+=ms[3]*M1[y]; }\n      }\n      // main rows, has top and bottom bins, use SSE for minor speedup\n      if( softBin<0 ) for( ; ; y++ ) {\n        yb0 = (int) yb; if(yb0>=hb-1) break; GHinit; _m0=sse::SET(M0[y]);\n        if(hasLf) { _m=sse::SET(0,0,ms[1],ms[0]); GH(H0+O0[y],_m,_m0); }\n        if(hasRt) { _m=sse::SET(0,0,ms[3],ms[2]); GH(H0+O0[y]+hb,_m,_m0); }\n      } else for( ; ; y++ ) {\n        yb0 = (int) yb; if(yb0>=hb-1) break; GHinit;\n        _m0=sse::SET(M0[y]); _m1=sse::SET(M1[y]);\n        if(hasLf) { _m=sse::SET(0,0,ms[1],ms[0]);\n          GH(H0+O0[y],_m,_m0); GH(H0+O1[y],_m,_m1); }\n        if(hasRt) { _m=sse::SET(0,0,ms[3],ms[2]);\n          GH(H0+O0[y]+hb,_m,_m0); GH(H0+O1[y]+hb,_m,_m1); }\n      }\n      // final rows, no bottom bin\n      for( ; y<h0; y++ ) {\n        yb0 = (int) yb; GHinit;\n        if(hasLf) { H0[O0[y]]+=ms[0]*M0[y]; H0[O1[y]]+=ms[0]*M1[y]; }\n        if(hasRt) { H0[O0[y]+hb]+=ms[2]*M0[y]; H0[O1[y]+hb]+=ms[2]*M1[y]; }\n      }\n      #undef GHinit\n      #undef GH\n    }\n  }\n  alFree((void *)O0);\n  alFree((void *)O1);\n  alFree((void *)M0);\n  alFree((void *)M1);\n  // normalize boundary bins which only get 7/8 of weight of interior bins\n  if( softBin%2!=0 ) for( int o=0; o<nOrients; o++ ) {\n    x=0; for( y=0; y<hb; y++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n    y=0; for( x=0; x<wb; x++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n    x=wb-1; for( y=0; y<hb; y++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n    y=hb-1; for( x=0; x<wb; x++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n  }\n}\n\n/******************************************************************************/\n\n// HOG helper: compute 2x2 block normalization values (padded by 1 pixel)\nfloat* hogNormMatrix( float *H, int nOrients, int hb, int wb, int bin ) {\n  float *N, *N1, *n; int o, x, y, dx, dy, hb1=hb+1, wb1=wb+1;\n  float eps = 1e-4f/4/bin/bin/bin/bin; // precise backward equality\n  N = (float*) wrCalloc(hb1*wb1,sizeof(float)); N1=N+hb1+1;\n  for( o=0; o<nOrients; o++ ) for( x=0; x<wb; x++ ) for( y=0; y<hb; y++ )\n    N1[x*hb1+y] += H[o*wb*hb+x*hb+y]*H[o*wb*hb+x*hb+y];\n  for( x=0; x<wb-1; x++ ) for( y=0; y<hb-1; y++ ) {\n    n=N1+x*hb1+y; *n=1/float(sqrt(n[0]+n[1]+n[hb1]+n[hb1+1]+eps)); }\n  x=0;     dx= 1; dy= 1; y=0;                  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=0;     dx= 1; dy= 0; for(y=0; y<hb1; y++)  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=0;     dx= 1; dy=-1; y=hb1-1;              N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=wb1-1; dx=-1; dy= 1; y=0;                  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=wb1-1; dx=-1; dy= 0; for( y=0; y<hb1; y++) N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=wb1-1; dx=-1; dy=-1; y=hb1-1;              N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  y=0;     dx= 0; dy= 1; for(x=0; x<wb1; x++)  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  y=hb1-1; dx= 0; dy=-1; for(x=0; x<wb1; x++)  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  return N;\n}\n\n// HOG helper: compute HOG or FHOG channels\nvoid hogChannels( float *H, const float *R, const float *N,\n  int hb, int wb, int nOrients, float clip, int type )\n{\n  #define GETT(blk) t=R1[y]*N1[y-(blk)]; if(t>clip) t=clip; c++;\n  const float r=.2357f; int o, x, y, c; float t;\n  const int nb=wb*hb, nbo=nOrients*nb, hb1=hb+1;\n  for( o=0; o<nOrients; o++ ) for( x=0; x<wb; x++ ) {\n    const float *R1=R+o*nb+x*hb, *N1=N+x*hb1+hb1+1;\n    float *H1 = (type<=1) ? (H+o*nb+x*hb) : (H+x*hb);\n    if( type==0) for( y=0; y<hb; y++ ) {\n      // store each orientation and normalization (nOrients*4 channels)\n      c=-1; GETT(0); H1[c*nbo+y]=t; GETT(1); H1[c*nbo+y]=t;\n      GETT(hb1); H1[c*nbo+y]=t; GETT(hb1+1); H1[c*nbo+y]=t;\n    } else if( type==1 ) for( y=0; y<hb; y++ ) {\n      // sum across all normalizations (nOrients channels)\n      c=-1; GETT(0); H1[y]+=t*.5f; GETT(1); H1[y]+=t*.5f;\n      GETT(hb1); H1[y]+=t*.5f; GETT(hb1+1); H1[y]+=t*.5f;\n    } else if( type==2 ) for( y=0; y<hb; y++ ) {\n      // sum across all orientations (4 channels)\n      c=-1; GETT(0); H1[c*nb+y]+=t*r; GETT(1); H1[c*nb+y]+=t*r;\n      GETT(hb1); H1[c*nb+y]+=t*r; GETT(hb1+1); H1[c*nb+y]+=t*r;\n    }\n  }\n  #undef GETT\n}\n\n// compute HOG features\nvoid hog( float *M, float *O, float *H, int h, int w, int binSize,\n  int nOrients, int softBin, bool full, float clip )\n{\n  float *N, *R; const int hb=h/binSize, wb=w/binSize, nb=hb*wb;\n  // compute unnormalized gradient histograms\n  R = (float*) wrCalloc(wb*hb*nOrients,sizeof(float));\n  gradHist( M, O, R, h, w, binSize, nOrients, softBin, full );\n  // compute block normalization values\n  N = hogNormMatrix( R, nOrients, hb, wb, binSize );\n  // perform four normalizations per spatial block\n  hogChannels( H, R, N, hb, wb, nOrients, clip, 0 );\n  wrFree((void*)N); \n  wrFree((void*)R);\n}\n\n// compute FHOG features\nbool fhog( float *M, float *O, float *H, int h, int w, int binSize,\n  int nOrients, int softBin, float clip )\n{\n  const int hb=h/binSize, wb=w/binSize, nb=hb*wb, nbo=nb*nOrients;\n  float *N, *R1, *R2; int o, x;\n  // compute unnormalized constrast sensitive histograms\n  int sz = wb*nb*nOrients;\n  if(sz <= 0){\n     return false;\n  }\n  R1 = (float*) wrCalloc(wb*hb*nOrients*2,sizeof(float));\n  gradHist( M, O, R1, h, w, binSize, nOrients*2, softBin, true );\n  // compute unnormalized contrast insensitive histograms\n  R2 = (float*) wrCalloc(wb*hb*nOrients,sizeof(float));\n  for( o=0; o<nOrients; o++ ) for( x=0; x<nb; x++ )\n    R2[o*nb+x] = R1[o*nb+x]+R1[(o+nOrients)*nb+x];\n  // compute block normalization values\n  N = hogNormMatrix( R2, nOrients, hb, wb, binSize );\n  // normalized histograms and texture channels\n  hogChannels( H+nbo*0, R1, N, hb, wb, nOrients*2, clip, 1 );\n  hogChannels( H+nbo*2, R2, N, hb, wb, nOrients*1, clip, 1 );\n  hogChannels( H+nbo*3, R1, N, hb, wb, nOrients*2, clip, 2 );\n  wrFree((void*)N); \n  wrFree((void*)R1);\n  wrFree((void*)R2);\n  return true;\n}\n\n/******************************************************************************/\n#ifdef MATLAB_MEX_FILE\n// Create [hxwxd] mxArray array, initialize to 0 if c=true\nmxArray* mxCreateMatrix3( int h, int w, int d, mxClassID id, bool c, void **I ){\n  const int dims[3]={h,w,d}, n=h*w*d; int b; mxArray* M;\n  if( id==mxINT32_CLASS ) b=sizeof(int);\n  else if( id==mxDOUBLE_CLASS ) b=sizeof(double);\n  else if( id==mxSINGLE_CLASS ) b=sizeof(float);\n  else mexErrMsgTxt(\"Unknown mxClassID.\");\n  *I = c ? mxCalloc(n,b) : mxMalloc(n*b);\n  M = mxCreateNumericMatrix(0,0,id,mxREAL);\n  mxSetData(M,*I); mxSetDimensions(M,dims,3); return M;\n}\n\n// Check inputs and outputs to mex, retrieve first input I\nvoid checkArgs( int nl, mxArray *pl[], int nr, const mxArray *pr[], int nl0,\n  int nl1, int nr0, int nr1, int *h, int *w, int *d, mxClassID id, void **I )\n{\n  const int *dims; int nDims;\n  if( nl<nl0 || nl>nl1 ) mexErrMsgTxt(\"Incorrect number of outputs.\");\n  if( nr<nr0 || nr>nr1 ) mexErrMsgTxt(\"Incorrect number of inputs.\");\n  nDims = mxGetNumberOfDimensions(pr[0]); dims = mxGetDimensions(pr[0]);\n  *h=dims[0]; *w=dims[1]; *d=(nDims==2) ? 1 : dims[2]; *I = mxGetPr(pr[0]);\n  if( nDims!=2 && nDims!=3 ) mexErrMsgTxt(\"I must be a 2D or 3D array.\");\n  if( mxGetClassID(pr[0])!=id ) mexErrMsgTxt(\"I has incorrect type.\");\n}\n\n// [Gx,Gy] = grad2(I) - see gradient2.m\nvoid mGrad2( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d; float *I, *Gx, *Gy;\n  checkArgs(nl,pl,nr,pr,1,2,1,1,&h,&w,&d,mxSINGLE_CLASS,(void**)&I);\n  if(h<2 || w<2) mexErrMsgTxt(\"I must be at least 2x2.\");\n  pl[0]= mxCreateMatrix3( h, w, d, mxSINGLE_CLASS, 0, (void**) &Gx );\n  pl[1]= mxCreateMatrix3( h, w, d, mxSINGLE_CLASS, 0, (void**) &Gy );\n  grad2( I, Gx, Gy, h, w, d );\n}\n\n// [M,O] = gradMag( I, channel, full ) - see gradientMag.m\nvoid mGradMag( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d, c, full; float *I, *M, *O=0;\n  checkArgs(nl,pl,nr,pr,1,2,3,3,&h,&w,&d,mxSINGLE_CLASS,(void**)&I);\n  if(h<2 || w<2) mexErrMsgTxt(\"I must be at least 2x2.\");\n  c = (int) mxGetScalar(pr[1]); full = (int) mxGetScalar(pr[2]);\n  if( c>0 && c<=d ) { I += h*w*(c-1); d=1; }\n  pl[0] = mxCreateMatrix3(h,w,1,mxSINGLE_CLASS,0,(void**)&M);\n  if(nl>=2) pl[1] = mxCreateMatrix3(h,w,1,mxSINGLE_CLASS,0,(void**)&O);\n  gradMag(I, M, O, h, w, d, full>0 );\n}\n\n// gradMagNorm( M, S, norm ) - operates on M - see gradientMag.m\nvoid mGradMagNorm( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d; float *M, *S, norm;\n  checkArgs(nl,pl,nr,pr,0,0,3,3,&h,&w,&d,mxSINGLE_CLASS,(void**)&M);\n  if( mxGetM(pr[1])!=h || mxGetN(pr[1])!=w || d!=1 ||\n    mxGetClassID(pr[1])!=mxSINGLE_CLASS ) mexErrMsgTxt(\"M or S is bad.\");\n  S = (float*) mxGetPr(pr[1]); norm = (float) mxGetScalar(pr[2]);\n  gradMagNorm(M,S,h,w,norm);\n}\n\n// H=gradHist(M,O,[...]) - see gradientHist.m\nvoid mGradHist( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d, hb, wb, nChns, binSize, nOrients, softBin, useHog;\n  bool full; float *M, *O, *H, clipHog;\n  checkArgs(nl,pl,nr,pr,1,3,2,8,&h,&w,&d,mxSINGLE_CLASS,(void**)&M);\n  O = (float*) mxGetPr(pr[1]);\n  if( mxGetM(pr[1])!=h || mxGetN(pr[1])!=w || d!=1 ||\n    mxGetClassID(pr[1])!=mxSINGLE_CLASS ) mexErrMsgTxt(\"M or O is bad.\");\n  binSize  = (nr>=3) ? (int)   mxGetScalar(pr[2])    : 8;\n  nOrients = (nr>=4) ? (int)   mxGetScalar(pr[3])    : 9;\n  softBin  = (nr>=5) ? (int)   mxGetScalar(pr[4])    : 1;\n  useHog   = (nr>=6) ? (int)   mxGetScalar(pr[5])    : 0;\n  clipHog  = (nr>=7) ? (float) mxGetScalar(pr[6])    : 0.2f;\n  full     = (nr>=8) ? (bool) (mxGetScalar(pr[7])>0) : false;\n  hb = h/binSize; wb = w/binSize;\n  nChns = useHog== 0 ? nOrients : (useHog==1 ? nOrients*4 : nOrients*3+5);\n  pl[0] = mxCreateMatrix3(hb,wb,nChns,mxSINGLE_CLASS,1,(void**)&H);\n  if( nOrients==0 ) return;\n  if( useHog==0 ) {\n    gradHist( M, O, H, h, w, binSize, nOrients, softBin, full );\n  } else if(useHog==1) {\n    hog( M, O, H, h, w, binSize, nOrients, softBin, full, clipHog );\n  } else {\n    fhog( M, O, H, h, w, binSize, nOrients, softBin, clipHog );\n  }\n}\n\n// inteface to various gradient functions (see corresponding Matlab functions)\nvoid mexFunction( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int f; char action[1024]; f=mxGetString(pr[0],action,1024); nr--; pr++;\n  if(f) mexErrMsgTxt(\"Failed to get action.\");\n  else if(!strcmp(action,\"gradient2\")) mGrad2(nl,pl,nr,pr);\n  else if(!strcmp(action,\"gradientMag\")) mGradMag(nl,pl,nr,pr);\n  else if(!strcmp(action,\"gradientMagNorm\")) mGradMagNorm(nl,pl,nr,pr);\n  else if(!strcmp(action,\"gradientHist\")) mGradHist(nl,pl,nr,pr);\n  else mexErrMsgTxt(\"Invalid action.\");\n}\n#endif\n\n\nfloat* crop_H(float *H,int* h_height,int* h_width,int depth,int dh,int dw){\n    int crop_h = *h_height-dh-1;\n    int crop_w = *h_width-dw-1;\n    float* crop_H = new float[crop_h*crop_w*depth];\n\n    for(int i = 1;i < *h_height-dh;i ++)\n        for(int j = 1;j < *h_width-dw;j ++)\n            for(int k = 0;k < depth;k ++)\n                crop_H[i-1 + (j-1)*(crop_h) + k*(crop_h*crop_w)] = H[k*(*h_width * *h_height) + j*(*h_height) + i];\n    delete []H;\n    *h_height = crop_h;*h_width = crop_w;\n    return crop_H;\n}\n\nfloat* fhog(float* I,int height,int width,int channel,int *h,int *w,int *d,int binSize = 4,int nOrients = 9,float clip=0.2f,bool crop = false){\n\n//float* fhog(float* I,int height,int width,int channel,int *h,int *w,int *d,int binSize, int nOrients, float clip, bool crop){\n    float *M = new float[height*width], *O = new float[height*width];\n    gradMag(I,M,O, height, width, channel, true);\n\n    *h = height/binSize;\n    *w = width/binSize;\n    *d = nOrients*3+5;\n\tprintf(\"fhog.cpp506:(binSize:%d, h:%d, w:%d, d:%d)\\n\", binSize, *h, *w, *d);\n\n    float* H = new float[(*h)*(*w)*(*d)];\n    memset(H,0.0f,(*h)*(*w)*(*d)*sizeof(float));\n\n    if(!fhog( M, O, H, height, width, binSize, nOrients, -1, clip )){\n\t\tdelete []M; \n\t\tdelete []O;\n\t\tdelete []H;\n        return NULL;\n    }\n\n    delete []M;delete []O;\n    if(!crop)\n        return H;\n    return crop_H(H,h,w,*d,height%binSize < binSize/2,width%binSize < binSize/2);\n}\n\nvoid change_format(float *des,float *source,int height,int width,int channel){\n    for(int i = 0;i < height;i ++)\n        for(int j = 0;j < width;j ++)\n            for(int k = 0;k < channel;k ++)\n                des[k*height*width+j*height+i] = source[i*width*channel+j*channel+k];\n}\nfloat* HOGXYZ(const cv::Mat& input, int &len){\n\tint binSize = 16;\n\tint nOrients = 9;\n\tfloat clip = 0.2f;\n\tbool crop = false;\n    int HEIGHT = input.rows;\n    int WIDTH = input.cols;\n    int DEPTH = input.channels();\n\n    CV_Assert(DEPTH == 1);\n\n    float *II = new float[HEIGHT*WIDTH*DEPTH];\n    int count = 0;\n    for (size_t i = 0; i < HEIGHT; i++) {\n        for (size_t j = 0; j < WIDTH; j++) {\n            // Vec3b vec = image.at<Vec3b>(i,j);\n            for (size_t k = 0; k < DEPTH; k++) {\n                II[count] = input.at<uchar>(i, j) / 255.;\n                // cout<<II[count]<<endl;\n                count++;\n            }\n        }\n    }\n\n    float *I = new float[HEIGHT*WIDTH*DEPTH];\n    change_format(I,II,HEIGHT,WIDTH,DEPTH);\n    int h,w,d;\n    float* HH = fhog(I,HEIGHT,WIDTH,DEPTH,&h,&w,&d,binSize,nOrients,clip,crop);\n    if(HH == NULL){\n\t\tdelete []I;\n\t\tdelete []II;\n        return NULL; \n    }\n\tprintf(\"fhog563:(WIDTH:%d, HEIGHT:%d, DEPTH:%d, w:%d, h:%d, d:%d)\\n\", \n\t\tWIDTH, HEIGHT, DEPTH, w, h, d);\n    float* H = new float[h*w*d];\n    change_format(H,HH,d,w,h);\n    delete []II;delete []I;delete []HH;\n\tlen = w*h*d;\n    return H;\n}\ncv::Mat fhog(const cv::Mat& input, int binSize, int nOrients, float clip, bool crop){\n    int HEIGHT = input.rows;\n    int WIDTH = input.cols;\n    int DEPTH = input.channels();\n\n    CV_Assert(DEPTH == 1);\n\n    float *II = new float[HEIGHT*WIDTH*DEPTH];\n    int count = 0;\n    for (size_t i = 0; i < HEIGHT; i++) {\n        for (size_t j = 0; j < WIDTH; j++) {\n            // Vec3b vec = image.at<Vec3b>(i,j);\n            for (size_t k = 0; k < DEPTH; k++) {\n                II[count] = input.at<uchar>(i, j) / 255.;\n                // cout<<II[count]<<endl;\n                count++;\n            }\n        }\n    }\n\n    float *I = new float[HEIGHT*WIDTH*DEPTH];\n    change_format(I,II,HEIGHT,WIDTH,DEPTH);\n    int h,w,d;\n    float* HH = fhog(I,HEIGHT,WIDTH,DEPTH,&h,&w,&d,binSize,nOrients,clip,crop);\n    if(HH == NULL){\n\t\tdelete []I;\n\t\tdelete []II;\n        cv::Mat re;\n        return re; \n    }\n\tprintf(\"fhog563:(WIDTH:%d, HEIGHT:%d, DEPTH:%d, w:%d, h:%d, d:%d)\\n\", \n\t\tWIDTH, HEIGHT, DEPTH, w, h, d);\n    float* H = new float[h*w*d];\n    change_format(H,HH,d,w,h);\n    cv::Mat fhog_feature(h,w,CV_32FC(32),H);\n\tcv::Mat out = fhog_feature.clone();\n    delete []II;delete []I;delete []HH;\n\tdelete []H;\n    return out;\n}\n"
  },
  {
    "path": "fdsst/fhog.h",
    "content": "#ifndef FHOG_H\n#define FHOG_H\n#include <opencv2/core/core.hpp>\n#include <boost/thread/mutex.hpp>\n#ifdef WIN32\n#ifndef _CRTDBG_MAP_ALLOC\n#define _CRTDBG_MAP_ALLOC\n#endif\n#include <stdlib.h>  \n#include <crtdbg.h> \n#ifdef _DEBUG  \n\t#ifndef new\n\t#define new   new(_NORMAL_BLOCK, __FILE__, __LINE__)  \n\t#endif\n#endif\n#endif\n//#include <cstdlib>\n#include <cmath>\n#include <cstring>\n#include \"sse.hpp\"\n#include <map>\n\n\n/**\n    Inputs:\n        float* I        - a gray or color image matrix with shape = channel x width x height\n        int *h, *w, *d  - return the size of the returned hog features\n        int binSize     -[8] spatial bin size\n        int nOrients    -[9] number of orientation bins\n        float clip      -[.2] value at which to clip histogram bins\n        bool crop       -[false] if true crop boundaries\n\n    Return:\n        float* H        - computed hog features with shape: (nOrients*3+5) x (w/binSize) x (h/binSize), if not crop\n\n    Author:\n        Sophia\n    Date:\n        2015-01-15\n**/\n\n//float* fhog(float* I,int height,int width,int channel,int *h,int *w,int *d,int binSize = 4,int nOrients = 9,float clip=0.2f,bool crop = false);\nfloat *HOGXYZ(const cv::Mat &input, int &len);\ncv::Mat fhog(const cv::Mat& input, int binSize = 4,int nOrients = 9,float clip=0.2f,bool crop = false);\n\nvoid change_format(float *des,float *source,int height,int width,int channel);\n//static std::map<void *, int> _nnmm;\n//static boost::mutex nmm_;\n// wrapper functions if compiling from C/C++\ninline void wrError(const char *errormsg) { throw errormsg; }\ninline void* wrCalloc(size_t num, size_t size) { \n\t/*unsigned char *buf = new unsigned char[num*size]; \n\t_nnmm.insert(std::make_pair(buf, 0));\n\treturn (void*)buf;\n\t*/\n\t//boost::mutex::scoped_lock lock(nmm_);\n\tvoid *buf = calloc(num, size);\n\t\n\t//_nnmm.insert(std::make_pair(buf, 0));\n\treturn buf;\n}\ninline void* wrMalloc( size_t size ) { \n\t//boost::mutex::scoped_lock lock(nmm_);\n\tvoid * buf = malloc(size); \n\t\n\t//_nnmm.insert(std::make_pair(buf, 0));\n\treturn buf;\n\t/*unsigned char *buf = new unsigned char[size];\n\t_nnmm.insert(std::make_pair(buf, 0));\n\treturn (void*)buf;*/\n}\ninline void wrFree( void * ptr ) { \n\t//boost::mutex::scoped_lock lock(nmm_);\n\t//std::map<void *, int>::iterator it;\n\t//it = _nnmm.find(ptr);\n\t//if (it == _nnmm.end()) {\n\t//\tprintf(\"wo qu!!\\n\");\n\t\t//exit(0);\n\t//\treturn;\n\t//}\n\tfree(ptr); \n\t//_nnmm.erase(it);\n\t/*unsigned char *buf = (unsigned char *)ptr;\n\tstd::map<unsigned char *, int>::iterator it;\n\tit = _nnmm.find(buf);\n\tif (it == _nnmm.end()) {\n\t\tprintf(\"wo qu!!\\n\");\n\t\texit(0);\n\t}\n\tdelete []buf;\n\t_nnmm.erase(it);*/\n}\n\n\nvoid hoglog();\nfloat* acosTable(); \n#endif\n"
  },
  {
    "path": "fdsst/fhogbk/fhog.cpp",
    "content": "#include <cstring>\n#include <iostream>\n\nusing namespace std;\n\n#include \"fhog.h\"\n#undef MIN\n#define GLOG_NO_ABBREVIATED_SEVERITIES\n#include <glog/logging.h>\n// platform independent aligned memory allocation (see also alFree)\nvoid* alMalloc( size_t size, int alignment, unsigned char **out) {\n  const size_t pSize = sizeof(void*);\n  const size_t aaa = alignment-1;\n  unsigned char *tmp = new unsigned char[size+aaa+pSize];\n  *out = tmp;\n  void *raw = (void*)tmp;\n  void *aligned = (void*) (\n\t\t\t\t((size_t)raw + pSize + aaa) & \n\t\t\t\t~aaa\n\t\t\t  );\n\n  *(void**)((size_t)aligned - pSize) = raw;\n  return aligned;\n}\n\n\n/*******************************************************************************\n* Piotr's Computer Vision Matlab Toolbox      Version 3.30\n* Copyright 2014 Piotr Dollar & Ron Appel.  [pdollar-at-gmail.com]\n* Licensed under the Simplified BSD License [see external/bsd.txt]\n*******************************************************************************/\n// #include \"wrappers.hpp\"\n\n#define PI 3.14159265f\n\n// compute x and y gradients for just one column (uses sse)\nvoid grad1( float *I, float *Gx, float *Gy, int h, int w, int x ) {\n  int y, y1; float *Ip, *In, r; __m128 *_Ip, *_In, *_G, _r;\n  // compute column of Gx\n  Ip=I-h; In=I+h; r=.5f;\n  if(x==0) { r=1; Ip+=h; } else if(x==w-1) { r=1; In-=h; }\n  if( h<4 || h%4>0 || (size_t(I)&15) || (size_t(Gx)&15) ) {\n    for( y=0; y<h; y++ ) *Gx++=(*In++-*Ip++)*r;\n  } else {\n    _G=(__m128*) Gx; _Ip=(__m128*) Ip; _In=(__m128*) In; _r = sse::SET(r);\n    for(y=0; y<h; y+=4) *_G++=sse::MUL(sse::SUB(*_In++,*_Ip++),_r);\n  }\n  // compute column of Gy\n  #define GRADY(r) *Gy++=(*In++-*Ip++)*r;\n  Ip=I; In=Ip+1;\n  // GRADY(1); Ip--; for(y=1; y<h-1; y++) GRADY(.5f); In--; GRADY(1);\n  y1=((~((size_t) Gy) + 1) & 15)/4; if(y1==0) y1=4; if(y1>h-1) y1=h-1;\n  GRADY(1); Ip--; for(y=1; y<y1; y++) GRADY(.5f);\n  _r = sse::SET(.5f); _G=(__m128*) Gy;\n  for(; y+4<h-1; y+=4, Ip+=4, In+=4, Gy+=4)\n    *_G++=sse::MUL(sse::SUB(sse::LDu(*In),sse::LDu(*Ip)),_r);\n  for(; y<h-1; y++) GRADY(.5f); In--; GRADY(1);\n  #undef GRADY\n}\n\n// compute x and y gradients at each location (uses sse)\nvoid grad2( float *I, float *Gx, float *Gy, int h, int w, int d ) {\n  int o, x, c, a=w*h; for(c=0; c<d; c++) for(x=0; x<w; x++) {\n    o=c*a+x*h; grad1( I+o, Gx+o, Gy+o, h, w, x );\n  }\n}\n\nstatic bool _hoglog = false;\n\nvoid hoglog(){\n\t_hoglog = true;\n}\n// build lookup table a[] s.t. a[x*n]~=acos(x) for x in [-1,1]\nfloat* acosTable() {\n  const int n=10000, b=10; \n  int i;\n  static float a[n*2+b*2]; \n  static bool init=false;\n  float *a1=a+n+b; \n  if( init ){\n\t return a1;\n  }\n  for( i=-n-b; i<-n; i++ )   a1[i]=PI;\n  for( i=-n; i<n; i++ )      a1[i]=float(acos(i/float(n)));\n  for( i=n; i<n+b; i++ )     a1[i]=0;\n  for( i=-n-b; i<n/10; i++ ) if( a1[i] > PI-1e-6f ) a1[i]=PI-1e-6f;\n  init=true; return a1;\n}\n\n// compute gradient magnitude and orientation at each location (uses sse)\nvoid gradMag( float *I, float *M, float *O, int h, int w, int d, bool full ) {\n  int x, y, y1, c, h4, s; float *Gx, *Gy, *M2; __m128 *_Gx, *_Gy, *_M2, _m;\n  float *acost = acosTable(), acMult=10000.0f;\n  // allocate memory for storing one column of output (padded so h4%4==0)\n  h4=(h%4==0) ? h : h-(h%4)+4; s=d*h4*sizeof(float);\n  //LOG(INFO) << \"gradMag----d:\" << d << \", h4:\" << h4 << \", s:\" << s;\n  unsigned char *d1 = NULL;\n  unsigned char *d2 = NULL;\n  unsigned char *d3 = NULL;\n  M2=(float*) alMalloc(s,16, &d1); _M2=(__m128*) M2;\n  Gx=(float*) alMalloc(s,16, &d2); _Gx=(__m128*) Gx;\n  Gy=(float*) alMalloc(s,16, &d3); _Gy=(__m128*) Gy;\n  // compute gradient magnitude and orientation for each column\n  for( x=0; x<w; x++ ) {\n    // compute gradients (Gx, Gy) with maximum squared magnitude (M2)\n    for(c=0; c<d; c++) {\n      grad1( I+x*h+c*w*h, Gx+c*h4, Gy+c*h4, h, w, x );\n      for( y=0; y<h4/4; y++ ) {\n        y1=h4/4*c+y;\n        _M2[y1]=sse::ADD(sse::MUL(_Gx[y1],_Gx[y1]),sse::MUL(_Gy[y1],_Gy[y1]));\n        if( c==0 ) continue; _m = sse::CMPGT( _M2[y1], _M2[y] );\n        _M2[y] = sse::OR( sse::AND(_m,_M2[y1]), sse::ANDNOT(_m,_M2[y]) );\n        _Gx[y] = sse::OR( sse::AND(_m,_Gx[y1]), sse::ANDNOT(_m,_Gx[y]) );\n        _Gy[y] = sse::OR( sse::AND(_m,_Gy[y1]), sse::ANDNOT(_m,_Gy[y]) );\n      }\n    }\n    // compute gradient mangitude (M) and normalize Gx\n    for( y=0; y<h4/4; y++ ) {\n      _m = sse::MIN( sse::RCPSQRT(_M2[y]), sse::SET(1e10f) );\n      _M2[y] = sse::RCP(_m);\n      if(O) _Gx[y] = sse::MUL( sse::MUL(_Gx[y],_m), sse::SET(acMult) );\n      if(O) _Gx[y] = sse::XOR( _Gx[y], sse::AND(_Gy[y], sse::SET(-0.f)) );\n    };\n    memcpy( M+x*h, M2, h*sizeof(float) );\n    // compute and store gradient orientation (O) via table lookup\n    if( O!=0 ){\n\t for( y=0; y<h; y++ ){\n\t\t if(_hoglog){\n\t\t \t//priaaantf(\"gradMag-w:%d, h:%d---x*h+y:%d, (int)Gx[y]:%d\\n\", w, h, x*h+y, (int)Gx[y]);\n\t\t }\n\t\t O[x*h+y] = acost[(int)Gx[y]];\n\t }\n    }\n    if( O!=0 && full ) {\n      y1=((~size_t(O+x*h)+1)&15)/4; y=0;\n      for( ; y<y1; y++ ) O[y+x*h]+=(Gy[y]<0)*PI;\n      for( ; y<h-4; y+=4 ) sse::STRu( O[y+x*h],\n        sse::ADD( sse::LDu(O[y+x*h]), sse::AND(sse::CMPLT(sse::LDu(Gy[y]),sse::SET(0.f)),sse::SET(PI)) ) );\n      for( ; y<h; y++ ) O[y+x*h]+=(Gy[y]<0)*PI;\n    }\n  }\n  delete []d1;\n  delete []d2;\n  delete []d3;\n}\n\n// normalize gradient magnitude at each location (uses sse)\nvoid gradMagNorm( float *M, float *S, int h, int w, float norm ) {\n  __m128 *_M, *_S, _norm; int i=0, n=h*w, n4=n/4;\n  _S = (__m128*) S; _M = (__m128*) M; _norm = sse::SET(norm);\n  bool sse = !(size_t(M)&15) && !(size_t(S)&15);\n  if(sse) for(; i<n4; i++) { *_M=sse::MUL(*_M,sse::RCP(sse::ADD(*_S++,_norm))); _M++; }\n  if(sse) i*=4; for(; i<n; i++) M[i] /= (S[i] + norm);\n}\n\n// helper for gradHist, quantize O and M into O0, O1 and M0, M1 (uses sse)\nvoid gradQuantize( float *O, float *M, int *O0, int *O1, float *M0, float *M1,\n  int nb, int n, float norm, int nOrients, bool full, bool interpolate )\n{\n  // assumes all *OUTPUT* matrices are 4-byte aligned\n  int i, o0, o1; float o, od, m;\n  __m128i _o0, _o1, *_O0, *_O1; __m128 _o, _od, _m, *_M0, *_M1;\n  // define useful constants\n  const float oMult=(float)nOrients/(full?2*PI:PI); const int oMax=nOrients*nb;\n  const __m128 _norm=sse::SET(norm), _oMult=sse::SET(oMult), _nbf=sse::SET((float)nb);\n  const __m128i _oMax=sse::SET(oMax), _nb=sse::SET(nb);\n  // perform the majority of the work with sse\n  _O0=(__m128i*) O0; _O1=(__m128i*) O1; _M0=(__m128*) M0; _M1=(__m128*) M1;\n  if( interpolate ) for( i=0; i<=n-4; i+=4 ) {\n    _o=sse::MUL(sse::LDu(O[i]),_oMult); _o0=sse::CVT(_o); _od=sse::SUB(_o,sse::CVT(_o0));\n    _o0=sse::CVT(sse::MUL(sse::CVT(_o0),_nbf)); _o0=sse::AND(sse::CMPGT(_oMax,_o0),_o0); *_O0++=_o0;\n    _o1=sse::ADD(_o0,_nb); _o1=sse::AND(sse::CMPGT(_oMax,_o1),_o1); *_O1++=_o1;\n    _m=sse::MUL(sse::LDu(M[i]),_norm); *_M1=sse::MUL(_od,_m); *_M0++=sse::SUB(_m,*_M1); _M1++;\n  } else for( i=0; i<=n-4; i+=4 ) {\n    _o=sse::MUL(sse::LDu(O[i]),_oMult); _o0=sse::CVT(sse::ADD(_o,sse::SET(.5f)));\n    _o0=sse::CVT(sse::MUL(sse::CVT(_o0),_nbf)); _o0=sse::AND(sse::CMPGT(_oMax,_o0),_o0); *_O0++=_o0;\n    *_M0++=sse::MUL(sse::LDu(M[i]),_norm); *_M1++=sse::SET(0.f); *_O1++=sse::SET(0);\n  }\n  // compute trailing locations without sse\n  if( interpolate ) for(; i<n; i++ ) {\n    o=O[i]*oMult; o0=(int) o; od=o-o0;\n    o0*=nb; if(o0>=oMax) o0=0; O0[i]=o0;\n    o1=o0+nb; if(o1==oMax) o1=0; O1[i]=o1;\n    m=M[i]*norm; M1[i]=od*m; M0[i]=m-M1[i];\n  } else for(; i<n; i++ ) {\n    o=O[i]*oMult; o0=(int) (o+.5f);\n    o0*=nb; if(o0>=oMax) o0=0; O0[i]=o0;\n    M0[i]=M[i]*norm; M1[i]=0; O1[i]=0;\n  }\n}\n\n// compute nOrients gradient histograms per bin x bin block of pixels\nvoid gradHist( float *M, float *O, float *H, int h, int w,\n  int bin, int nOrients, int softBin, bool full )\n{\n  const int hb=h/bin, wb=w/bin, h0=hb*bin, w0=wb*bin, nb=wb*hb;\n  const float s=(float)bin, sInv=1/s, sInv2=1/s/s;\n  float *H0, *H1, *M0, *M1; int x, y; int *O0, *O1; float xb, init;\n  unsigned char *d1 = NULL;\n  unsigned char *d2 = NULL;\n  unsigned char *d3 = NULL;\n  unsigned char *d4 = NULL;\n\n  O0=(int*)alMalloc(h*sizeof(int),16, &d1); \n  M0=(float*) alMalloc(h*sizeof(float),16, &d2);\n  O1=(int*)alMalloc(h*sizeof(int),16, &d3); \n  M1=(float*) alMalloc(h*sizeof(float),16, &d4);\n  // main loop\n  for( x=0; x<w0; x++ ) {\n    // compute target orientation bins for entire column - very fast\n    gradQuantize(O+x*h,M+x*h,O0,O1,M0,M1,nb,h0,sInv2,nOrients,full,softBin>=0);\n\n    if( softBin<0 && softBin%2==0 ) {\n      // no interpolation w.r.t. either orienation or spatial bin\n      H1=H+(x/bin)*hb;\n      #define GH H1[O0[y]]+=M0[y]; y++;\n      if( bin==1 )      for(y=0; y<h0;) { GH; H1++; }\n      else if( bin==2 ) for(y=0; y<h0;) { GH; GH; H1++; }\n      else if( bin==3 ) for(y=0; y<h0;) { GH; GH; GH; H1++; }\n      else if( bin==4 ) for(y=0; y<h0;) { GH; GH; GH; GH; H1++; }\n      else for( y=0; y<h0;) { for( int y1=0; y1<bin; y1++ ) { GH; } H1++; }\n      #undef GH\n\n    } else if( softBin%2==0 || bin==1 ) {\n      // interpolate w.r.t. orientation only, not spatial bin\n      H1=H+(x/bin)*hb;\n      #define GH H1[O0[y]]+=M0[y]; H1[O1[y]]+=M1[y]; y++;\n      if( bin==1 )      for(y=0; y<h0;) { GH; H1++; }\n      else if( bin==2 ) for(y=0; y<h0;) { GH; GH; H1++; }\n      else if( bin==3 ) for(y=0; y<h0;) { GH; GH; GH; H1++; }\n      else if( bin==4 ) for(y=0; y<h0;) { GH; GH; GH; GH; H1++; }\n      else for( y=0; y<h0;) { for( int y1=0; y1<bin; y1++ ) { GH; } H1++; }\n      #undef GH\n\n    } else {\n      // interpolate using trilinear interpolation\n      float ms[4], xyd, yb, xd, yd; __m128 _m, _m0, _m1;\n      bool hasLf, hasRt; int xb0, yb0;\n      if( x==0 ) { init=(0+.5f)*sInv-0.5f; xb=init; }\n      hasLf = xb>=0; xb0 = hasLf?(int)xb:-1; hasRt = xb0 < wb-1;\n      xd=xb-xb0; xb+=sInv; yb=init; y=0;\n      // macros for code conciseness\n      #define GHinit yd=yb-yb0; yb+=sInv; H0=H+xb0*hb+yb0; xyd=xd*yd; \\\n        ms[0]=1-xd-yd+xyd; ms[1]=yd-xyd; ms[2]=xd-xyd; ms[3]=xyd;\n      #define GH(H,ma,mb) H1=H; sse::STRu(*H1,sse::ADD(sse::LDu(*H1),sse::MUL(ma,mb)));\n      // leading rows, no top bin\n      for( ; y<bin/2; y++ ) {\n        yb0=-1; GHinit;\n        if(hasLf) { H0[O0[y]+1]+=ms[1]*M0[y]; H0[O1[y]+1]+=ms[1]*M1[y]; }\n        if(hasRt) { H0[O0[y]+hb+1]+=ms[3]*M0[y]; H0[O1[y]+hb+1]+=ms[3]*M1[y]; }\n      }\n      // main rows, has top and bottom bins, use SSE for minor speedup\n      if( softBin<0 ) for( ; ; y++ ) {\n        yb0 = (int) yb; if(yb0>=hb-1) break; GHinit; _m0=sse::SET(M0[y]);\n        if(hasLf) { _m=sse::SET(0,0,ms[1],ms[0]); GH(H0+O0[y],_m,_m0); }\n        if(hasRt) { _m=sse::SET(0,0,ms[3],ms[2]); GH(H0+O0[y]+hb,_m,_m0); }\n      } else for( ; ; y++ ) {\n        yb0 = (int) yb; if(yb0>=hb-1) break; GHinit;\n        _m0=sse::SET(M0[y]); _m1=sse::SET(M1[y]);\n        if(hasLf) { _m=sse::SET(0,0,ms[1],ms[0]);\n          GH(H0+O0[y],_m,_m0); GH(H0+O1[y],_m,_m1); }\n        if(hasRt) { _m=sse::SET(0,0,ms[3],ms[2]);\n          GH(H0+O0[y]+hb,_m,_m0); GH(H0+O1[y]+hb,_m,_m1); }\n      }\n      // final rows, no bottom bin\n      for( ; y<h0; y++ ) {\n        yb0 = (int) yb; GHinit;\n        if(hasLf) { H0[O0[y]]+=ms[0]*M0[y]; H0[O1[y]]+=ms[0]*M1[y]; }\n        if(hasRt) { H0[O0[y]+hb]+=ms[2]*M0[y]; H0[O1[y]+hb]+=ms[2]*M1[y]; }\n      }\n      #undef GHinit\n      #undef GH\n    }\n  }\n  delete []d1;\n  delete []d2;\n  delete []d3;\n  delete []d4;\n  // normalize boundary bins which only get 7/8 of weight of interior bins\n  if( softBin%2!=0 ) for( int o=0; o<nOrients; o++ ) {\n    x=0; for( y=0; y<hb; y++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n    y=0; for( x=0; x<wb; x++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n    x=wb-1; for( y=0; y<hb; y++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n    y=hb-1; for( x=0; x<wb; x++ ) H[o*nb+x*hb+y]*=8.f/7.f;\n  }\n}\n\n/******************************************************************************/\n\n// HOG helper: compute 2x2 block normalization values (padded by 1 pixel)\nfloat* hogNormMatrix( float *H, int nOrients, int hb, int wb, int bin ) {\n  float *N, *N1, *n; int o, x, y, dx, dy, hb1=hb+1, wb1=wb+1;\n  float eps = 1e-4f/4/bin/bin/bin/bin; // precise backward equality\n  N = new float[hb1*wb1];\n  N1=N+hb1+1;\n  for( o=0; o<nOrients; o++ ) for( x=0; x<wb; x++ ) for( y=0; y<hb; y++ )\n    N1[x*hb1+y] += H[o*wb*hb+x*hb+y]*H[o*wb*hb+x*hb+y];\n  for( x=0; x<wb-1; x++ ) for( y=0; y<hb-1; y++ ) {\n    n=N1+x*hb1+y; *n=1/float(sqrt(n[0]+n[1]+n[hb1]+n[hb1+1]+eps)); }\n  x=0;     dx= 1; dy= 1; y=0;                  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=0;     dx= 1; dy= 0; for(y=0; y<hb1; y++)  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=0;     dx= 1; dy=-1; y=hb1-1;              N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=wb1-1; dx=-1; dy= 1; y=0;                  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=wb1-1; dx=-1; dy= 0; for( y=0; y<hb1; y++) N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  x=wb1-1; dx=-1; dy=-1; y=hb1-1;              N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  y=0;     dx= 0; dy= 1; for(x=0; x<wb1; x++)  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  y=hb1-1; dx= 0; dy=-1; for(x=0; x<wb1; x++)  N[x*hb1+y]=N[(x+dx)*hb1+y+dy];\n  return N;\n}\n\n// HOG helper: compute HOG or FHOG channels\nvoid hogChannels( float *H, const float *R, const float *N,\n  int hb, int wb, int nOrients, float clip, int type )\n{\n  #define GETT(blk) t=R1[y]*N1[y-(blk)]; if(t>clip) t=clip; c++;\n  const float r=.2357f; int o, x, y, c; float t;\n  const int nb=wb*hb, nbo=nOrients*nb, hb1=hb+1;\n  for( o=0; o<nOrients; o++ ) for( x=0; x<wb; x++ ) {\n    const float *R1=R+o*nb+x*hb, *N1=N+x*hb1+hb1+1;\n    float *H1 = (type<=1) ? (H+o*nb+x*hb) : (H+x*hb);\n    if( type==0) for( y=0; y<hb; y++ ) {\n      // store each orientation and normalization (nOrients*4 channels)\n      c=-1; GETT(0); H1[c*nbo+y]=t; GETT(1); H1[c*nbo+y]=t;\n      GETT(hb1); H1[c*nbo+y]=t; GETT(hb1+1); H1[c*nbo+y]=t;\n    } else if( type==1 ) for( y=0; y<hb; y++ ) {\n      // sum across all normalizations (nOrients channels)\n      c=-1; GETT(0); H1[y]+=t*.5f; GETT(1); H1[y]+=t*.5f;\n      GETT(hb1); H1[y]+=t*.5f; GETT(hb1+1); H1[y]+=t*.5f;\n    } else if( type==2 ) for( y=0; y<hb; y++ ) {\n      // sum across all orientations (4 channels)\n      c=-1; GETT(0); H1[c*nb+y]+=t*r; GETT(1); H1[c*nb+y]+=t*r;\n      GETT(hb1); H1[c*nb+y]+=t*r; GETT(hb1+1); H1[c*nb+y]+=t*r;\n    }\n  }\n  #undef GETT\n}\n\n// compute HOG features\nvoid hog( float *M, float *O, float *H, int h, int w, int binSize,\n  int nOrients, int softBin, bool full, float clip )\n{\n  float *N, *R; const int hb=h/binSize, wb=w/binSize, nb=hb*wb;\n  // compute unnormalized gradient histograms\n  R = new float[wb*hb*nOrients];\n  gradHist( M, O, R, h, w, binSize, nOrients, softBin, full );\n  // compute block normalization values\n  N = hogNormMatrix( R, nOrients, hb, wb, binSize );\n  // perform four normalizations per spatial block\n  hogChannels( H, R, N, hb, wb, nOrients, clip, 0 );\n  delete []N;\n  delete []R;\n}\n\n// compute FHOG features\nbool fhog( float *M, float *O, float *H, int h, int w, int binSize,\n  int nOrients, int softBin, float clip )\n{\n  const int hb=h/binSize, wb=w/binSize, nb=hb*wb, nbo=nb*nOrients;\n  float *N, *R1, *R2; int o, x;\n  // compute unnormalized constrast sensitive histograms\n  int sz = wb*nb*nOrients;\n  if(sz <= 0){\n     return false;\n  }\n  R1 = new float[wb*hb*nOrients*2];\n  gradHist( M, O, R1, h, w, binSize, nOrients*2, softBin, true );\n  // compute unnormalized contrast insensitive histograms\n  R2 = new float[wb*hb*nOrients];\n  for( o=0; o<nOrients; o++ ) for( x=0; x<nb; x++ )\n    R2[o*nb+x] = R1[o*nb+x]+R1[(o+nOrients)*nb+x];\n  // compute block normalization values\n  N = hogNormMatrix( R2, nOrients, hb, wb, binSize );\n  // normalized histograms and texture channels\n  hogChannels( H+nbo*0, R1, N, hb, wb, nOrients*2, clip, 1 );\n  hogChannels( H+nbo*2, R2, N, hb, wb, nOrients*1, clip, 1 );\n  hogChannels( H+nbo*3, R1, N, hb, wb, nOrients*2, clip, 2 );\n  delete []N;\n  delete []R1;\n  delete []R2;\n  return true;\n}\n\n/******************************************************************************/\n#ifdef MATLAB_MEX_FILE\n// Create [hxwxd] mxArray array, initialize to 0 if c=true\nmxArray* mxCreateMatrix3( int h, int w, int d, mxClassID id, bool c, void **I ){\n  const int dims[3]={h,w,d}, n=h*w*d; int b; mxArray* M;\n  if( id==mxINT32_CLASS ) b=sizeof(int);\n  else if( id==mxDOUBLE_CLASS ) b=sizeof(double);\n  else if( id==mxSINGLE_CLASS ) b=sizeof(float);\n  else mexErrMsgTxt(\"Unknown mxClassID.\");\n  *I = c ? mxCalloc(n,b) : mxMalloc(n*b);\n  M = mxCreateNumericMatrix(0,0,id,mxREAL);\n  mxSetData(M,*I); mxSetDimensions(M,dims,3); return M;\n}\n\n// Check inputs and outputs to mex, retrieve first input I\nvoid checkArgs( int nl, mxArray *pl[], int nr, const mxArray *pr[], int nl0,\n  int nl1, int nr0, int nr1, int *h, int *w, int *d, mxClassID id, void **I )\n{\n  const int *dims; int nDims;\n  if( nl<nl0 || nl>nl1 ) mexErrMsgTxt(\"Incorrect number of outputs.\");\n  if( nr<nr0 || nr>nr1 ) mexErrMsgTxt(\"Incorrect number of inputs.\");\n  nDims = mxGetNumberOfDimensions(pr[0]); dims = mxGetDimensions(pr[0]);\n  *h=dims[0]; *w=dims[1]; *d=(nDims==2) ? 1 : dims[2]; *I = mxGetPr(pr[0]);\n  if( nDims!=2 && nDims!=3 ) mexErrMsgTxt(\"I must be a 2D or 3D array.\");\n  if( mxGetClassID(pr[0])!=id ) mexErrMsgTxt(\"I has incorrect type.\");\n}\n\n// [Gx,Gy] = grad2(I) - see gradient2.m\nvoid mGrad2( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d; float *I, *Gx, *Gy;\n  checkArgs(nl,pl,nr,pr,1,2,1,1,&h,&w,&d,mxSINGLE_CLASS,(void**)&I);\n  if(h<2 || w<2) mexErrMsgTxt(\"I must be at least 2x2.\");\n  pl[0]= mxCreateMatrix3( h, w, d, mxSINGLE_CLASS, 0, (void**) &Gx );\n  pl[1]= mxCreateMatrix3( h, w, d, mxSINGLE_CLASS, 0, (void**) &Gy );\n  grad2( I, Gx, Gy, h, w, d );\n}\n\n// [M,O] = gradMag( I, channel, full ) - see gradientMag.m\nvoid mGradMag( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d, c, full; float *I, *M, *O=0;\n  checkArgs(nl,pl,nr,pr,1,2,3,3,&h,&w,&d,mxSINGLE_CLASS,(void**)&I);\n  if(h<2 || w<2) mexErrMsgTxt(\"I must be at least 2x2.\");\n  c = (int) mxGetScalar(pr[1]); full = (int) mxGetScalar(pr[2]);\n  if( c>0 && c<=d ) { I += h*w*(c-1); d=1; }\n  pl[0] = mxCreateMatrix3(h,w,1,mxSINGLE_CLASS,0,(void**)&M);\n  if(nl>=2) pl[1] = mxCreateMatrix3(h,w,1,mxSINGLE_CLASS,0,(void**)&O);\n  gradMag(I, M, O, h, w, d, full>0 );\n}\n\n// gradMagNorm( M, S, norm ) - operates on M - see gradientMag.m\nvoid mGradMagNorm( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d; float *M, *S, norm;\n  checkArgs(nl,pl,nr,pr,0,0,3,3,&h,&w,&d,mxSINGLE_CLASS,(void**)&M);\n  if( mxGetM(pr[1])!=h || mxGetN(pr[1])!=w || d!=1 ||\n    mxGetClassID(pr[1])!=mxSINGLE_CLASS ) mexErrMsgTxt(\"M or S is bad.\");\n  S = (float*) mxGetPr(pr[1]); norm = (float) mxGetScalar(pr[2]);\n  gradMagNorm(M,S,h,w,norm);\n}\n\n// H=gradHist(M,O,[...]) - see gradientHist.m\nvoid mGradHist( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int h, w, d, hb, wb, nChns, binSize, nOrients, softBin, useHog;\n  bool full; float *M, *O, *H, clipHog;\n  checkArgs(nl,pl,nr,pr,1,3,2,8,&h,&w,&d,mxSINGLE_CLASS,(void**)&M);\n  O = (float*) mxGetPr(pr[1]);\n  if( mxGetM(pr[1])!=h || mxGetN(pr[1])!=w || d!=1 ||\n    mxGetClassID(pr[1])!=mxSINGLE_CLASS ) mexErrMsgTxt(\"M or O is bad.\");\n  binSize  = (nr>=3) ? (int)   mxGetScalar(pr[2])    : 8;\n  nOrients = (nr>=4) ? (int)   mxGetScalar(pr[3])    : 9;\n  softBin  = (nr>=5) ? (int)   mxGetScalar(pr[4])    : 1;\n  useHog   = (nr>=6) ? (int)   mxGetScalar(pr[5])    : 0;\n  clipHog  = (nr>=7) ? (float) mxGetScalar(pr[6])    : 0.2f;\n  full     = (nr>=8) ? (bool) (mxGetScalar(pr[7])>0) : false;\n  hb = h/binSize; wb = w/binSize;\n  nChns = useHog== 0 ? nOrients : (useHog==1 ? nOrients*4 : nOrients*3+5);\n  pl[0] = mxCreateMatrix3(hb,wb,nChns,mxSINGLE_CLASS,1,(void**)&H);\n  if( nOrients==0 ) return;\n  if( useHog==0 ) {\n    gradHist( M, O, H, h, w, binSize, nOrients, softBin, full );\n  } else if(useHog==1) {\n    hog( M, O, H, h, w, binSize, nOrients, softBin, full, clipHog );\n  } else {\n    fhog( M, O, H, h, w, binSize, nOrients, softBin, clipHog );\n  }\n}\n\n// inteface to various gradient functions (see corresponding Matlab functions)\nvoid mexFunction( int nl, mxArray *pl[], int nr, const mxArray *pr[] ) {\n  int f; char action[1024]; f=mxGetString(pr[0],action,1024); nr--; pr++;\n  if(f) mexErrMsgTxt(\"Failed to get action.\");\n  else if(!strcmp(action,\"gradient2\")) mGrad2(nl,pl,nr,pr);\n  else if(!strcmp(action,\"gradientMag\")) mGradMag(nl,pl,nr,pr);\n  else if(!strcmp(action,\"gradientMagNorm\")) mGradMagNorm(nl,pl,nr,pr);\n  else if(!strcmp(action,\"gradientHist\")) mGradHist(nl,pl,nr,pr);\n  else mexErrMsgTxt(\"Invalid action.\");\n}\n#endif\n\n\nfloat* crop_H(float *H,int* h_height,int* h_width,int depth,int dh,int dw){\n    int crop_h = *h_height-dh-1;\n    int crop_w = *h_width-dw-1;\n    float* crop_H = new float[crop_h*crop_w*depth];\n\n    for(int i = 1;i < *h_height-dh;i ++)\n        for(int j = 1;j < *h_width-dw;j ++)\n            for(int k = 0;k < depth;k ++)\n                crop_H[i-1 + (j-1)*(crop_h) + k*(crop_h*crop_w)] = H[k*(*h_width * *h_height) + j*(*h_height) + i];\n    delete []H;\n    *h_height = crop_h;*h_width = crop_w;\n    return crop_H;\n}\n\nfloat* fhog(float* I,int height,int width,int channel,int *h,int *w,int *d,int binSize = 4,int nOrients = 9,float clip=0.2f,bool crop = false){\n\n//float* fhog(float* I,int height,int width,int channel,int *h,int *w,int *d,int binSize, int nOrients, float clip, bool crop){\n    float *M = new float[height*width], *O = new float[height*width];\n    gradMag(I,M,O, height, width, channel, true);\n\n    *h = height/binSize;\n    *w = width/binSize;\n    *d = nOrients*3+5;\n\tprintf(\"fhog.cpp506:(binSize:%d, h:%d, w:%d, d:%d)\\n\", binSize, *h, *w, *d);\n\n    float* H = new float[(*h)*(*w)*(*d)];\n    memset(H,0.0f,(*h)*(*w)*(*d)*sizeof(float));\n\n    if(!fhog( M, O, H, height, width, binSize, nOrients, -1, clip )){\n\t\tdelete []M; \n\t\tdelete []O;\n\t\tdelete []H;\n        return NULL;\n    }\n\n    delete []M;delete []O;\n    if(!crop)\n        return H;\n    return crop_H(H,h,w,*d,height%binSize < binSize/2,width%binSize < binSize/2);\n}\n\nvoid change_format(float *des,float *source,int height,int width,int channel){\n    for(int i = 0;i < height;i ++)\n        for(int j = 0;j < width;j ++)\n            for(int k = 0;k < channel;k ++)\n                des[k*height*width+j*height+i] = source[i*width*channel+j*channel+k];\n}\nfloat* HOGXYZ(const cv::Mat& input, int &len){\n\tint binSize = 16;\n\tint nOrients = 9;\n\tfloat clip = 0.2f;\n\tbool crop = false;\n    int HEIGHT = input.rows;\n    int WIDTH = input.cols;\n    int DEPTH = input.channels();\n\n    CV_Assert(DEPTH == 1);\n\n    float *II = new float[HEIGHT*WIDTH*DEPTH];\n    int count = 0;\n    for (size_t i = 0; i < HEIGHT; i++) {\n        for (size_t j = 0; j < WIDTH; j++) {\n            // Vec3b vec = image.at<Vec3b>(i,j);\n            for (size_t k = 0; k < DEPTH; k++) {\n                II[count] = input.at<uchar>(i, j) / 255.;\n                // cout<<II[count]<<endl;\n                count++;\n            }\n        }\n    }\n\n    float *I = new float[HEIGHT*WIDTH*DEPTH];\n    change_format(I,II,HEIGHT,WIDTH,DEPTH);\n    int h,w,d;\n    float* HH = fhog(I,HEIGHT,WIDTH,DEPTH,&h,&w,&d,binSize,nOrients,clip,crop);\n    if(HH == NULL){\n\t\tdelete []I;\n\t\tdelete []II;\n        return NULL; \n    }\n\tprintf(\"fhog563:(WIDTH:%d, HEIGHT:%d, DEPTH:%d, w:%d, h:%d, d:%d)\\n\", \n\t\tWIDTH, HEIGHT, DEPTH, w, h, d);\n    float* H = new float[h*w*d];\n    change_format(H,HH,d,w,h);\n    delete []II;delete []I;delete []HH;\n\tlen = w*h*d;\n    return H;\n}\ncv::Mat fhog(const cv::Mat& input, int binSize, int nOrients, float clip, bool crop){\n    int HEIGHT = input.rows;\n    int WIDTH = input.cols;\n    int DEPTH = input.channels();\n\n    CV_Assert(DEPTH == 1);\n\n    float *II = new float[HEIGHT*WIDTH*DEPTH];\n    int count = 0;\n    for (size_t i = 0; i < HEIGHT; i++) {\n        for (size_t j = 0; j < WIDTH; j++) {\n            // Vec3b vec = image.at<Vec3b>(i,j);\n            for (size_t k = 0; k < DEPTH; k++) {\n                II[count] = input.at<uchar>(i, j) / 255.;\n                // cout<<II[count]<<endl;\n                count++;\n            }\n        }\n    }\n\n    float *I = new float[HEIGHT*WIDTH*DEPTH];\n    change_format(I,II,HEIGHT,WIDTH,DEPTH);\n    int h,w,d;\n    float* HH = fhog(I,HEIGHT,WIDTH,DEPTH,&h,&w,&d,binSize,nOrients,clip,crop);\n    if(HH == NULL){\n\t\tdelete []I;\n\t\tdelete []II;\n        cv::Mat re;\n        return re; \n    }\n\tprintf(\"fhog563:(WIDTH:%d, HEIGHT:%d, DEPTH:%d, w:%d, h:%d, d:%d)\\n\", \n\t\tWIDTH, HEIGHT, DEPTH, w, h, d);\n    float* H = new float[h*w*d];\n    change_format(H,HH,d,w,h);\n    cv::Mat fhog_feature(h,w,CV_32FC(32),H);\n\tcv::Mat out = fhog_feature.clone();\n    delete []II;delete []I;delete []HH;\n\tdelete []H;\n    return out;\n}\n"
  },
  {
    "path": "fdsst/fhogbk/fhog.h",
    "content": "#ifndef FHOG_H\n#define FHOG_H\n#include <opencv2/core/core.hpp>\n#include <boost/thread/mutex.hpp>\n//#include <cstdlib>\n#include <cmath>\n#include <cstring>\n#include \"sse.hpp\"\n#include <map>\n\n\n/**\n    Inputs:\n        float* I        - a gray or color image matrix with shape = channel x width x height\n        int *h, *w, *d  - return the size of the returned hog features\n        int binSize     -[8] spatial bin size\n        int nOrients    -[9] number of orientation bins\n        float clip      -[.2] value at which to clip histogram bins\n        bool crop       -[false] if true crop boundaries\n\n    Return:\n        float* H        - computed hog features with shape: (nOrients*3+5) x (w/binSize) x (h/binSize), if not crop\n\n    Author:\n        Sophia\n    Date:\n        2015-01-15\n**/\n\n//float* fhog(float* I,int height,int width,int channel,int *h,int *w,int *d,int binSize = 4,int nOrients = 9,float clip=0.2f,bool crop = false);\nfloat *HOGXYZ(const cv::Mat &input, int &len);\ncv::Mat fhog(const cv::Mat& input, int binSize = 4,int nOrients = 9,float clip=0.2f,bool crop = false);\n\nvoid change_format(float *des,float *source,int height,int width,int channel);\n\n\nvoid hoglog();\nfloat* acosTable(); \n#endif\n"
  },
  {
    "path": "fdsst/labdata.hpp",
    "content": "const int nClusters = 15;\nfloat data[nClusters][3] = {\n{161.317504, 127.223401, 128.609333},\n{142.922425, 128.666965, 127.532319},\n{67.879757, 127.721830, 135.903311},\n{92.705062, 129.965717, 137.399500},\n{120.172257, 128.279647, 127.036493},\n{195.470568, 127.857070, 129.345415},\n{41.257102, 130.059468, 132.675336},\n{12.014861, 129.480555, 127.064714},\n{226.567086, 127.567831, 136.345727},\n{154.664210, 131.676606, 156.481669},\n{121.180447, 137.020793, 153.433743},\n{87.042204, 137.211742, 98.614874},\n{113.809537, 106.577104, 157.818094},\n{81.083293, 170.051905, 148.904079},\n{45.015485, 138.543124, 102.402528}};"
  },
  {
    "path": "fdsst/recttools.hpp",
    "content": "/*\nAuthor: Christian Bailer\nContact address: Christian.Bailer@dfki.de\nDepartment Augmented Vision DFKI\n\n                          License Agreement\n               For Open Source Computer Vision Library\n                       (3-clause BSD License)\n\nRedistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:\n\n  * Redistributions of source code must retain the above copyright notice,\n    this list of conditions and the following disclaimer.\n\n  * Redistributions in binary form must reproduce the above copyright notice,\n    this list of conditions and the following disclaimer in the documentation\n    and/or other materials provided with the distribution.\n\n  * Neither the names of the copyright holders nor the names of the contributors\n    may be used to endorse or promote products derived from this software\n    without specific prior written permission.\n\nThis software is provided by the copyright holders and contributors \"as is\" and\nany express or implied warranties, including, but not limited to, the implied\nwarranties of merchantability and fitness for a particular purpose are disclaimed.\nIn no event shall copyright holders or contributors be liable for any direct,\nindirect, incidental, special, exemplary, or consequential damages\n(including, but not limited to, procurement of substitute goods or services;\nloss of use, data, or profits; or business interruption) however caused\nand on any theory of liability, whether in contract, strict liability,\nor tort (including negligence or otherwise) arising in any way out of\nthe use of this software, even if advised of the possibility of such damage.\n*/\n\n#pragma once\n\n//#include <cv.h>\n#include <math.h>\n\n#ifndef _OPENCV_RECTTOOLS_HPP_\n#define _OPENCV_RECTTOOLS_HPP_\n#endif\nnamespace RectTools\n{\n\ntemplate <typename t>\ninline cv::Vec<t, 2 > center(const cv::Rect_<t> &rect)\n{\n    return cv::Vec<t, 2 > (rect.x + rect.width / (t) 2, rect.y + rect.height / (t) 2);\n}\n\ntemplate <typename t>\ninline t x2(const cv::Rect_<t> &rect)\n{\n    return rect.x + rect.width;\n}\n\ntemplate <typename t>\ninline t y2(const cv::Rect_<t> &rect)\n{\n    return rect.y + rect.height;\n}\n\ntemplate <typename t>\ninline void resize(cv::Rect_<t> &rect, float scalex, float scaley = 0)\n{\n    if (!scaley)scaley = scalex;\n    rect.x -= rect.width * (scalex - 1.f) / 2.f;\n    rect.width *= scalex;\n\n    rect.y -= rect.height * (scaley - 1.f) / 2.f;\n    rect.height *= scaley;\n\n}\n\ntemplate <typename t>\ninline void limit(cv::Rect_<t> &rect, cv::Rect_<t> limit)\n{\n    if (rect.x + rect.width > limit.x + limit.width)rect.width = (limit.x + limit.width - rect.x);\n    if (rect.y + rect.height > limit.y + limit.height)rect.height = (limit.y + limit.height - rect.y);\n    if (rect.x < limit.x)\n    {\n        rect.width -= (limit.x - rect.x);\n        rect.x = limit.x;\n    }\n    if (rect.y < limit.y)\n    {\n        rect.height -= (limit.y - rect.y);\n        rect.y = limit.y;\n    }\n    if(rect.width<0)rect.width=0;\n    if(rect.height<0)rect.height=0;\n}\n\ntemplate <typename t>\ninline void limit(cv::Rect_<t> &rect, t width, t height, t x = 0, t y = 0)\n{\n    limit(rect, cv::Rect_<t > (x, y, width, height));\n}\n\ntemplate <typename t>\ninline cv::Rect getBorder(const cv::Rect_<t > &original, cv::Rect_<t > & limited)\n{\n    cv::Rect_<t > res;\n    res.x = limited.x - original.x;\n    res.y = limited.y - original.y;\n    res.width = x2(original) - x2(limited);\n    res.height = y2(original) - y2(limited);\n    assert(res.x >= 0 && res.y >= 0 && res.width >= 0 && res.height >= 0);\n    return res;\n}\n\ninline cv::Mat subwindow(const cv::Mat &in, const cv::Rect & window, int borderType = cv::BORDER_CONSTANT)\n{\n    cv::Rect cutWindow = window;\n    RectTools::limit(cutWindow, in.cols, in.rows);\n    if (cutWindow.height <= 0 || cutWindow.width <= 0)assert(0); //return cv::Mat(window.height,window.width,in.type(),0) ;\n    cv::Rect border = RectTools::getBorder(window, cutWindow);\n    cv::Mat res = in(cutWindow);\n\n    if (border != cv::Rect(0, 0, 0, 0))\n    {\n        cv::copyMakeBorder(res, res, border.y, border.height, border.x, border.width, borderType);\n    }\n    return res;\n}\n\n\ninline void cutOutsize(float &num, int limit)\n{\n  if(num < 0)\n    num = 0;\n  else if(num > limit - 1)\n    num = limit - 1;\n}\n\ninline cv::Mat extractImage(const cv::Mat &in, float cx, float cy, float patch_width, float patch_height)\n{\n\n    float xs_s = floor(cx) - floor(patch_width / 2);\n    RectTools::cutOutsize(xs_s, in.cols);\n\n    float xs_e = floor(cx + patch_width - 1) - floor(patch_width / 2);\n    RectTools::cutOutsize(xs_e, in.cols);\n\n    float ys_s = floor(cy) - floor(patch_height / 2);\n    RectTools::cutOutsize(ys_s, in.rows);\n\n    float ys_e = floor(cy + patch_height - 1) - floor(patch_height / 2);\n    RectTools::cutOutsize(ys_e, in.rows);\n\n    if(xs_s<0)xs_s = 0;\n    if(ys_s<0)ys_s = 0;\n    double w = xs_e - xs_s;\n    double h = ys_e - ys_s;\n    if(w < 0)w = 1;\n    if(w > in.cols-1)w = in.cols-1;\n    if(h < 0)h = 1;\n    if(h > in.rows-1)h = in.rows-1;\n    return in(cv::Rect(xs_s, ys_s, w, h));\n    //return in(cv::Rect(xs_s, ys_s, xs_e - xs_s, ys_e - ys_s));\n}\n\ninline cv::Mat getGrayImage(cv::Mat img)\n{\n    cv::cvtColor(img, img, CV_BGR2GRAY);\n    img.convertTo(img, CV_32F, 1 / 255.f);\n    return img;\n}\n\n}\n"
  },
  {
    "path": "fdsst/sse.hpp",
    "content": "/*******************************************************************************\n* Piotr's Computer Vision Matlab Toolbox      Version 3.23\n* Copyright 2014 Piotr Dollar.  [pdollar-at-gmail.com]\n* Licensed under the Simplified BSD License [see external/bsd.txt]\n*******************************************************************************/\n#ifndef _SSE_HPP_\n#define _SSE_HPP_\n#include <emmintrin.h> // SSE2:<e*.h>, SSE3:<p*.h>, SSE4:<s*.h>\nnamespace sse{\n\n#undef  MIN\n#define RETf inline __m128\n#define RETi inline __m128i\n\n// set, load and store values\nRETf SET( const float &x ) { return _mm_set1_ps(x); }\nRETf SET( float x, float y, float z, float w ) { return _mm_set_ps(x,y,z,w); }\nRETi SET( const int &x ) { return _mm_set1_epi32(x); }\nRETf LD( const float &x ) { return _mm_load_ps(&x); }\nRETf LDu( const float &x ) { return _mm_loadu_ps(&x); }\nRETf STR( float &x, const __m128 y ) { _mm_store_ps(&x,y); return y; }\nRETf STR1( float &x, const __m128 y ) { _mm_store_ss(&x,y); return y; }\nRETf STRu( float &x, const __m128 y ) { _mm_storeu_ps(&x,y); return y; }\nRETf STR( float &x, const float y ) { return STR(x,SET(y)); }\n\n// arithmetic operators\nRETi ADD( const __m128i x, const __m128i y ) { return _mm_add_epi32(x,y); }\nRETf ADD( const __m128 x, const __m128 y ) { return _mm_add_ps(x,y); }\nRETf ADD( const __m128 x, const __m128 y, const __m128 z ) {\n  return ADD(ADD(x,y),z); }\nRETf ADD( const __m128 a, const __m128 b, const __m128 c, const __m128 &d ) {\n  return ADD(ADD(ADD(a,b),c),d); }\nRETf SUB( const __m128 x, const __m128 y ) { return _mm_sub_ps(x,y); }\nRETf MUL( const __m128 x, const __m128 y ) { return _mm_mul_ps(x,y); }\nRETf MUL( const __m128 x, const float y ) { return MUL(x,SET(y)); }\nRETf MUL( const float x, const __m128 y ) { return MUL(SET(x),y); }\nRETf INC( __m128 &x, const __m128 y ) { return x = ADD(x,y); }\nRETf INC( float &x, const __m128 y ) { __m128 t=ADD(LD(x),y); return STR(x,t); }\nRETf DEC( __m128 &x, const __m128 y ) { return x = SUB(x,y); }\nRETf DEC( float &x, const __m128 y ) { __m128 t=SUB(LD(x),y); return STR(x,t); }\nRETf MIN( const __m128 x, const __m128 y ) { return _mm_min_ps(x,y); }\nRETf RCP( const __m128 x ) { return _mm_rcp_ps(x); }\nRETf RCPSQRT( const __m128 x ) { return _mm_rsqrt_ps(x); }\n\n// logical operators\nRETf AND( const __m128 x, const __m128 y ) { return _mm_and_ps(x,y); }\nRETi AND( const __m128i x, const __m128i y ) { return _mm_and_si128(x,y); }\nRETf ANDNOT( const __m128 x, const __m128 y ) { return _mm_andnot_ps(x,y); }\nRETf OR( const __m128 x, const __m128 y ) { return _mm_or_ps(x,y); }\nRETf XOR( const __m128 x, const __m128 y ) { return _mm_xor_ps(x,y); }\n\n// comparison operators\nRETf CMPGT( const __m128 x, const __m128 y ) { return _mm_cmpgt_ps(x,y); }\nRETf CMPLT( const __m128 x, const __m128 y ) { return _mm_cmplt_ps(x,y); }\nRETi CMPGT( const __m128i x, const __m128i y ) { return _mm_cmpgt_epi32(x,y); }\nRETi CMPLT( const __m128i x, const __m128i y ) { return _mm_cmplt_epi32(x,y); }\n\n// conversion operators\nRETf CVT( const __m128i x ) { return _mm_cvtepi32_ps(x); }\nRETi CVT( const __m128 x ) { return _mm_cvttps_epi32(x); }\n\n#undef RETf\n#undef RETi\n\n}\n#endif\n"
  },
  {
    "path": "fdsst/tracker.h",
    "content": "/*\n * File:   BasicTracker.h\n * Author: Joao F. Henriques, Joao Faro, Christian Bailer\n * Contact address: henriques@isr.uc.pt, joaopfaro@gmail.com, Christian.Bailer@dfki.de \n * Instute of Systems and Robotics- University of COimbra / Department Augmented Vision DFKI \n * \n * This source code is provided for for research purposes only. For a commercial license or a different use case please contact us. \n * You are not allowed to publish the unmodified sourcecode on your own e.g. on your webpage. Please refer to the official download page instead.\n * If you want to publish a modified/extended version e.g. because you wrote a publication with a modified version of the sourcecode you need our\n * permission (Please contact us for the permission).\n * \n * We reserve the right to change the license of this sourcecode anytime to BSD, GPL or LGPL. \n * By using the sourcecode you agree to possible restrictions and requirements of these three license models so that the license can be changed\n * anytime without you knowledge. \n */\n\n\n\n#pragma once\n\n#include <opencv2/opencv.hpp>\n#include <string>\nclass Tracker\n{\npublic:\n    Tracker()  {}\n   virtual  ~Tracker() { }\n\n    virtual void init(const cv::Rect &roi, cv::Mat image) = 0;\n    virtual cv::Rect  update( cv::Mat image)=0;\n\n\nprotected:\n    cv::Rect_<float> _roi;\n};\n\n\n\n"
  },
  {
    "path": "lmake.sh",
    "content": "#!/bin/bash\n\nfunction getbazel(){\n\tLINE=`readlink -f /home/$USER/code1/tensorflow-1.4.0-rc0/bazel-bin/`\n\n\tPOS1=\"_bazel_$USER/\"\n\tSTR=${LINE##*$POS1}\n\n\tBAZEL=${STR:0:32}\n\n\techo $BAZEL\n}\n\n\n\nBAZEL=`getbazel`\n\n\n\n\nIINCLUDE=\"-I/home/$USER/code/test/pp/opencvlib/include -I/usr/local/include -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/eigen_archive/Eigen -I/home/$USER/code1/tbb-2018_U1/include/tbb -I/home/$USER/code1/tbb-2018_U1/include\"\n\n\nLLIBPATH=\"-L/home/$USER/code/test/pp/opencvlib/lib -L/usr/local/lib -L/home/$USER/code1/DS/deepsort/FeatureGetter -L/home/$USER/code1/tbb-2018_U1/build/linux_intel64_gcc_cc5.4.0_libc2.17_kernel3.10.0_release \"\n\nrm libDS.so -rf\n\n\nfunction BOPENMP(){\n\tLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz  -lopencv_highguixyz -lFeatureGetter -lboost_system -lglog\"\n\tg++ --std=c++14 -fPIC -shared -O3 -fopenmp -DUDL -o libDS.so $IINCLUDE $LLIBPATH  deepsort/munkres/munkres.cpp deepsort/munkres/adapters/adapter.cpp deepsort/munkres/adapters/boostmatrixadapter.cpp  NT.cpp fdsst/fdssttracker.cpp fdsst/fhog.cpp Main.cpp $LLIBS\n}\n\n\nfunction BTBB(){\n\tLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz -lopencv_highguixyz -lFeatureGetter -lboost_system -lglog -ltbb\"\n\tg++ --std=c++14 -fPIC -shared -DUSETBB -o libDS.so $IINCLUDE $LLIBPATH deepsort/munkres/munkres.cpp deepsort/munkres/adapters/adapter.cpp deepsort/munkres/adapters/boostmatrixadapter.cpp  NT.cpp Main.cpp $LLIBS\n}\n\n\nfunction BOPENMPHOG(){\n\tLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz  -lopencv_highguixyz  -lboost_system -lglog\"\n\tg++ --std=c++14  -fPIC -shared -O3 -fopenmp -o libDS.so $IINCLUDE $LLIBPATH  deepsort/munkres/munkres.cpp deepsort/munkres/adapters/adapter.cpp deepsort/munkres/adapters/boostmatrixadapter.cpp  NT.cpp fdsst/fdssttracker.cpp fdsst/fhog.cpp Main.cpp $LLIBS\n}\n\nBOPENMPHOG\n\n\n\n\n"
  },
  {
    "path": "log.txt",
    "content": "hahahah0\nhahahah1\nhahahah2\nprocess image cost time:2\n_create_network\nbatch_norm_fn\nbatch_norm_fn\n('feature dimensionality: ', 128)\nbatch_norm_fn\nhahahah\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:663\n(incpp)call encode cost time:tmd-tmc:746954\n1----rcs.size():0[tm0:1507941579516057,tm1:1507941579521742,tm2:1507941579521742(0),tm3:1507941579521750(8),tm4:1507941579521751(9)][tm4-tm0]:5694\nfinish 1 frame\n2----rcs.size():0[tm0:1507941579582337,tm1:1507941579583596,tm2:1507941579583596(0),tm3:1507941579583599(3),tm4:1507941579583599(3)][tm4-tm0]:1262\nfinish 2 frame\n3----rcs.size():0[tm0:1507941579626888,tm1:1507941579627544,tm2:1507941579627544(0),tm3:1507941579627546(2),tm4:1507941579627547(3)][tm4-tm0]:659\nfinish 3 frame\n4----rcs.size():0[tm0:1507941579660254,tm1:1507941579661845,tm2:1507941579661845(0),tm3:1507941579661848(3),tm4:1507941579661848(3)][tm4-tm0]:1594\nfinish 4 frame\n5----rcs.size():0[tm0:1507941579691629,tm1:1507941579693068,tm2:1507941579693068(0),tm3:1507941579693071(3),tm4:1507941579693071(3)][tm4-tm0]:1442\nfinish 5 frame\n6----rcs.size():0[tm0:1507941579722306,tm1:1507941579722873,tm2:1507941579722873(0),tm3:1507941579722875(2),tm4:1507941579722875(2)][tm4-tm0]:569\nfinish 6 frame\n7----rcs.size():0[tm0:1507941579767825,tm1:1507941579768390,tm2:1507941579768390(0),tm3:1507941579768392(2),tm4:1507941579768392(2)][tm4-tm0]:567\nfinish 7 frame\n8----rcs.size():0[tm0:1507941579802545,tm1:1507941579803098,tm2:1507941579803098(0),tm3:1507941579803100(2),tm4:1507941579803100(2)][tm4-tm0]:555\nfinish 8 frame\n9----rcs.size():0[tm0:1507941579841817,tm1:1507941579842926,tm2:1507941579842926(0),tm3:1507941579842929(3),tm4:1507941579842930(4)][tm4-tm0]:1113\nfinish 9 frame\n10----rcs.size():0[tm0:1507941579875686,tm1:1507941579876242,tm2:1507941579876242(0),tm3:1507941579876244(2),tm4:1507941579876244(2)][tm4-tm0]:558\nfinish 10 frame\n11----rcs.size():0[tm0:1507941579910491,tm1:1507941579911050,tm2:1507941579911050(0),tm3:1507941579911052(2),tm4:1507941579911052(2)][tm4-tm0]:561\nfinish 11 frame\n12----rcs.size():0[tm0:1507941579945090,tm1:1507941579945653,tm2:1507941579945653(0),tm3:1507941579945656(3),tm4:1507941579945656(3)][tm4-tm0]:566\nfinish 12 frame\n13----rcs.size():0[tm0:1507941579980565,tm1:1507941579981124,tm2:1507941579981124(0),tm3:1507941579981126(2),tm4:1507941579981126(2)][tm4-tm0]:561\nfinish 13 frame\n14----rcs.size():0[tm0:1507941580014434,tm1:1507941580014996,tm2:1507941580014996(0),tm3:1507941580014998(2),tm4:1507941580014999(3)][tm4-tm0]:565\nfinish 14 frame\n15----rcs.size():0[tm0:1507941580050273,tm1:1507941580050850,tm2:1507941580050850(0),tm3:1507941580050852(2),tm4:1507941580050852(2)][tm4-tm0]:579\nfinish 15 frame\n16----rcs.size():0[tm0:1507941580084899,tm1:1507941580085458,tm2:1507941580085458(0),tm3:1507941580085460(2),tm4:1507941580085460(2)][tm4-tm0]:561\nfinish 16 frame\n17----rcs.size():0[tm0:1507941580120307,tm1:1507941580121070,tm2:1507941580121070(0),tm3:1507941580121072(2),tm4:1507941580121072(2)][tm4-tm0]:765\nfinish 17 frame\n18----rcs.size():0[tm0:1507941580155238,tm1:1507941580155818,tm2:1507941580155819(1),tm3:1507941580155821(3),tm4:1507941580155821(3)][tm4-tm0]:583\nfinish 18 frame\n19----rcs.size():0[tm0:1507941580190508,tm1:1507941580191081,tm2:1507941580191081(0),tm3:1507941580191083(2),tm4:1507941580191084(3)][tm4-tm0]:576\nfinish 19 frame\n20----rcs.size():0[tm0:1507941580226029,tm1:1507941580226572,tm2:1507941580226572(0),tm3:1507941580226574(2),tm4:1507941580226574(2)][tm4-tm0]:545\nfinish 20 frame\n21----rcs.size():0[tm0:1507941580261572,tm1:1507941580262157,tm2:1507941580262157(0),tm3:1507941580262159(2),tm4:1507941580262160(3)][tm4-tm0]:588\nfinish 21 frame\n22----rcs.size():0[tm0:1507941580296627,tm1:1507941580297170,tm2:1507941580297170(0),tm3:1507941580297173(3),tm4:1507941580297173(3)][tm4-tm0]:546\nfinish 22 frame\n23----rcs.size():0[tm0:1507941580333016,tm1:1507941580333590,tm2:1507941580333590(0),tm3:1507941580333592(2),tm4:1507941580333593(3)][tm4-tm0]:577\nfinish 23 frame\n24----rcs.size():0[tm0:1507941580369969,tm1:1507941580370886,tm2:1507941580370886(0),tm3:1507941580370888(2),tm4:1507941580370888(2)][tm4-tm0]:919\nfinish 24 frame\n25----rcs.size():0[tm0:1507941580406745,tm1:1507941580407404,tm2:1507941580407404(0),tm3:1507941580407406(2),tm4:1507941580407406(2)][tm4-tm0]:661\nfinish 25 frame\n26----rcs.size():0[tm0:1507941580442233,tm1:1507941580442797,tm2:1507941580442797(0),tm3:1507941580442799(2),tm4:1507941580442800(3)][tm4-tm0]:567\nfinish 26 frame\n27----rcs.size():0[tm0:1507941580476649,tm1:1507941580477212,tm2:1507941580477212(0),tm3:1507941580477214(2),tm4:1507941580477214(2)][tm4-tm0]:565\nfinish 27 frame\n28----rcs.size():0[tm0:1507941580511822,tm1:1507941580512381,tm2:1507941580512381(0),tm3:1507941580512383(2),tm4:1507941580512383(2)][tm4-tm0]:561\nfinish 28 frame\n29----rcs.size():0[tm0:1507941580546700,tm1:1507941580547283,tm2:1507941580547283(0),tm3:1507941580547285(2),tm4:1507941580547286(3)][tm4-tm0]:586\nfinish 29 frame\n30----rcs.size():0[tm0:1507941580582040,tm1:1507941580582640,tm2:1507941580582640(0),tm3:1507941580582642(2),tm4:1507941580582643(3)][tm4-tm0]:603\nfinish 30 frame\n31----rcs.size():0[tm0:1507941580616801,tm1:1507941580617361,tm2:1507941580617361(0),tm3:1507941580617363(2),tm4:1507941580617363(2)][tm4-tm0]:562\nfinish 31 frame\n32----rcs.size():0[tm0:1507941580651990,tm1:1507941580652536,tm2:1507941580652537(1),tm3:1507941580652539(3),tm4:1507941580652539(3)][tm4-tm0]:549\nfinish 32 frame\n33----rcs.size():0[tm0:1507941580687327,tm1:1507941580688055,tm2:1507941580688055(0),tm3:1507941580688057(2),tm4:1507941580688058(3)][tm4-tm0]:731\nfinish 33 frame\n34----rcs.size():0[tm0:1507941580723593,tm1:1507941580724220,tm2:1507941580724220(0),tm3:1507941580724222(2),tm4:1507941580724223(3)][tm4-tm0]:630\nfinish 34 frame\n35----rcs.size():0[tm0:1507941580760430,tm1:1507941580761089,tm2:1507941580761089(0),tm3:1507941580761091(2),tm4:1507941580761091(2)][tm4-tm0]:661\nfinish 35 frame\n36----rcs.size():0[tm0:1507941580796666,tm1:1507941580797318,tm2:1507941580797318(0),tm3:1507941580797320(2),tm4:1507941580797320(2)][tm4-tm0]:654\nfinish 36 frame\n37----rcs.size():0[tm0:1507941580832836,tm1:1507941580833362,tm2:1507941580833362(0),tm3:1507941580833364(2),tm4:1507941580833364(2)][tm4-tm0]:528\nfinish 37 frame\n38----rcs.size():0[tm0:1507941580870631,tm1:1507941580871316,tm2:1507941580871316(0),tm3:1507941580871319(3),tm4:1507941580871319(3)][tm4-tm0]:688\nfinish 38 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4224\n39----rcs.size():1[tm0:1507941580906720,tm1:1507941580907309,tm2:1507941580911575(4266),tm3:1507941580911605(4296),tm4:1507941580911605(4296)][tm4-tm0]:4885\nfinish 39 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4021\n40----rcs.size():1[tm0:1507941580947058,tm1:1507941580947658,tm2:1507941580951701(4043),tm3:1507941580951734(4076),tm4:1507941580951734(4076)][tm4-tm0]:4676\nfinish 40 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4102\n41----rcs.size():1[tm0:1507941580987778,tm1:1507941580988406,tm2:1507941580992531(4125),tm3:1507941580992564(4158),tm4:1507941580992599(4193)][tm4-tm0]:4821\nfinish 41 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3990\n42----rcs.size():1[tm0:1507941581024416,tm1:1507941581025025,tm2:1507941581029037(4012),tm3:1507941581029062(4037),tm4:1507941581029069(4044)][tm4-tm0]:4653\nfinish 42 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3931\n43----rcs.size():1[tm0:1507941581063197,tm1:1507941581063849,tm2:1507941581067802(3953),tm3:1507941581067830(3981),tm4:1507941581067842(3993)][tm4-tm0]:4645\nfinish 43 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4190\n44----rcs.size():1[tm0:1507941581102975,tm1:1507941581103790,tm2:1507941581108005(4215),tm3:1507941581108024(4234),tm4:1507941581108032(4242)][tm4-tm0]:5057\nfinish 44 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4052\n45----rcs.size():1[tm0:1507941581147020,tm1:1507941581147633,tm2:1507941581151707(4074),tm3:1507941581151727(4094),tm4:1507941581151733(4100)][tm4-tm0]:4713\nfinish 45 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4015\n46----rcs.size():1[tm0:1507941581188007,tm1:1507941581188661,tm2:1507941581192698(4037),tm3:1507941581192718(4057),tm4:1507941581192724(4063)][tm4-tm0]:4717\nfinish 46 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4031\n47----rcs.size():1[tm0:1507941581232123,tm1:1507941581232662,tm2:1507941581236733(4071),tm3:1507941581236754(4092),tm4:1507941581236760(4098)][tm4-tm0]:4637\nfinish 47 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4134\n48----rcs.size():1[tm0:1507941581275775,tm1:1507941581276410,tm2:1507941581280584(4174),tm3:1507941581280605(4195),tm4:1507941581280611(4201)][tm4-tm0]:4836\nfinish 48 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4242\n49----rcs.size():1[tm0:1507941581318675,tm1:1507941581319309,tm2:1507941581323575(4266),tm3:1507941581323612(4303),tm4:1507941581323620(4311)][tm4-tm0]:4945\nfinish 49 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3984\n50----rcs.size():1[tm0:1507941581362938,tm1:1507941581363589,tm2:1507941581367596(4007),tm3:1507941581367616(4027),tm4:1507941581367623(4034)][tm4-tm0]:4685\nfinish 50 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3922\n51----rcs.size():1[tm0:1507941581401487,tm1:1507941581402120,tm2:1507941581406069(3949),tm3:1507941581406090(3970),tm4:1507941581406113(3993)][tm4-tm0]:4626\nfinish 51 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4028\n52----rcs.size():1[tm0:1507941581436514,tm1:1507941581437323,tm2:1507941581441392(4069),tm3:1507941581441414(4091),tm4:1507941581441422(4099)][tm4-tm0]:4908\nfinish 52 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4030\n53----rcs.size():1[tm0:1507941581471890,tm1:1507941581472436,tm2:1507941581476489(4053),tm3:1507941581476527(4091),tm4:1507941581476533(4097)][tm4-tm0]:4643\nfinish 53 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3969\n54----rcs.size():1[tm0:1507941581507252,tm1:1507941581507839,tm2:1507941581511829(3990),tm3:1507941581511867(4028),tm4:1507941581511875(4036)][tm4-tm0]:4623\nfinish 54 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4132\n55----rcs.size():1[tm0:1507941581547626,tm1:1507941581548195,tm2:1507941581552351(4156),tm3:1507941581552374(4179),tm4:1507941581552380(4185)][tm4-tm0]:4754\nfinish 55 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4075\n56----rcs.size():1[tm0:1507941581587607,tm1:1507941581588317,tm2:1507941581592416(4099),tm3:1507941581592454(4137),tm4:1507941581592461(4144)][tm4-tm0]:4854\nfinish 56 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4011\n57----rcs.size():1[tm0:1507941581627919,tm1:1507941581628472,tm2:1507941581632507(4035),tm3:1507941581632545(4073),tm4:1507941581632553(4081)][tm4-tm0]:4634\nfinish 57 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4000\n58----rcs.size():1[tm0:1507941581668090,tm1:1507941581668680,tm2:1507941581672703(4023),tm3:1507941581672725(4045),tm4:1507941581672732(4052)][tm4-tm0]:4642\nfinish 58 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3978\n59----rcs.size():1[tm0:1507941581708392,tm1:1507941581708956,tm2:1507941581712957(4001),tm3:1507941581712995(4039),tm4:1507941581713002(4046)][tm4-tm0]:4610\nfinish 59 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4046\n60----rcs.size():1[tm0:1507941581751864,tm1:1507941581752451,tm2:1507941581756519(4068),tm3:1507941581756541(4090),tm4:1507941581756548(4097)][tm4-tm0]:4684\nfinish 60 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3912\n61----rcs.size():1[tm0:1507941581795166,tm1:1507941581795768,tm2:1507941581799703(3935),tm3:1507941581799726(3958),tm4:1507941581799732(3964)][tm4-tm0]:4566\nfinish 61 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3961\n62----rcs.size():1[tm0:1507941581833531,tm1:1507941581834058,tm2:1507941581838061(4003),tm3:1507941581838100(4042),tm4:1507941581838108(4050)][tm4-tm0]:4577\nfinish 62 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3868\n63----rcs.size():1[tm0:1507941581872285,tm1:1507941581872837,tm2:1507941581876728(3891),tm3:1507941581876752(3915),tm4:1507941581876760(3923)][tm4-tm0]:4475\nfinish 63 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:3966\n64----rcs.size():1[tm0:1507941581915436,tm1:1507941581916022,tm2:1507941581920011(3989),tm3:1507941581920050(4028),tm4:1507941581920056(4034)][tm4-tm0]:4620\nfinish 64 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4032\n65----rcs.size():1[tm0:1507941581956885,tm1:1507941581957462,tm2:1507941581961517(4055),tm3:1507941581961540(4078),tm4:1507941581961547(4085)][tm4-tm0]:4662\nfinish 65 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:3914\n66----rcs.size():1[tm0:1507941581999805,tm1:1507941582000430,tm2:1507941582004367(3937),tm3:1507941582004409(3979),tm4:1507941582004415(3985)][tm4-tm0]:4610\nfinish 66 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4008\n67----rcs.size():1[tm0:1507941582042735,tm1:1507941582043327,tm2:1507941582047377(4050),tm3:1507941582047400(4073),tm4:1507941582047423(4096)][tm4-tm0]:4688\nfinish 67 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4030\n68----rcs.size():1[tm0:1507941582082701,tm1:1507941582083268,tm2:1507941582087323(4055),tm3:1507941582087384(4116),tm4:1507941582087392(4124)][tm4-tm0]:4691\nfinish 68 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4163\n69----rcs.size():1[tm0:1507941582122592,tm1:1507941582123165,tm2:1507941582127352(4187),tm3:1507941582127377(4212),tm4:1507941582127383(4218)][tm4-tm0]:4791\nfinish 69 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4069\n70----rcs.size():1[tm0:1507941582162706,tm1:1507941582163374,tm2:1507941582167466(4092),tm3:1507941582167492(4118),tm4:1507941582167516(4142)][tm4-tm0]:4810\nfinish 70 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4491\n71----rcs.size():1[tm0:1507941582202440,tm1:1507941582203042,tm2:1507941582207575(4533),tm3:1507941582207617(4575),tm4:1507941582207624(4582)][tm4-tm0]:5184\nfinish 71 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4243\n72----rcs.size():1[tm0:1507941582242646,tm1:1507941582243312,tm2:1507941582247578(4266),tm3:1507941582247620(4308),tm4:1507941582247643(4331)][tm4-tm0]:4997\nfinish 72 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4293\n73----rcs.size():1[tm0:1507941582286045,tm1:1507941582286898,tm2:1507941582291218(4320),tm3:1507941582291253(4355),tm4:1507941582291262(4364)][tm4-tm0]:5217\nfinish 73 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:203\n(incpp)call encode cost time:tmd-tmc:203288\n74----rcs.size():2[tm0:1507941582330114,tm1:1507941582330662,tm2:1507941582533983(203321),tm3:1507941582534045(203383),tm4:1507941582534053(203391)]****[tm4-tm0]:203939\nfinish 74 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5493\n75----rcs.size():2[tm0:1507941582565199,tm1:1507941582565835,tm2:1507941582571361(5526),tm3:1507941582571412(5577),tm4:1507941582571427(5592)][tm4-tm0]:6228\nfinish 75 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5675\n76----rcs.size():2[tm0:1507941582602100,tm1:1507941582602685,tm2:1507941582608393(5708),tm3:1507941582608446(5761),tm4:1507941582608484(5799)][tm4-tm0]:6384\nfinish 76 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5456\n77----rcs.size():2[tm0:1507941582641049,tm1:1507941582641669,tm2:1507941582647158(5489),tm3:1507941582647255(5586),tm4:1507941582647266(5597)][tm4-tm0]:6217\nfinish 77 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5445\n78----rcs.size():2[tm0:1507941582679393,tm1:1507941582680005,tm2:1507941582685482(5477),tm3:1507941582685538(5533),tm4:1507941582685548(5543)][tm4-tm0]:6155\nfinish 78 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:5673\n79----rcs.size():2[tm0:1507941582720103,tm1:1507941582720826,tm2:1507941582726565(5739),tm3:1507941582726639(5813),tm4:1507941582726665(5839)][tm4-tm0]:6562\nfinish 79 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5494\n80----rcs.size():2[tm0:1507941582760867,tm1:1507941582761564,tm2:1507941582767092(5528),tm3:1507941582767167(5603),tm4:1507941582767179(5615)][tm4-tm0]:6312\nfinish 80 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5620\n81----rcs.size():2[tm0:1507941582801802,tm1:1507941582802427,tm2:1507941582808079(5652),tm3:1507941582808134(5707),tm4:1507941582808170(5743)][tm4-tm0]:6368\nfinish 81 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5499\n82----rcs.size():2[tm0:1507941582839278,tm1:1507941582839871,tm2:1507941582845405(5534),tm3:1507941582845461(5590),tm4:1507941582845483(5612)][tm4-tm0]:6205\nfinish 82 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5500\n83----rcs.size():2[tm0:1507941582879140,tm1:1507941582879690,tm2:1507941582885235(5545),tm3:1507941582885309(5619),tm4:1507941582885318(5628)][tm4-tm0]:6178\nfinish 83 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5478\n84----rcs.size():2[tm0:1507941582921846,tm1:1507941582922408,tm2:1507941582927922(5514),tm3:1507941582927998(5590),tm4:1507941582928024(5616)][tm4-tm0]:6178\nfinish 84 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5524\n85----rcs.size():2[tm0:1507941582962767,tm1:1507941582963312,tm2:1507941582968870(5558),tm3:1507941582968944(5632),tm4:1507941582968963(5651)][tm4-tm0]:6196\nfinish 85 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5544\n86----rcs.size():2[tm0:1507941583001249,tm1:1507941583001819,tm2:1507941583007412(5593),tm3:1507941583007452(5633),tm4:1507941583007463(5644)][tm4-tm0]:6214\nfinish 86 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:5452\n87----rcs.size():2[tm0:1507941583041486,tm1:1507941583042085,tm2:1507941583047603(5518),tm3:1507941583047660(5575),tm4:1507941583047682(5597)][tm4-tm0]:6196\nfinish 87 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5305\n88----rcs.size():2[tm0:1507941583081802,tm1:1507941583082402,tm2:1507941583087740(5338),tm3:1507941583087817(5415),tm4:1507941583087839(5437)][tm4-tm0]:6037\nfinish 88 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5575\n89----rcs.size():2[tm0:1507941583127079,tm1:1507941583127611,tm2:1507941583133220(5609),tm3:1507941583133280(5669),tm4:1507941583133301(5690)][tm4-tm0]:6222\nfinish 89 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5592\n90----rcs.size():2[tm0:1507941583171527,tm1:1507941583172111,tm2:1507941583177777(5666),tm3:1507941583177837(5726),tm4:1507941583177860(5749)][tm4-tm0]:6333\nfinish 90 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5485\n91----rcs.size():2[tm0:1507941583213910,tm1:1507941583214414,tm2:1507941583219956(5542),tm3:1507941583220000(5586),tm4:1507941583220012(5598)][tm4-tm0]:6102\nfinish 91 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5617\n92----rcs.size():2[tm0:1507941583252423,tm1:1507941583253066,tm2:1507941583258790(5724),tm3:1507941583258850(5784),tm4:1507941583258876(5810)][tm4-tm0]:6453\nfinish 92 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5594\n93----rcs.size():2[tm0:1507941583292566,tm1:1507941583293128,tm2:1507941583298764(5636),tm3:1507941583298824(5696),tm4:1507941583298854(5726)][tm4-tm0]:6288\nfinish 93 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5643\n94----rcs.size():2[tm0:1507941583332578,tm1:1507941583333117,tm2:1507941583338796(5679),tm3:1507941583338838(5721),tm4:1507941583338866(5749)][tm4-tm0]:6288\nfinish 94 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5601\n95----rcs.size():2[tm0:1507941583372522,tm1:1507941583373155,tm2:1507941583378815(5660),tm3:1507941583378877(5722),tm4:1507941583378890(5735)][tm4-tm0]:6368\nfinish 95 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:5500\n96----rcs.size():2[tm0:1507941583416506,tm1:1507941583417088,tm2:1507941583422623(5535),tm3:1507941583422683(5595),tm4:1507941583422695(5607)][tm4-tm0]:6189\nfinish 96 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5440\n97----rcs.size():2[tm0:1507941583462196,tm1:1507941583462794,tm2:1507941583468268(5474),tm3:1507941583468314(5520),tm4:1507941583468324(5530)][tm4-tm0]:6128\nfinish 97 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5439\n98----rcs.size():2[tm0:1507941583501351,tm1:1507941583501917,tm2:1507941583507393(5476),tm3:1507941583507453(5536),tm4:1507941583507462(5545)][tm4-tm0]:6111\nfinish 98 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5623\n99----rcs.size():2[tm0:1507941583542848,tm1:1507941583543455,tm2:1507941583549116(5661),tm3:1507941583549224(5769),tm4:1507941583549237(5782)][tm4-tm0]:6389\nfinish 99 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:210\n(incpp)call encode cost time:tmd-tmc:210307\n100----rcs.size():3[tm0:1507941583582365,tm1:1507941583582931,tm2:1507941583793301(210370),tm3:1507941583793349(210418),tm4:1507941583793359(210428)]****[tm4-tm0]:210994\nfinish 100 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6750\n101----rcs.size():3[tm0:1507941583824625,tm1:1507941583825181,tm2:1507941583831978(6797),tm3:1507941583832034(6853),tm4:1507941583832046(6865)][tm4-tm0]:7421\nfinish 101 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6780\n102----rcs.size():3[tm0:1507941583863386,tm1:1507941583863930,tm2:1507941583870757(6827),tm3:1507941583870831(6901),tm4:1507941583870847(6917)][tm4-tm0]:7461\nfinish 102 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6954\n103----rcs.size():3[tm0:1507941583902112,tm1:1507941583902676,tm2:1507941583909677(7001),tm3:1507941583909743(7067),tm4:1507941583909775(7099)][tm4-tm0]:7663\nfinish 103 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6811\n104----rcs.size():3[tm0:1507941583941817,tm1:1507941583942389,tm2:1507941583949244(6855),tm3:1507941583949305(6916),tm4:1507941583949318(6929)][tm4-tm0]:7501\nfinish 104 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6695\n105----rcs.size():3[tm0:1507941583982409,tm1:1507941583982997,tm2:1507941583989757(6760),tm3:1507941583989815(6818),tm4:1507941583989828(6831)][tm4-tm0]:7419\nfinish 105 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6819\n106----rcs.size():3[tm0:1507941584020970,tm1:1507941584021566,tm2:1507941584028429(6863),tm3:1507941584028488(6922),tm4:1507941584028502(6936)][tm4-tm0]:7532\nfinish 106 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6824\n107----rcs.size():3[tm0:1507941584063012,tm1:1507941584063546,tm2:1507941584070429(6883),tm3:1507941584070491(6945),tm4:1507941584070506(6960)][tm4-tm0]:7494\nfinish 107 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6858\n108----rcs.size():3[tm0:1507941584101594,tm1:1507941584102108,tm2:1507941584109014(6906),tm3:1507941584109070(6962),tm4:1507941584109082(6974)][tm4-tm0]:7488\nfinish 108 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6835\n109----rcs.size():3[tm0:1507941584142466,tm1:1507941584143035,tm2:1507941584149914(6879),tm3:1507941584149973(6938),tm4:1507941584149987(6952)][tm4-tm0]:7521\nfinish 109 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6785\n110----rcs.size():3[tm0:1507941584181721,tm1:1507941584182278,tm2:1507941584189103(6825),tm3:1507941584189170(6892),tm4:1507941584189182(6904)][tm4-tm0]:7461\nfinish 110 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6694\n111----rcs.size():3[tm0:1507941584222182,tm1:1507941584222768,tm2:1507941584229511(6743),tm3:1507941584229577(6809),tm4:1507941584229593(6825)][tm4-tm0]:7411\nfinish 111 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6738\n112----rcs.size():3[tm0:1507941584261612,tm1:1507941584262216,tm2:1507941584269000(6784),tm3:1507941584269062(6846),tm4:1507941584269077(6861)][tm4-tm0]:7465\nfinish 112 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6794\n113----rcs.size():3[tm0:1507941584301240,tm1:1507941584301824,tm2:1507941584308663(6839),tm3:1507941584308725(6901),tm4:1507941584308737(6913)][tm4-tm0]:7497\nfinish 113 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6656\n114----rcs.size():3[tm0:1507941584342020,tm1:1507941584342634,tm2:1507941584349339(6705),tm3:1507941584349420(6786),tm4:1507941584349453(6819)][tm4-tm0]:7433\nfinish 114 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6980\n115----rcs.size():3[tm0:1507941584382902,tm1:1507941584383508,tm2:1507941584390537(7029),tm3:1507941584390603(7095),tm4:1507941584390640(7132)][tm4-tm0]:7738\nfinish 115 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5448\n116----rcs.size():2[tm0:1507941584422313,tm1:1507941584422839,tm2:1507941584428325(5486),tm3:1507941584428402(5563),tm4:1507941584428413(5574)][tm4-tm0]:6100\nfinish 116 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5388\n117\n117----rcs.size():2[tm0:1507941584462356,tm1:1507941584462905,tm2:1507941584468332(5427),tm3:1507941584468413(5508),tm4:1507941584468423(5518)][tm4-tm0]:6067\nfinish 117 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5589\n118----rcs.size():2[tm0:1507941584506605,tm1:1507941584507165,tm2:1507941584512794(5629),tm3:1507941584512844(5679),tm4:1507941584512871(5706)][tm4-tm0]:6266\nfinish 118 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5775\n119----rcs.size():2[tm0:1507941584551909,tm1:1507941584552509,tm2:1507941584558324(5815),tm3:1507941584558390(5881),tm4:1507941584558421(5912)][tm4-tm0]:6512\nfinish 119 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5458\n120----rcs.size():2[tm0:1507941584591838,tm1:1507941584592419,tm2:1507941584597918(5499),tm3:1507941584597980(5561),tm4:1507941584597990(5571)][tm4-tm0]:6152\nfinish 120 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5443\n121----rcs.size():2[tm0:1507941584631077,tm1:1507941584631641,tm2:1507941584637132(5491),tm3:1507941584637207(5566),tm4:1507941584637216(5575)][tm4-tm0]:6139\nfinish 121 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5446\n122----rcs.size():2[tm0:1507941584671402,tm1:1507941584671937,tm2:1507941584677425(5488),tm3:1507941584677510(5573),tm4:1507941584677520(5583)][tm4-tm0]:6118\nfinish 122 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5345\n123----rcs.size():2[tm0:1507941584711521,tm1:1507941584712051,tm2:1507941584717434(5383),tm3:1507941584717499(5448),tm4:1507941584717508(5457)][tm4-tm0]:5987\nfinish 123 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6741\n124----rcs.size():3[tm0:1507941584752302,tm1:1507941584753126,tm2:1507941584759940(6814),tm3:1507941584760041(6915),tm4:1507941584760070(6944)][tm4-tm0]:7768\nfinish 124 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6852\n125----rcs.size():3[tm0:1507941584791480,tm1:1507941584792065,tm2:1507941584798964(6899),tm3:1507941584799054(6989),tm4:1507941584799065(7000)][tm4-tm0]:7585\nfinish 125 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6822\n126----rcs.size():3[tm0:1507941584830822,tm1:1507941584831384,tm2:1507941584838261(6877),tm3:1507941584838342(6958),tm4:1507941584838355(6971)][tm4-tm0]:7533\nfinish 126 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6693\n127----rcs.size():3[tm0:1507941584870640,tm1:1507941584871283,tm2:1507941584878038(6755),tm3:1507941584878117(6834),tm4:1507941584878131(6848)][tm4-tm0]:7491\nfinish 127 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6783\n128----rcs.size():3[tm0:1507941584909940,tm1:1507941584910572,tm2:1507941584917426(6854),tm3:1507941584917505(6933),tm4:1507941584917520(6948)][tm4-tm0]:7580\nfinish 128 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6877\n129----rcs.size():3[tm0:1507941584948558,tm1:1507941584949168,tm2:1507941584956095(6927),tm3:1507941584956168(7000),tm4:1507941584956184(7016)][tm4-tm0]:7626\nfinish 129 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6717\n130----rcs.size():3[tm0:1507941584987967,tm1:1507941584988684,tm2:1507941584995455(6771),tm3:1507941584995538(6854),tm4:1507941584995554(6870)][tm4-tm0]:7587\nfinish 130 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7124\n131----rcs.size():3[tm0:1507941585035056,tm1:1507941585035674,tm2:1507941585042851(7177),tm3:1507941585042915(7241),tm4:1507941585042931(7257)][tm4-tm0]:7875\nfinish 131 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6819\n132----rcs.size():3[tm0:1507941585074127,tm1:1507941585074680,tm2:1507941585081548(6868),tm3:1507941585081631(6951),tm4:1507941585081645(6965)][tm4-tm0]:7518\nfinish 132 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6619\n133----rcs.size():3[tm0:1507941585113228,tm1:1507941585113791,tm2:1507941585120468(6677),tm3:1507941585120556(6765),tm4:1507941585120573(6782)][tm4-tm0]:7345\nfinish 133 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:5462\n134----rcs.size():2[tm0:1507941585151495,tm1:1507941585152106,tm2:1507941585157620(5514),tm3:1507941585157718(5612),tm4:1507941585157728(5622)][tm4-tm0]:6233\nfinish 134 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5484\n135----rcs.size():2[tm0:1507941585192915,tm1:1507941585193519,tm2:1507941585199045(5526),tm3:1507941585199116(5597),tm4:1507941585199129(5610)][tm4-tm0]:6214\nfinish 135 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5409\n136----rcs.size():2[tm0:1507941585232938,tm1:1507941585233550,tm2:1507941585239021(5471),tm3:1507941585239096(5546),tm4:1507941585239109(5559)][tm4-tm0]:6171\nfinish 136 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5433\n137----rcs.size():2[tm0:1507941585270107,tm1:1507941585270803,tm2:1507941585276299(5496),tm3:1507941585276391(5588),tm4:1507941585276404(5601)][tm4-tm0]:6297\nfinish 137 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5477\n138----rcs.size():2[tm0:1507941585307111,tm1:1507941585307703,tm2:1507941585313230(5527),tm3:1507941585313307(5604),tm4:1507941585313317(5614)][tm4-tm0]:6206\nfinish 138 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:5719\n139----rcs.size():2[tm0:1507941585348122,tm1:1507941585348766,tm2:1507941585354536(5770),tm3:1507941585354611(5845),tm4:1507941585354621(5855)][tm4-tm0]:6499\nfinish 139 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5441\n140----rcs.size():2[tm0:1507941585390666,tm1:1507941585391206,tm2:1507941585396721(5515),tm3:1507941585396796(5590),tm4:1507941585396809(5603)][tm4-tm0]:6143\nfinish 140 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5579\n141----rcs.size():2[tm0:1507941585436446,tm1:1507941585437142,tm2:1507941585442777(5635),tm3:1507941585442837(5695),tm4:1507941585442867(5725)][tm4-tm0]:6421\nfinish 141 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5396\n142----rcs.size():2[tm0:1507941585481910,tm1:1507941585482530,tm2:1507941585487979(5449),tm3:1507941585488074(5544),tm4:1507941585488103(5573)][tm4-tm0]:6193\nfinish 142 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5460\n143----rcs.size():2[tm0:1507941585523267,tm1:1507941585523917,tm2:1507941585529487(5570),tm3:1507941585529561(5644),tm4:1507941585529575(5658)][tm4-tm0]:6308\nfinish 143 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6865\n144----rcs.size():3[tm0:1507941585561252,tm1:1507941585561865,tm2:1507941585568818(6953),tm3:1507941585568901(7036),tm4:1507941585568915(7050)][tm4-tm0]:7663\nfinish 144 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6792\n145----rcs.size():3[tm0:1507941585600789,tm1:1507941585601401,tm2:1507941585608259(6858),tm3:1507941585608356(6955),tm4:1507941585608370(6969)][tm4-tm0]:7581\nfinish 145 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6851\n146----rcs.size():3[tm0:1507941585641778,tm1:1507941585642334,tm2:1507941585649250(6916),tm3:1507941585649333(6999),tm4:1507941585649346(7012)][tm4-tm0]:7568\nfinish 146 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:219\n(incpp)call encode cost time:tmd-tmc:220406\n147----rcs.size():4[tm0:1507941585683303,tm1:1507941585683874,tm2:1507941585904353(220479),tm3:1507941585904428(220554),tm4:1507941585904496(220622)]****[tm4-tm0]:221193\nfinish 147 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8101\n148----rcs.size():4[tm0:1507941585939899,tm1:1507941585940510,tm2:1507941585948687(8177),tm3:1507941585948767(8257),tm4:1507941585948813(8303)][tm4-tm0]:8914\nfinish 148 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8379\n149----rcs.size():4[tm0:1507941585981277,tm1:1507941585981839,tm2:1507941585990302(8463),tm3:1507941585990395(8556),tm4:1507941585990411(8572)][tm4-tm0]:9134\nfinish 149 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8241\n150----rcs.size():4[tm0:1507941586021671,tm1:1507941586022248,tm2:1507941586030568(8320),tm3:1507941586030646(8398),tm4:1507941586030666(8418)][tm4-tm0]:8995\nfinish 150 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8244\n151----rcs.size():4[tm0:1507941586060396,tm1:1507941586061106,tm2:1507941586069520(8414),tm3:1507941586069615(8509),tm4:1507941586069635(8529)][tm4-tm0]:9239\nfinish 151 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6783\n152----rcs.size():3[tm0:1507941586100904,tm1:1507941586101492,tm2:1507941586108333(6841),tm3:1507941586108431(6939),tm4:1507941586108448(6956)][tm4-tm0]:7544\nfinish 152 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7096\n153----rcs.size():3[tm0:1507941586138712,tm1:1507941586139307,tm2:1507941586146468(7161),tm3:1507941586146552(7245),tm4:1507941586146591(7284)][tm4-tm0]:7879\nfinish 153 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:6765\n154----rcs.size():3[tm0:1507941586177252,tm1:1507941586177903,tm2:1507941586184736(6833),tm3:1507941586184830(6927),tm4:1507941586184845(6942)][tm4-tm0]:7593\nfinish 154 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8112\n155----rcs.size():4[tm0:1507941586223487,tm1:1507941586224097,tm2:1507941586232295(8198),tm3:1507941586232409(8312),tm4:1507941586232425(8328)][tm4-tm0]:8938\nfinish 155 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:233\n(incpp)call encode cost time:tmd-tmc:233545\n156----rcs.size():5[tm0:1507941586262921,tm1:1507941586263601,tm2:1507941586497247(233646),tm3:1507941586497350(233749),tm4:1507941586497419(233818)]****[tm4-tm0]:234498\nfinish 156 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9453\n157----rcs.size():5[tm0:1507941586531182,tm1:1507941586531839,tm2:1507941586541396(9557),tm3:1507941586541497(9658),tm4:1507941586541521(9682)][tm4-tm0]:10339\nfinish 157 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9666\n158----rcs.size():5[tm0:1507941586571530,tm1:1507941586572098,tm2:1507941586581863(9765),tm3:1507941586581954(9856),tm4:1507941586581971(9873)][tm4-tm0]:10441\nfinish 158 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9312\n159----rcs.size():5[tm0:1507941586611945,tm1:1507941586612528,tm2:1507941586621957(9429),tm3:1507941586622064(9536),tm4:1507941586622130(9602)][tm4-tm0]:10185\nfinish 159 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9524\n160----rcs.size():5[tm0:1507941586651939,tm1:1507941586652748,tm2:1507941586662396(9648),tm3:1507941586662518(9770),tm4:1507941586662582(9834)][tm4-tm0]:10643\nfinish 160 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9255\n161----rcs.size():5[tm0:1507941586693205,tm1:1507941586693803,tm2:1507941586703173(9370),tm3:1507941586703276(9473),tm4:1507941586703302(9499)][tm4-tm0]:10097\nfinish 161 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9553\n162----rcs.size():5[tm0:1507941586733277,tm1:1507941586733825,tm2:1507941586743478(9653),tm3:1507941586743593(9768),tm4:1507941586743617(9792)][tm4-tm0]:10340\nfinish 162 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9514\n163----rcs.size():5[tm0:1507941586777792,tm1:1507941586778381,tm2:1507941586788000(9619),tm3:1507941586788121(9740),tm4:1507941586788172(9791)][tm4-tm0]:10380\nfinish 163 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9504\n164----rcs.size():5[tm0:1507941586821820,tm1:1507941586822371,tm2:1507941586831984(9613),tm3:1507941586832122(9751),tm4:1507941586832158(9787)][tm4-tm0]:10338\nfinish 164 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9328\n165----rcs.size():5[tm0:1507941586862809,tm1:1507941586863452,tm2:1507941586872892(9440),tm3:1507941586873032(9580),tm4:1507941586873058(9606)][tm4-tm0]:10249\nfinish 165 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9658\n166----rcs.size():5[tm0:1507941586903894,tm1:1507941586904580,tm2:1507941586914352(9772),tm3:1507941586914494(9914),tm4:1507941586914560(9980)][tm4-tm0]:10666\nfinish 166 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9530\n167----rcs.size():5[tm0:1507941586945713,tm1:1507941586946269,tm2:1507941586955911(9642),tm3:1507941586956053(9784),tm4:1507941586956081(9812)][tm4-tm0]:10368\nfinish 167 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9651\n168----rcs.size():5[tm0:1507941586986802,tm1:1507941586987472,tm2:1507941586997238(9766),tm3:1507941586997392(9920),tm4:1507941586997419(9947)][tm4-tm0]:10617\nfinish 168 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9641\n169----rcs.size():5[tm0:1507941587033249,tm1:1507941587033869,tm2:1507941587043647(9778),tm3:1507941587043774(9905),tm4:1507941587043817(9948)][tm4-tm0]:10568\nfinish 169 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9706\n170----rcs.size():5[tm0:1507941587074814,tm1:1507941587075460,tm2:1507941587085286(9826),tm3:1507941587085416(9956),tm4:1507941587085442(9982)][tm4-tm0]:10628\nfinish 170 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9465\n171----rcs.size():5[tm0:1507941587116334,tm1:1507941587116933,tm2:1507941587126516(9583),tm3:1507941587126662(9729),tm4:1507941587126687(9754)][tm4-tm0]:10353\nfinish 171 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9559\n172----rcs.size():5[tm0:1507941587157876,tm1:1507941587158438,tm2:1507941587168121(9683),tm3:1507941587168261(9823),tm4:1507941587168287(9849)][tm4-tm0]:10411\nfinish 172 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9549\n173----rcs.size():5[tm0:1507941587206996,tm1:1507941587207610,tm2:1507941587217283(9673),tm3:1507941587217430(9820),tm4:1507941587217457(9847)][tm4-tm0]:10461\nfinish 173 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9620\n174----rcs.size():5[tm0:1507941587251708,tm1:1507941587252601,tm2:1507941587262384(9783),tm3:1507941587262536(9935),tm4:1507941587262565(9964)][tm4-tm0]:10857\nfinish 174 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9513\n175----rcs.size():5[tm0:1507941587293855,tm1:1507941587294484,tm2:1507941587304134(9650),tm3:1507941587304306(9822),tm4:1507941587304327(9843)][tm4-tm0]:10472\nfinish 175 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9467\n176----rcs.size():5[tm0:1507941587338813,tm1:1507941587339388,tm2:1507941587348981(9593),tm3:1507941587349129(9741),tm4:1507941587349169(9781)][tm4-tm0]:10356\nfinish 176 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9615\n177----rcs.size():5[tm0:1507941587381869,tm1:1507941587382462,tm2:1507941587392204(9742),tm3:1507941587392320(9858),tm4:1507941587392340(9878)][tm4-tm0]:10471\nfinish 177 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9708\n178----rcs.size():5[tm0:1507941587422943,tm1:1507941587423517,tm2:1507941587433372(9855),tm3:1507941587433522(10005),tm4:1507941587433541(10024)][tm4-tm0]:10598\nfinish 178 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9648\n179----rcs.size():5[tm0:1507941587464601,tm1:1507941587465176,tm2:1507941587474974(9798),tm3:1507941587475109(9933),tm4:1507941587475173(9997)][tm4-tm0]:10572\nfinish 179 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9684\n180----rcs.size():5[tm0:1507941587509275,tm1:1507941587509925,tm2:1507941587519757(9832),tm3:1507941587519890(9965),tm4:1507941587519924(9999)][tm4-tm0]:10649\nfinish 180 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9837\n181----rcs.size():5[tm0:1507941587551570,tm1:1507941587552270,tm2:1507941587562424(10154),tm3:1507941587562568(10298),tm4:1507941587562601(10331)][tm4-tm0]:11031\nfinish 181 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9709\n182----rcs.size():5[tm0:1507941587593409,tm1:1507941587594146,tm2:1507941587604002(9856),tm3:1507941587604158(10012),tm4:1507941587604177(10031)][tm4-tm0]:10768\nfinish 182 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9782\n183----rcs.size():5[tm0:1507941587633815,tm1:1507941587634404,tm2:1507941587644342(9938),tm3:1507941587644490(10086),tm4:1507941587644525(10121)][tm4-tm0]:10710\nfinish 183 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:247\n(incpp)call encode cost time:tmd-tmc:247581\n184----rcs.size():6[tm0:1507941587675284,tm1:1507941587675855,tm2:1507941587923624(247769),tm3:1507941587923777(247922),tm4:1507941587923809(247954)]****[tm4-tm0]:248525\nfinish 184 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11347\n185----rcs.size():6[tm0:1507941587954948,tm1:1507941587955548,tm2:1507941587967091(11543),tm3:1507941587967256(11708),tm4:1507941587967286(11738)][tm4-tm0]:12338\nfinish 185 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11348\n186----rcs.size():6[tm0:1507941588005915,tm1:1507941588006493,tm2:1507941588018022(11529),tm3:1507941588018317(11824),tm4:1507941588018368(11875)][tm4-tm0]:12453\nfinish 186 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11630\n187----rcs.size():6[tm0:1507941588060035,tm1:1507941588060727,tm2:1507941588072541(11814),tm3:1507941588072706(11979),tm4:1507941588072743(12016)][tm4-tm0]:12708\nfinish 187 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11443\n188----rcs.size():6[tm0:1507941588103992,tm1:1507941588104608,tm2:1507941588116235(11627),tm3:1507941588116416(11808),tm4:1507941588116469(11861)][tm4-tm0]:12477\nfinish 188 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11386\n189----rcs.size():6[tm0:1507941588147225,tm1:1507941588147815,tm2:1507941588159388(11573),tm3:1507941588159558(11743),tm4:1507941588159662(11847)][tm4-tm0]:12437\nfinish 189 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11456\n190----rcs.size():6[tm0:1507941588190894,tm1:1507941588191546,tm2:1507941588203249(11703),tm3:1507941588203403(11857),tm4:1507941588203439(11893)][tm4-tm0]:12545\nfinish 190 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11714\n191----rcs.size():6[tm0:1507941588234329,tm1:1507941588234936,tm2:1507941588246854(11918),tm3:1507941588247022(12086),tm4:1507941588247059(12123)][tm4-tm0]:12730\nfinish 191 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11305\n192----rcs.size():6[tm0:1507941588280395,tm1:1507941588280982,tm2:1507941588292472(11490),tm3:1507941588292630(11648),tm4:1507941588292678(11696)][tm4-tm0]:12283\nfinish 192 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11558\n193----rcs.size():6[tm0:1507941588323759,tm1:1507941588324337,tm2:1507941588336097(11760),tm3:1507941588336253(11916),tm4:1507941588336278(11941)][tm4-tm0]:12519\nfinish 193 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11576\n194----rcs.size():6[tm0:1507941588366095,tm1:1507941588366684,tm2:1507941588378452(11768),tm3:1507941588378611(11927),tm4:1507941588378651(11967)][tm4-tm0]:12556\nfinish 194 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11474\n195----rcs.size():6[tm0:1507941588409229,tm1:1507941588409920,tm2:1507941588421597(11677),tm3:1507941588421774(11854),tm4:1507941588421816(11896)][tm4-tm0]:12587\nfinish 195 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11483\n196----rcs.size():6[tm0:1507941588453408,tm1:1507941588453989,tm2:1507941588465737(11748),tm3:1507941588465903(11914),tm4:1507941588465942(11953)][tm4-tm0]:12534\nfinish 196 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11466\n197----rcs.size():6[tm0:1507941588496243,tm1:1507941588496791,tm2:1507941588508459(11668),tm3:1507941588508628(11837),tm4:1507941588508743(11952)][tm4-tm0]:12500\nfinish 197 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11429\n198----rcs.size():6[tm0:1507941588539852,tm1:1507941588540520,tm2:1507941588552154(11634),tm3:1507941588552338(11818),tm4:1507941588552381(11861)][tm4-tm0]:12529\nfinish 198 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11772\n199----rcs.size():6[tm0:1507941588584405,tm1:1507941588585039,tm2:1507941588597066(12027),tm3:1507941588597231(12192),tm4:1507941588597257(12218)][tm4-tm0]:12852\nfinish 199 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11690\n200----rcs.size():6[tm0:1507941588627895,tm1:1507941588628428,tm2:1507941588640372(11944),tm3:1507941588640534(12106),tm4:1507941588640561(12133)][tm4-tm0]:12666\nfinish 200 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11459\n201----rcs.size():6[tm0:1507941588669222,tm1:1507941588669919,tm2:1507941588681611(11692),tm3:1507941588681809(11890),tm4:1507941588681850(11931)][tm4-tm0]:12628\nfinish 201 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11564\n202----rcs.size():6[tm0:1507941588711509,tm1:1507941588712113,tm2:1507941588723916(11803),tm3:1507941588724087(11974),tm4:1507941588724115(12002)][tm4-tm0]:12606\nfinish 202 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11527\n203----rcs.size():6[tm0:1507941588754133,tm1:1507941588754703,tm2:1507941588766470(11767),tm3:1507941588766663(11960),tm4:1507941588766688(11985)][tm4-tm0]:12555\nfinish 203 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11533\n204----rcs.size():6[tm0:1507941588795858,tm1:1507941588796503,tm2:1507941588808293(11790),tm3:1507941588808484(11981),tm4:1507941588808512(12009)][tm4-tm0]:12654\nfinish 204 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11482\n205----rcs.size():6[tm0:1507941588841592,tm1:1507941588842158,tm2:1507941588853887(11729),tm3:1507941588854086(11928),tm4:1507941588854214(12056)][tm4-tm0]:12622\nfinish 205 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11339\n206----rcs.size():6[tm0:1507941588884591,tm1:1507941588885152,tm2:1507941588896959(11807),tm3:1507941588897158(12006),tm4:1507941588897186(12034)][tm4-tm0]:12595\nfinish 206 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11686\n207----rcs.size():6[tm0:1507941588926383,tm1:1507941588926939,tm2:1507941588938903(11964),tm3:1507941588939118(12179),tm4:1507941588939315(12376)][tm4-tm0]:12932\nfinish 207 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11501\n208----rcs.size():6[tm0:1507941588969144,tm1:1507941588969816,tm2:1507941588981574(11758),tm3:1507941588981790(11974),tm4:1507941588981832(12016)][tm4-tm0]:12688\nfinish 208 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11586\n209----rcs.size():6[tm0:1507941589011465,tm1:1507941589012055,tm2:1507941589024000(11945),tm3:1507941589024219(12164),tm4:1507941589024348(12293)][tm4-tm0]:12883\nfinish 209 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:260\n(incpp)call encode cost time:tmd-tmc:261591\n210----rcs.size():7[tm0:1507941589055372,tm1:1507941589055959,tm2:1507941589317887(261928),tm3:1507941589318159(262200),tm4:1507941589318298(262339)]****[tm4-tm0]:262926\nfinish 210 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13344\n211----rcs.size():7[tm0:1507941589352160,tm1:1507941589352836,tm2:1507941589366546(13710),tm3:1507941589366771(13935),tm4:1507941589366904(14068)][tm4-tm0]:14744\nfinish 211 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13350\n212----rcs.size():7[tm0:1507941589402613,tm1:1507941589403371,tm2:1507941589417043(13672),tm3:1507941589417270(13899),tm4:1507941589417317(13946)][tm4-tm0]:14704\nfinish 212 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13188\n213----rcs.size():7[tm0:1507941589451397,tm1:1507941589452224,tm2:1507941589465823(13599),tm3:1507941589466068(13844),tm4:1507941589466113(13889)][tm4-tm0]:14716\nfinish 213 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13336\n214----rcs.size():7[tm0:1507941589498800,tm1:1507941589499406,tm2:1507941589513083(13677),tm3:1507941589513301(13895),tm4:1507941589513347(13941)][tm4-tm0]:14547\nfinish 214 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13064\n215----rcs.size():7[tm0:1507941589543017,tm1:1507941589543656,tm2:1507941589557048(13392),tm3:1507941589557307(13651),tm4:1507941589557363(13707)][tm4-tm0]:14346\nfinish 215 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13467\n216----rcs.size():7[tm0:1507941589591382,tm1:1507941589591952,tm2:1507941589605786(13834),tm3:1507941589605996(14044),tm4:1507941589606043(14091)][tm4-tm0]:14661\nfinish 216 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13119\n217----rcs.size():7[tm0:1507941589636302,tm1:1507941589636958,tm2:1507941589650541(13583),tm3:1507941589650806(13848),tm4:1507941589650857(13899)][tm4-tm0]:14555\nfinish 217 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13331\n218----rcs.size():7[tm0:1507941589680598,tm1:1507941589681219,tm2:1507941589694923(13704),tm3:1507941589695197(13978),tm4:1507941589695245(14026)][tm4-tm0]:14647\nfinish 218 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11596\n219----rcs.size():6[tm0:1507941589725330,tm1:1507941589725928,tm2:1507941589737911(11983),tm3:1507941589738150(12222),tm4:1507941589738178(12250)][tm4-tm0]:12848\nfinish 219 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12004\n220----rcs.size():6[tm0:1507941589767539,tm1:1507941589768148,tm2:1507941589780727(12579),tm3:1507941589780944(12796),tm4:1507941589781107(12959)][tm4-tm0]:13568\nfinish 220 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11825\n221----rcs.size():6[tm0:1507941589811019,tm1:1507941589811653,tm2:1507941589823816(12163),tm3:1507941589824031(12378),tm4:1507941589824075(12422)][tm4-tm0]:13056\nfinish 221 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11901\n222----rcs.size():6[tm0:1507941589854861,tm1:1507941589855521,tm2:1507941589867736(12215),tm3:1507941589867982(12461),tm4:1507941589868026(12505)][tm4-tm0]:13165\nfinish 222 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11902\n223----rcs.size():6[tm0:1507941589898958,tm1:1507941589899544,tm2:1507941589911796(12252),tm3:1507941589912030(12486),tm4:1507941589912076(12532)][tm4-tm0]:13118\nfinish 223 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11896\n224----rcs.size():6[tm0:1507941589941896,tm1:1507941589942477,tm2:1507941589954650(12173),tm3:1507941589954883(12406),tm4:1507941589954926(12449)][tm4-tm0]:13030\nfinish 224 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12019\n225----rcs.size():6[tm0:1507941589985472,tm1:1507941589986217,tm2:1507941589998698(12481),tm3:1507941589998916(12699),tm4:1507941589998967(12750)][tm4-tm0]:13495\nfinish 225 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13371\n226----rcs.size():7[tm0:1507941590029284,tm1:1507941590029916,tm2:1507941590043705(13789),tm3:1507941590043968(14052),tm4:1507941590044019(14103)][tm4-tm0]:14735\nfinish 226 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13468\n227----rcs.size():7[tm0:1507941590075468,tm1:1507941590076067,tm2:1507941590089955(13888),tm3:1507941590090219(14152),tm4:1507941590090274(14207)][tm4-tm0]:14806\nfinish 227 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13471\n228----rcs.size():7[tm0:1507941590121184,tm1:1507941590121827,tm2:1507941590135758(13931),tm3:1507941590135991(14164),tm4:1507941590136040(14213)][tm4-tm0]:14856\nfinish 228 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:13734\n229----rcs.size():7[tm0:1507941590166584,tm1:1507941590167286,tm2:1507941590181409(14123),tm3:1507941590181684(14398),tm4:1507941590181735(14449)][tm4-tm0]:15151\nfinish 229 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:224\n(incpp)call encode cost time:tmd-tmc:225897\n230----rcs.size():8[tm0:1507941590212120,tm1:1507941590212836,tm2:1507941590439116(226280),tm3:1507941590439356(226520),tm4:1507941590439410(226574)]****[tm4-tm0]:227290\nfinish 230 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14989\n231----rcs.size():8[tm0:1507941590470748,tm1:1507941590471332,tm2:1507941590486831(15499),tm3:1507941590487091(15759),tm4:1507941590487153(15821)][tm4-tm0]:16405\nfinish 231 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14807\n232----rcs.size():8[tm0:1507941590517605,tm1:1507941590518326,tm2:1507941590533823(15497),tm3:1507941590534078(15752),tm4:1507941590534132(15806)][tm4-tm0]:16527\nfinish 232 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14896\n233----rcs.size():8[tm0:1507941590564875,tm1:1507941590565474,tm2:1507941590580801(15327),tm3:1507941590581053(15579),tm4:1507941590581107(15633)][tm4-tm0]:16232\nfinish 233 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:15202\n234----rcs.size():8[tm0:1507941590611578,tm1:1507941590612242,tm2:1507941590627989(15747),tm3:1507941590628249(16007),tm4:1507941590628306(16064)][tm4-tm0]:16728\nfinish 234 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:15047\n235----rcs.size():8[tm0:1507941590658776,tm1:1507941590659356,tm2:1507941590674876(15520),tm3:1507941590675124(15768),tm4:1507941590675174(15818)][tm4-tm0]:16398\nfinish 235 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14952\n236----rcs.size():8[tm0:1507941590705761,tm1:1507941590706339,tm2:1507941590721767(15428),tm3:1507941590722046(15707),tm4:1507941590722103(15764)][tm4-tm0]:16342\nfinish 236 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:15076\n237----rcs.size():8[tm0:1507941590752514,tm1:1507941590753333,tm2:1507941590768935(15602),tm3:1507941590769193(15860),tm4:1507941590769248(15915)][tm4-tm0]:16734\nfinish 237 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:15116\n238----rcs.size():8[tm0:1507941590800341,tm1:1507941590800904,tm2:1507941590816568(15664),tm3:1507941590816831(15927),tm4:1507941590816885(15981)][tm4-tm0]:16544\nfinish 238 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12936\n239----rcs.size():7[tm0:1507941590847101,tm1:1507941590847726,tm2:1507941590860874(13148),tm3:1507941590861130(13404),tm4:1507941590861238(13512)][tm4-tm0]:14137\nfinish 239 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12909\n240----rcs.size():7[tm0:1507941590891723,tm1:1507941590892345,tm2:1507941590905458(13113),tm3:1507941590905676(13331),tm4:1507941590905718(13373)][tm4-tm0]:13995\nfinish 240 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12901\n241----rcs.size():7[tm0:1507941590936937,tm1:1507941590937547,tm2:1507941590950672(13125),tm3:1507941590950874(13327),tm4:1507941590950919(13372)][tm4-tm0]:13982\nfinish 241 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12916\n242----rcs.size():7[tm0:1507941590980971,tm1:1507941590981533,tm2:1507941590994679(13146),tm3:1507941590994891(13358),tm4:1507941590994936(13403)][tm4-tm0]:13965\nfinish 242 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12949\n243----rcs.size():7[tm0:1507941591025627,tm1:1507941591026203,tm2:1507941591039364(13161),tm3:1507941591039590(13387),tm4:1507941591039635(13432)][tm4-tm0]:14008\nfinish 243 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12846\n244----rcs.size():7[tm0:1507941591070241,tm1:1507941591070820,tm2:1507941591083900(13080),tm3:1507941591084108(13288),tm4:1507941591084177(13357)][tm4-tm0]:13936\nfinish 244 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12758\n245----rcs.size():7[tm0:1507941591114723,tm1:1507941591115325,tm2:1507941591128278(12953),tm3:1507941591128490(13165),tm4:1507941591128535(13210)][tm4-tm0]:13812\nfinish 245 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12951\n246----rcs.size():7[tm0:1507941591159582,tm1:1507941591160201,tm2:1507941591173352(13151),tm3:1507941591173567(13366),tm4:1507941591173596(13395)][tm4-tm0]:14014\nfinish 246 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12797\n247----rcs.size():7[tm0:1507941591203884,tm1:1507941591204466,tm2:1507941591217460(12994),tm3:1507941591217682(13216),tm4:1507941591217710(13244)][tm4-tm0]:13826\nfinish 247 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12980\n248----rcs.size():7[tm0:1507941591247676,tm1:1507941591248301,tm2:1507941591261506(13205),tm3:1507941591261721(13420),tm4:1507941591261765(13464)][tm4-tm0]:14089\nfinish 248 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13081\n249----rcs.size():7[tm0:1507941591294044,tm1:1507941591294660,tm2:1507941591308042(13382),tm3:1507941591308272(13612),tm4:1507941591308318(13658)][tm4-tm0]:14274\nfinish 249 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12892\n250----rcs.size():7[tm0:1507941591339798,tm1:1507941591340361,tm2:1507941591353457(13096),tm3:1507941591353675(13314),tm4:1507941591353717(13356)][tm4-tm0]:13919\nfinish 250 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13081\n251----rcs.size():7[tm0:1507941591382877,tm1:1507941591383438,tm2:1507941591396749(13311),tm3:1507941591396985(13547),tm4:1507941591397031(13593)][tm4-tm0]:14154\nfinish 251 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12993\n252----rcs.size():7[tm0:1507941591426805,tm1:1507941591427407,tm2:1507941591440625(13218),tm3:1507941591440909(13502),tm4:1507941591440956(13549)][tm4-tm0]:14151\nfinish 252 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12885\n253----rcs.size():7[tm0:1507941591470717,tm1:1507941591471307,tm2:1507941591484406(13099),tm3:1507941591484630(13323),tm4:1507941591484693(13386)][tm4-tm0]:13976\nfinish 253 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12931\n254----rcs.size():7[tm0:1507941591514710,tm1:1507941591515274,tm2:1507941591528424(13150),tm3:1507941591528656(13382),tm4:1507941591528686(13412)][tm4-tm0]:13976\nfinish 254 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12984\n255----rcs.size():7[tm0:1507941591560159,tm1:1507941591560718,tm2:1507941591573923(13205),tm3:1507941591574186(13468),tm4:1507941591574217(13499)][tm4-tm0]:14058\nfinish 255 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12850\n256----rcs.size():7[tm0:1507941591604075,tm1:1507941591604680,tm2:1507941591617750(13070),tm3:1507941591617986(13306),tm4:1507941591618025(13345)][tm4-tm0]:13950\nfinish 256 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12991\n257----rcs.size():7[tm0:1507941591647450,tm1:1507941591647992,tm2:1507941591661288(13296),tm3:1507941591661531(13539),tm4:1507941591661562(13570)][tm4-tm0]:14112\nfinish 257 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13186\n258----rcs.size():7[tm0:1507941591692010,tm1:1507941591692603,tm2:1507941591706051(13448),tm3:1507941591706323(13720),tm4:1507941591706371(13768)][tm4-tm0]:14361\nfinish 258 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13044\n259----rcs.size():7[tm0:1507941591736687,tm1:1507941591737344,tm2:1507941591750658(13314),tm3:1507941591750906(13562),tm4:1507941591750955(13611)][tm4-tm0]:14268\nfinish 259 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13072\n260----rcs.size():7[tm0:1507941591780951,tm1:1507941591781529,tm2:1507941591794925(13396),tm3:1507941591795219(13690),tm4:1507941591795271(13742)][tm4-tm0]:14320\nfinish 260 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12963\n261----rcs.size():7[tm0:1507941591825484,tm1:1507941591826010,tm2:1507941591839282(13272),tm3:1507941591839557(13547),tm4:1507941591839707(13697)][tm4-tm0]:14223\nfinish 261 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12962\n262----rcs.size():7[tm0:1507941591870153,tm1:1507941591870779,tm2:1507941591883997(13218),tm3:1507941591884276(13497),tm4:1507941591884309(13530)][tm4-tm0]:14156\nfinish 262 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13071\n263----rcs.size():7[tm0:1507941591914700,tm1:1507941591915284,tm2:1507941591928705(13421),tm3:1507941591928959(13675),tm4:1507941591929119(13835)][tm4-tm0]:14419\nfinish 263 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13063\n264----rcs.size():7[tm0:1507941591959634,tm1:1507941591960237,tm2:1507941591973600(13363),tm3:1507941591973846(13609),tm4:1507941591973879(13642)][tm4-tm0]:14245\nfinish 264 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13107\n265----rcs.size():7[tm0:1507941592004679,tm1:1507941592005291,tm2:1507941592018691(13400),tm3:1507941592018963(13672),tm4:1507941592019151(13860)][tm4-tm0]:14472\nfinish 265 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13726\n266----rcs.size():7[tm0:1507941592049366,tm1:1507941592050061,tm2:1507941592064157(14096),tm3:1507941592064411(14350),tm4:1507941592064445(14384)][tm4-tm0]:15079\nfinish 266 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:13215\n267----rcs.size():7[tm0:1507941592095203,tm1:1507941592095781,tm2:1507941592109366(13585),tm3:1507941592109657(13876),tm4:1507941592109711(13930)][tm4-tm0]:14508\nfinish 267 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13079\n268----rcs.size():7[tm0:1507941592142183,tm1:1507941592142735,tm2:1507941592156115(13380),tm3:1507941592156388(13653),tm4:1507941592156436(13701)][tm4-tm0]:14253\nfinish 268 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12948\n269----rcs.size():7[tm0:1507941592185818,tm1:1507941592186379,tm2:1507941592199647(13268),tm3:1507941592199932(13553),tm4:1507941592199983(13604)][tm4-tm0]:14165\nfinish 269 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11582\n270----rcs.size():6[tm0:1507941592233033,tm1:1507941592233625,tm2:1507941592245359(11734),tm3:1507941592245615(11990),tm4:1507941592245654(12029)][tm4-tm0]:12621\nfinish 270 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11452\n271----rcs.size():6[tm0:1507941592280158,tm1:1507941592280735,tm2:1507941592292336(11601),tm3:1507941592292536(11801),tm4:1507941592292562(11827)][tm4-tm0]:12404\nfinish 271 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11297\n272----rcs.size():6[tm0:1507941592322484,tm1:1507941592323141,tm2:1507941592334583(11442),tm3:1507941592334797(11656),tm4:1507941592334823(11682)][tm4-tm0]:12339\nfinish 272 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11235\n273----rcs.size():6[tm0:1507941592363999,tm1:1507941592364581,tm2:1507941592375967(11386),tm3:1507941592376181(11600),tm4:1507941592376211(11630)][tm4-tm0]:12212\nfinish 273 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11287\n274----rcs.size():6[tm0:1507941592405731,tm1:1507941592406294,tm2:1507941592417733(11439),tm3:1507941592417945(11651),tm4:1507941592417971(11677)][tm4-tm0]:12240\nfinish 274 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11339\n275----rcs.size():6[tm0:1507941592449457,tm1:1507941592450047,tm2:1507941592461547(11500),tm3:1507941592461735(11688),tm4:1507941592461761(11714)][tm4-tm0]:12304\nfinish 275 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11358\n276----rcs.size():6[tm0:1507941592499329,tm1:1507941592500177,tm2:1507941592511680(11503),tm3:1507941592511906(11729),tm4:1507941592512024(11847)][tm4-tm0]:12695\nfinish 276 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11374\n277----rcs.size():6[tm0:1507941592541540,tm1:1507941592542121,tm2:1507941592553654(11533),tm3:1507941592553882(11761),tm4:1507941592553996(11875)][tm4-tm0]:12456\nfinish 277 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11587\n278----rcs.size():6[tm0:1507941592584275,tm1:1507941592585053,tm2:1507941592596893(11840),tm3:1507941592597118(12065),tm4:1507941592597193(12140)][tm4-tm0]:12918\nfinish 278 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11392\n279----rcs.size():6[tm0:1507941592626747,tm1:1507941592627402,tm2:1507941592638950(11548),tm3:1507941592639206(11804),tm4:1507941592639239(11837)][tm4-tm0]:12492\nfinish 279 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11336\n280----rcs.size():6[tm0:1507941592671695,tm1:1507941592672227,tm2:1507941592683730(11503),tm3:1507941592683950(11723),tm4:1507941592684004(11777)][tm4-tm0]:12309\nfinish 280 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11809\n281----rcs.size():6[tm0:1507941592716734,tm1:1507941592717305,tm2:1507941592729359(12054),tm3:1507941592729593(12288),tm4:1507941592729641(12336)][tm4-tm0]:12907\nfinish 281 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11367\n282----rcs.size():6[tm0:1507941592763965,tm1:1507941592764518,tm2:1507941592776107(11589),tm3:1507941592776335(11817),tm4:1507941592776364(11846)][tm4-tm0]:12399\nfinish 282 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12937\n283----rcs.size():7[tm0:1507941592806518,tm1:1507941592807178,tm2:1507941592820342(13164),tm3:1507941592820642(13464),tm4:1507941592820705(13527)][tm4-tm0]:14187\nfinish 283 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12612\n284----rcs.size():7[tm0:1507941592852705,tm1:1507941592853296,tm2:1507941592866097(12801),tm3:1507941592866632(13336),tm4:1507941592866684(13388)][tm4-tm0]:13979\nfinish 284 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12920\n285----rcs.size():7[tm0:1507941592903670,tm1:1507941592904265,tm2:1507941592917404(13139),tm3:1507941592917678(13413),tm4:1507941592917709(13444)][tm4-tm0]:14039\nfinish 285 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12823\n286----rcs.size():7[tm0:1507941592949326,tm1:1507941592949906,tm2:1507941592962947(13041),tm3:1507941592963314(13408),tm4:1507941592963364(13458)][tm4-tm0]:14038\nfinish 286 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12974\n287----rcs.size():7[tm0:1507941593000982,tm1:1507941593001684,tm2:1507941593014908(13224),tm3:1507941593015177(13493),tm4:1507941593015209(13525)][tm4-tm0]:14227\nfinish 287 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12708\n288----rcs.size():7[tm0:1507941593045204,tm1:1507941593045776,tm2:1507941593058699(12923),tm3:1507941593058995(13219),tm4:1507941593059034(13258)][tm4-tm0]:13830\nfinish 288 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12802\n289----rcs.size():7[tm0:1507941593089172,tm1:1507941593089791,tm2:1507941593102873(13082),tm3:1507941593103166(13375),tm4:1507941593103215(13424)][tm4-tm0]:14043\nfinish 289 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12884\n290----rcs.size():7[tm0:1507941593138478,tm1:1507941593139075,tm2:1507941593152187(13112),tm3:1507941593152436(13361),tm4:1507941593152470(13395)][tm4-tm0]:13992\nfinish 290 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13130\n291----rcs.size():7[tm0:1507941593181804,tm1:1507941593182423,tm2:1507941593195777(13354),tm3:1507941593196040(13617),tm4:1507941593196089(13666)][tm4-tm0]:14285\nfinish 291 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:12873\n292----rcs.size():7[tm0:1507941593226120,tm1:1507941593226640,tm2:1507941593239812(13172),tm3:1507941593240076(13436),tm4:1507941593240126(13486)][tm4-tm0]:14006\nfinish 292 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11505\n293----rcs.size():6[tm0:1507941593270107,tm1:1507941593270690,tm2:1507941593282408(11718),tm3:1507941593282649(11959),tm4:1507941593282786(12096)][tm4-tm0]:12679\nfinish 293 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11798\n294----rcs.size():6[tm0:1507941593316297,tm1:1507941593316899,tm2:1507941593328906(12007),tm3:1507941593329244(12345),tm4:1507941593329390(12491)][tm4-tm0]:13093\nfinish 294 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11410\n295----rcs.size():6[tm0:1507941593360282,tm1:1507941593360931,tm2:1507941593372629(11698),tm3:1507941593372887(11956),tm4:1507941593373028(12097)][tm4-tm0]:12746\nfinish 295 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11370\n296----rcs.size():6[tm0:1507941593406339,tm1:1507941593406897,tm2:1507941593418534(11637),tm3:1507941593418842(11945),tm4:1507941593418888(11991)][tm4-tm0]:12549\nfinish 296 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11693\n297----rcs.size():6[tm0:1507941593448917,tm1:1507941593449463,tm2:1507941593461451(11988),tm3:1507941593461685(12222),tm4:1507941593461734(12271)][tm4-tm0]:12817\nfinish 297 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11585\n298----rcs.size():6[tm0:1507941593492316,tm1:1507941593492949,tm2:1507941593504833(11884),tm3:1507941593505085(12136),tm4:1507941593505134(12185)][tm4-tm0]:12818\nfinish 298 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11264\n299----rcs.size():6[tm0:1507941593537800,tm1:1507941593538514,tm2:1507941593550006(11492),tm3:1507941593550287(11773),tm4:1507941593550337(11823)][tm4-tm0]:12537\nfinish 299 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11511\n300----rcs.size():6[tm0:1507941593580044,tm1:1507941593580740,tm2:1507941593592529(11789),tm3:1507941593592818(12078),tm4:1507941593592869(12129)][tm4-tm0]:12825\nfinish 300 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11607\n301----rcs.size():6[tm0:1507941593623129,tm1:1507941593623720,tm2:1507941593635606(11886),tm3:1507941593635843(12123),tm4:1507941593635892(12172)][tm4-tm0]:12763\nfinish 301 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11625\n302----rcs.size():6[tm0:1507941593665759,tm1:1507941593666360,tm2:1507941593678217(11857),tm3:1507941593678458(12098),tm4:1507941593678503(12143)][tm4-tm0]:12744\nfinish 302 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11396\n303----rcs.size():6[tm0:1507941593708223,tm1:1507941593708825,tm2:1507941593720509(11684),tm3:1507941593720755(11930),tm4:1507941593720806(11981)][tm4-tm0]:12583\nfinish 303 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11834\n304----rcs.size():6[tm0:1507941593749989,tm1:1507941593750632,tm2:1507941593762771(12139),tm3:1507941593763032(12400),tm4:1507941593763084(12452)][tm4-tm0]:13095\nfinish 304 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11531\n305----rcs.size():6[tm0:1507941593793332,tm1:1507941593793986,tm2:1507941593805831(11845),tm3:1507941593806099(12113),tm4:1507941593806164(12178)][tm4-tm0]:12832\nfinish 305 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11709\n306----rcs.size():6[tm0:1507941593835674,tm1:1507941593836305,tm2:1507941593848283(11978),tm3:1507941593848546(12241),tm4:1507941593848599(12294)][tm4-tm0]:12925\nfinish 306 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11478\n307----rcs.size():6[tm0:1507941593880009,tm1:1507941593880709,tm2:1507941593892471(11762),tm3:1507941593892725(12016),tm4:1507941593892779(12070)][tm4-tm0]:12770\nfinish 307 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11717\n308----rcs.size():6[tm0:1507941593922125,tm1:1507941593922840,tm2:1507941593934823(11983),tm3:1507941593935089(12249),tm4:1507941593935152(12312)][tm4-tm0]:13027\nfinish 308 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:13046\n309----rcs.size():7[tm0:1507941593964446,tm1:1507941593965106,tm2:1507941593978480(13374),tm3:1507941593978759(13653),tm4:1507941593978813(13707)][tm4-tm0]:14367\nfinish 309 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12964\n310----rcs.size():7[tm0:1507941594009602,tm1:1507941594010190,tm2:1507941594023433(13243),tm3:1507941594023728(13538),tm4:1507941594023784(13594)][tm4-tm0]:14182\nfinish 310 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13015\n311----rcs.size():7[tm0:1507941594054003,tm1:1507941594054725,tm2:1507941594068035(13310),tm3:1507941594068343(13618),tm4:1507941594068400(13675)][tm4-tm0]:14397\nfinish 311 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13470\n312----rcs.size():7[tm0:1507941594099663,tm1:1507941594100223,tm2:1507941594114058(13835),tm3:1507941594114373(14150),tm4:1507941594114451(14228)][tm4-tm0]:14788\nfinish 312 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14317\n313----rcs.size():8[tm0:1507941594144052,tm1:1507941594144722,tm2:1507941594159375(14653),tm3:1507941594159674(14952),tm4:1507941594159732(15010)][tm4-tm0]:15680\nfinish 313 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14355\n314----rcs.size():8[tm0:1507941594189456,tm1:1507941594190166,tm2:1507941594204865(14699),tm3:1507941594205175(15009),tm4:1507941594205236(15070)][tm4-tm0]:15780\nfinish 314 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14264\n315----rcs.size():8[tm0:1507941594235535,tm1:1507941594236340,tm2:1507941594250950(14610),tm3:1507941594251336(14996),tm4:1507941594251399(15059)][tm4-tm0]:15864\nfinish 315 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14612\n316----rcs.size():8[tm0:1507941594281126,tm1:1507941594281714,tm2:1507941594296726(15012),tm3:1507941594297033(15319),tm4:1507941594297097(15383)][tm4-tm0]:15971\nfinish 316 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14516\n317----rcs.size():8[tm0:1507941594329046,tm1:1507941594329683,tm2:1507941594344585(14902),tm3:1507941594344903(15220),tm4:1507941594344945(15262)][tm4-tm0]:15899\nfinish 317 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14510\n318----rcs.size():8[tm0:1507941594379275,tm1:1507941594379823,tm2:1507941594394810(14987),tm3:1507941594395124(15301),tm4:1507941594395191(15368)][tm4-tm0]:15916\nfinish 318 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14497\n319----rcs.size():8[tm0:1507941594424724,tm1:1507941594425317,tm2:1507941594440235(14918),tm3:1507941594440526(15209),tm4:1507941594440567(15250)][tm4-tm0]:15843\nfinish 319 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14740\n320----rcs.size():8[tm0:1507941594470522,tm1:1507941594471055,tm2:1507941594486413(15358),tm3:1507941594486713(15658),tm4:1507941594486754(15699)][tm4-tm0]:16232\nfinish 320 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14915\n321----rcs.size():8[tm0:1507941594516024,tm1:1507941594516571,tm2:1507941594531943(15372),tm3:1507941594532254(15683),tm4:1507941594532301(15730)][tm4-tm0]:16277\nfinish 321 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14498\n322----rcs.size():8[tm0:1507941594562630,tm1:1507941594563168,tm2:1507941594578125(14957),tm3:1507941594578469(15301),tm4:1507941594578544(15376)][tm4-tm0]:15914\nfinish 322 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14648\n323----rcs.size():8[tm0:1507941594609170,tm1:1507941594609889,tm2:1507941594624989(15100),tm3:1507941594625353(15464),tm4:1507941594625422(15533)][tm4-tm0]:16252\nfinish 323 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14789\n324----rcs.size():8[tm0:1507941594655013,tm1:1507941594655706,tm2:1507941594670999(15293),tm3:1507941594671354(15648),tm4:1507941594671398(15692)][tm4-tm0]:16385\nfinish 324 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14496\n325----rcs.size():8[tm0:1507941594704087,tm1:1507941594704661,tm2:1507941594719617(14956),tm3:1507941594719938(15277),tm4:1507941594720007(15346)][tm4-tm0]:15920\nfinish 325 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14875\n326----rcs.size():8[tm0:1507941594749640,tm1:1507941594750235,tm2:1507941594765564(15329),tm3:1507941594765867(15632),tm4:1507941594765911(15676)][tm4-tm0]:16271\nfinish 326 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14720\n327----rcs.size():8[tm0:1507941594800441,tm1:1507941594801338,tm2:1507941594816654(15316),tm3:1507941594817001(15663),tm4:1507941594817069(15731)][tm4-tm0]:16628\nfinish 327 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13203\n328----rcs.size():7[tm0:1507941594846366,tm1:1507941594846917,tm2:1507941594860576(13659),tm3:1507941594860916(13999),tm4:1507941594860980(14063)][tm4-tm0]:14614\nfinish 328 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:13\n(incpp)call encode cost time:tmd-tmc:14695\n329----rcs.size():8[tm0:1507941594891140,tm1:1507941594891713,tm2:1507941594906996(15283),tm3:1507941594907359(15646),tm4:1507941594907426(15713)][tm4-tm0]:16286\nfinish 329 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:13334\n330----rcs.size():7[tm0:1507941594940734,tm1:1507941594941271,tm2:1507941594955110(13839),tm3:1507941594955473(14202),tm4:1507941594955533(14262)][tm4-tm0]:14799\nfinish 330 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:13328\n331----rcs.size():7[tm0:1507941594986968,tm1:1507941594987557,tm2:1507941595001355(13798),tm3:1507941595001699(14142),tm4:1507941595001755(14198)][tm4-tm0]:14787\nfinish 331 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12048\n332----rcs.size():6[tm0:1507941595038028,tm1:1507941595038713,tm2:1507941595051202(12489),tm3:1507941595051465(12752),tm4:1507941595051522(12809)][tm4-tm0]:13494\nfinish 332 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11996\n333----rcs.size():6[tm0:1507941595083920,tm1:1507941595084731,tm2:1507941595097268(12537),tm3:1507941595097545(12814),tm4:1507941595097602(12871)][tm4-tm0]:13682\nfinish 333 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:13485\n334----rcs.size():7[tm0:1507941595127607,tm1:1507941595128299,tm2:1507941595142318(14019),tm3:1507941595142709(14410),tm4:1507941595142772(14473)][tm4-tm0]:15165\nfinish 334 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13454\n335----rcs.size():7[tm0:1507941595177728,tm1:1507941595178340,tm2:1507941595192245(13905),tm3:1507941595192528(14188),tm4:1507941595192584(14244)][tm4-tm0]:14856\nfinish 335 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11703\n336----rcs.size():6[tm0:1507941595222083,tm1:1507941595222647,tm2:1507941595234758(12111),tm3:1507941595235039(12392),tm4:1507941595235101(12454)][tm4-tm0]:13018\nfinish 336 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13645\n337----rcs.size():7[tm0:1507941595269925,tm1:1507941595270499,tm2:1507941595284694(14195),tm3:1507941595285037(14538),tm4:1507941595285113(14614)][tm4-tm0]:15188\nfinish 337 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12486\n338----rcs.size():6[tm0:1507941595315168,tm1:1507941595315718,tm2:1507941595328746(13028),tm3:1507941595329076(13358),tm4:1507941595329131(13413)][tm4-tm0]:13963\nfinish 338 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11875\n339----rcs.size():6[tm0:1507941595359326,tm1:1507941595359885,tm2:1507941595372220(12335),tm3:1507941595372544(12659),tm4:1507941595372597(12712)][tm4-tm0]:13271\nfinish 339 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:12\n(incpp)call encode cost time:tmd-tmc:13684\n340----rcs.size():7[tm0:1507941595407976,tm1:1507941595408529,tm2:1507941595422871(14342),tm3:1507941595423233(14704),tm4:1507941595423273(14744)][tm4-tm0]:15297\nfinish 340 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11945\n341----rcs.size():6[tm0:1507941595457804,tm1:1507941595458359,tm2:1507941595470708(12349),tm3:1507941595470988(12629),tm4:1507941595471024(12665)][tm4-tm0]:13220\nfinish 341 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12160\n342----rcs.size():6[tm0:1507941595503599,tm1:1507941595504215,tm2:1507941595516879(12664),tm3:1507941595517102(12887),tm4:1507941595517179(12964)][tm4-tm0]:13580\nfinish 342 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12014\n343----rcs.size():6[tm0:1507941595551131,tm1:1507941595551787,tm2:1507941595564314(12527),tm3:1507941595564555(12768),tm4:1507941595564610(12823)][tm4-tm0]:13479\nfinish 343 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12164\n344----rcs.size():6[tm0:1507941595595166,tm1:1507941595595831,tm2:1507941595608467(12636),tm3:1507941595608712(12881),tm4:1507941595608767(12936)][tm4-tm0]:13601\nfinish 344 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12141\n345----rcs.size():6[tm0:1507941595639419,tm1:1507941595640024,tm2:1507941595652634(12610),tm3:1507941595652876(12852),tm4:1507941595653047(13023)][tm4-tm0]:13628\nfinish 345 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12159\n346----rcs.size():6[tm0:1507941595683573,tm1:1507941595684474,tm2:1507941595697264(12790),tm3:1507941595697704(13230),tm4:1507941595697766(13292)][tm4-tm0]:14193\nfinish 346 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12221\n347----rcs.size():6[tm0:1507941595730884,tm1:1507941595731426,tm2:1507941595744158(12732),tm3:1507941595744402(12976),tm4:1507941595744437(13011)][tm4-tm0]:13553\nfinish 347 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12188\n348----rcs.size():6[tm0:1507941595775308,tm1:1507941595775989,tm2:1507941595788665(12676),tm3:1507941595788907(12918),tm4:1507941595789073(13084)][tm4-tm0]:13765\nfinish 348 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12258\n349----rcs.size():6[tm0:1507941595819666,tm1:1507941595820236,tm2:1507941595832984(12748),tm3:1507941595833232(12996),tm4:1507941595833265(13029)][tm4-tm0]:13599\nfinish 349 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12154\n350----rcs.size():6[tm0:1507941595862391,tm1:1507941595862929,tm2:1507941595875611(12682),tm3:1507941595875949(13020),tm4:1507941595876123(13194)][tm4-tm0]:13732\nfinish 350 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12284\n351----rcs.size():6[tm0:1507941595904507,tm1:1507941595905091,tm2:1507941595917894(12803),tm3:1507941595918153(13062),tm4:1507941595918347(13256)][tm4-tm0]:13840\nfinish 351 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12381\n352----rcs.size():6[tm0:1507941595951398,tm1:1507941595952096,tm2:1507941595965088(12992),tm3:1507941595965467(13371),tm4:1507941595965519(13423)][tm4-tm0]:14121\nfinish 352 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12192\n353----rcs.size():6[tm0:1507941595994858,tm1:1507941595995440,tm2:1507941596008121(12681),tm3:1507941596008472(13032),tm4:1507941596008639(13199)][tm4-tm0]:13781\nfinish 353 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9634\n354----rcs.size():5[tm0:1507941596038598,tm1:1507941596039157,tm2:1507941596049070(9913),tm3:1507941596049350(10193),tm4:1507941596049390(10233)][tm4-tm0]:10792\nfinish 354 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11901\n355----rcs.size():6[tm0:1507941596082870,tm1:1507941596083468,tm2:1507941596095639(12171),tm3:1507941596095965(12497),tm4:1507941596095994(12526)][tm4-tm0]:13124\nfinish 355 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11660\n356----rcs.size():6[tm0:1507941596131463,tm1:1507941596132064,tm2:1507941596144044(11980),tm3:1507941596144381(12317),tm4:1507941596144506(12442)][tm4-tm0]:13043\nfinish 356 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11686\n357----rcs.size():6[tm0:1507941596176152,tm1:1507941596176733,tm2:1507941596188676(11943),tm3:1507941596189003(12270),tm4:1507941596189150(12417)][tm4-tm0]:12998\nfinish 357 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11674\n358----rcs.size():6[tm0:1507941596223640,tm1:1507941596224229,tm2:1507941596236202(11973),tm3:1507941596236411(12182),tm4:1507941596236458(12229)][tm4-tm0]:12818\nfinish 358 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11537\n359----rcs.size():6[tm0:1507941596271619,tm1:1507941596272178,tm2:1507941596284003(11825),tm3:1507941596284368(12190),tm4:1507941596284416(12238)][tm4-tm0]:12797\nfinish 359 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11708\n360----rcs.size():6[tm0:1507941596315018,tm1:1507941596315610,tm2:1507941596327610(12000),tm3:1507941596327814(12204),tm4:1507941596327843(12233)][tm4-tm0]:12825\nfinish 360 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11564\n361----rcs.size():6[tm0:1507941596361780,tm1:1507941596362364,tm2:1507941596374253(11889),tm3:1507941596374495(12131),tm4:1507941596374633(12269)][tm4-tm0]:12853\nfinish 361 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11743\n362----rcs.size():6[tm0:1507941596406037,tm1:1507941596406598,tm2:1507941596418645(12047),tm3:1507941596418871(12273),tm4:1507941596419009(12411)][tm4-tm0]:12972\nfinish 362 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12083\n363----rcs.size():6[tm0:1507941596448969,tm1:1507941596449530,tm2:1507941596461910(12380),tm3:1507941596462118(12588),tm4:1507941596462185(12655)][tm4-tm0]:13216\nfinish 363 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11848\n364----rcs.size():6[tm0:1507941596491639,tm1:1507941596492227,tm2:1507941596504404(12177),tm3:1507941596504631(12404),tm4:1507941596504778(12551)][tm4-tm0]:13139\nfinish 364 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11801\n365----rcs.size():6[tm0:1507941596535319,tm1:1507941596535913,tm2:1507941596548077(12164),tm3:1507941596548345(12432),tm4:1507941596548469(12556)][tm4-tm0]:13150\nfinish 365 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11989\n366----rcs.size():6[tm0:1507941596580967,tm1:1507941596581563,tm2:1507941596593873(12310),tm3:1507941596594091(12528),tm4:1507941596594195(12632)][tm4-tm0]:13228\nfinish 366 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11750\n367----rcs.size():6[tm0:1507941596624879,tm1:1507941596625550,tm2:1507941596637603(12053),tm3:1507941596637856(12306),tm4:1507941596637977(12427)][tm4-tm0]:13098\nfinish 367 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11526\n368----rcs.size():6[tm0:1507941596669504,tm1:1507941596670115,tm2:1507941596681952(11837),tm3:1507941596682205(12090),tm4:1507941596682233(12118)][tm4-tm0]:12729\nfinish 368 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11487\n369----rcs.size():6[tm0:1507941596713841,tm1:1507941596714401,tm2:1507941596726175(11774),tm3:1507941596726472(12071),tm4:1507941596726506(12105)][tm4-tm0]:12665\nfinish 369 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9485\n370----rcs.size():5[tm0:1507941596760470,tm1:1507941596760981,tm2:1507941596770664(9683),tm3:1507941596770906(9925),tm4:1507941596770996(10015)][tm4-tm0]:10526\nfinish 370 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9447\n371----rcs.size():5[tm0:1507941596801300,tm1:1507941596801977,tm2:1507941596811564(9587),tm3:1507941596811739(9762),tm4:1507941596811775(9798)][tm4-tm0]:10475\nfinish 371 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9455\n372----rcs.size():5[tm0:1507941596845619,tm1:1507941596846193,tm2:1507941596855821(9628),tm3:1507941596856027(9834),tm4:1507941596856061(9868)][tm4-tm0]:10442\nfinish 372 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9538\n373----rcs.size():5[tm0:1507941596892929,tm1:1507941596893589,tm2:1507941596903297(9708),tm3:1507941596903473(9884),tm4:1507941596903576(9987)][tm4-tm0]:10647\nfinish 373 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9703\n374----rcs.size():5[tm0:1507941596935125,tm1:1507941596935687,tm2:1507941596945540(9853),tm3:1507941596945702(10015),tm4:1507941596945796(10109)][tm4-tm0]:10671\nfinish 374 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9694\n375----rcs.size():5[tm0:1507941596976177,tm1:1507941596976799,tm2:1507941596986665(9866),tm3:1507941596986827(10028),tm4:1507941596986934(10135)][tm4-tm0]:10757\nfinish 375 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9706\n376----rcs.size():5[tm0:1507941597017295,tm1:1507941597017962,tm2:1507941597027875(9913),tm3:1507941597028038(10076),tm4:1507941597028147(10185)][tm4-tm0]:10852\nfinish 376 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9629\n377----rcs.size():5[tm0:1507941597070252,tm1:1507941597070820,tm2:1507941597080595(9775),tm3:1507941597080775(9955),tm4:1507941597080873(10053)][tm4-tm0]:10621\nfinish 377 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9728\n378----rcs.size():5[tm0:1507941597111045,tm1:1507941597111577,tm2:1507941597121512(9935),tm3:1507941597121693(10116),tm4:1507941597121794(10217)][tm4-tm0]:10749\nfinish 378 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9562\n379----rcs.size():5[tm0:1507941597152399,tm1:1507941597153017,tm2:1507941597162784(9767),tm3:1507941597162977(9960),tm4:1507941597163011(9994)][tm4-tm0]:10612\nfinish 379 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9653\n380----rcs.size():5[tm0:1507941597193834,tm1:1507941597194417,tm2:1507941597204259(9842),tm3:1507941597204573(10156),tm4:1507941597204621(10204)][tm4-tm0]:10787\nfinish 380 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9678\n381----rcs.size():5[tm0:1507941597240547,tm1:1507941597241155,tm2:1507941597250998(9843),tm3:1507941597251259(10104),tm4:1507941597251334(10179)][tm4-tm0]:10787\nfinish 381 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9675\n382----rcs.size():5[tm0:1507941597290086,tm1:1507941597290698,tm2:1507941597300635(9937),tm3:1507941597300872(10174),tm4:1507941597300925(10227)][tm4-tm0]:10839\nfinish 382 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9820\n383----rcs.size():5[tm0:1507941597332452,tm1:1507941597332983,tm2:1507941597342986(10003),tm3:1507941597343236(10253),tm4:1507941597343264(10281)][tm4-tm0]:10812\nfinish 383 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9670\n384----rcs.size():5[tm0:1507941597374400,tm1:1507941597374974,tm2:1507941597384892(9918),tm3:1507941597385072(10098),tm4:1507941597385107(10133)][tm4-tm0]:10707\nfinish 384 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9710\n385----rcs.size():5[tm0:1507941597418839,tm1:1507941597419495,tm2:1507941597429452(9957),tm3:1507941597429649(10154),tm4:1507941597429685(10190)][tm4-tm0]:10846\nfinish 385 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9496\n386----rcs.size():5[tm0:1507941597460365,tm1:1507941597460918,tm2:1507941597470666(9748),tm3:1507941597470851(9933),tm4:1507941597470888(9970)][tm4-tm0]:10523\nfinish 386 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9817\n387----rcs.size():5[tm0:1507941597502647,tm1:1507941597503258,tm2:1507941597513276(10018),tm3:1507941597513483(10225),tm4:1507941597513519(10261)][tm4-tm0]:10872\nfinish 387 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9776\n388----rcs.size():5[tm0:1507941597548136,tm1:1507941597548741,tm2:1507941597558761(10020),tm3:1507941597558947(10206),tm4:1507941597558986(10245)][tm4-tm0]:10850\nfinish 388 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9736\n389----rcs.size():5[tm0:1507941597592369,tm1:1507941597592992,tm2:1507941597602965(9973),tm3:1507941597603184(10192),tm4:1507941597603219(10227)][tm4-tm0]:10850\nfinish 389 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9801\n390----rcs.size():5[tm0:1507941597634091,tm1:1507941597634759,tm2:1507941597644788(10029),tm3:1507941597644985(10226),tm4:1507941597645025(10266)][tm4-tm0]:10934\nfinish 390 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9681\n391----rcs.size():5[tm0:1507941597680193,tm1:1507941597680781,tm2:1507941597690718(9937),tm3:1507941597690937(10156),tm4:1507941597690992(10211)][tm4-tm0]:10799\nfinish 391 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9527\n392----rcs.size():5[tm0:1507941597725643,tm1:1507941597726248,tm2:1507941597736029(9781),tm3:1507941597736306(10058),tm4:1507941597736350(10102)][tm4-tm0]:10707\nfinish 392 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11202\n393----rcs.size():6[tm0:1507941597772472,tm1:1507941597773082,tm2:1507941597784515(11433),tm3:1507941597784779(11697),tm4:1507941597784814(11732)][tm4-tm0]:12342\nfinish 393 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11479\n394----rcs.size():6[tm0:1507941597819969,tm1:1507941597820535,tm2:1507941597832294(11759),tm3:1507941597832543(12008),tm4:1507941597832571(12036)][tm4-tm0]:12602\nfinish 394 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11688\n395----rcs.size():6[tm0:1507941597863087,tm1:1507941597863627,tm2:1507941597875643(12016),tm3:1507941597875879(12252),tm4:1507941597875939(12312)][tm4-tm0]:12852\nfinish 395 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11570\n396----rcs.size():6[tm0:1507941597905954,tm1:1507941597906538,tm2:1507941597918436(11898),tm3:1507941597918641(12103),tm4:1507941597918670(12132)][tm4-tm0]:12716\nfinish 396 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11744\n397----rcs.size():6[tm0:1507941597948331,tm1:1507941597948919,tm2:1507941597960925(12006),tm3:1507941597961135(12216),tm4:1507941597961177(12258)][tm4-tm0]:12846\nfinish 397 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11807\n398----rcs.size():6[tm0:1507941597992038,tm1:1507941597992747,tm2:1507941598004826(12079),tm3:1507941598005032(12285),tm4:1507941598005080(12333)][tm4-tm0]:13042\nfinish 398 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11509\n399----rcs.size():6[tm0:1507941598039982,tm1:1507941598040534,tm2:1507941598052372(11838),tm3:1507941598052594(12060),tm4:1507941598052639(12105)][tm4-tm0]:12657\nfinish 399 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11555\n400----rcs.size():6[tm0:1507941598082903,tm1:1507941598083816,tm2:1507941598095649(11833),tm3:1507941598095878(12062),tm4:1507941598095927(12111)][tm4-tm0]:13024\nfinish 400 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11621\n401----rcs.size():6[tm0:1507941598125979,tm1:1507941598126571,tm2:1507941598138506(11935),tm3:1507941598138731(12160),tm4:1507941598138777(12206)][tm4-tm0]:12798\nfinish 401 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11696\n402----rcs.size():6[tm0:1507941598169293,tm1:1507941598169843,tm2:1507941598181922(12079),tm3:1507941598182182(12339),tm4:1507941598182213(12370)][tm4-tm0]:12920\nfinish 402 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11636\n403----rcs.size():6[tm0:1507941598213382,tm1:1507941598213990,tm2:1507941598225957(11967),tm3:1507941598226223(12233),tm4:1507941598226273(12283)][tm4-tm0]:12891\nfinish 403 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11659\n404----rcs.size():6[tm0:1507941598256472,tm1:1507941598257060,tm2:1507941598269037(11977),tm3:1507941598269291(12231),tm4:1507941598269442(12382)][tm4-tm0]:12970\nfinish 404 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11801\n405----rcs.size():6[tm0:1507941598302963,tm1:1507941598303536,tm2:1507941598315713(12177),tm3:1507941598315953(12417),tm4:1507941598316107(12571)][tm4-tm0]:13144\nfinish 405 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11808\n406----rcs.size():6[tm0:1507941598346203,tm1:1507941598346839,tm2:1507941598359033(12194),tm3:1507941598359316(12477),tm4:1507941598359349(12510)][tm4-tm0]:13146\nfinish 406 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11871\n407----rcs.size():6[tm0:1507941598390494,tm1:1507941598391084,tm2:1507941598403310(12226),tm3:1507941598403556(12472),tm4:1507941598403606(12522)][tm4-tm0]:13112\nfinish 407 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11831\n408----rcs.size():6[tm0:1507941598437195,tm1:1507941598437720,tm2:1507941598449977(12257),tm3:1507941598450249(12529),tm4:1507941598450413(12693)][tm4-tm0]:13218\nfinish 408 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11924\n409----rcs.size():6[tm0:1507941598480883,tm1:1507941598481555,tm2:1507941598493813(12258),tm3:1507941598494053(12498),tm4:1507941598494103(12548)][tm4-tm0]:13220\nfinish 409 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11873\n410----rcs.size():6[tm0:1507941598529290,tm1:1507941598529924,tm2:1507941598542200(12276),tm3:1507941598542421(12497),tm4:1507941598542470(12546)][tm4-tm0]:13180\nfinish 410 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11668\n411----rcs.size():6[tm0:1507941598575369,tm1:1507941598575942,tm2:1507941598588011(12069),tm3:1507941598588263(12321),tm4:1507941598588308(12366)][tm4-tm0]:12939\nfinish 411 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11834\n412----rcs.size():6[tm0:1507941598622865,tm1:1507941598623448,tm2:1507941598635656(12208),tm3:1507941598635911(12463),tm4:1507941598635959(12511)][tm4-tm0]:13094\nfinish 412 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11799\n413----rcs.size():6[tm0:1507941598671775,tm1:1507941598672351,tm2:1507941598684580(12229),tm3:1507941598684825(12474),tm4:1507941598684870(12519)][tm4-tm0]:13095\nfinish 413 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11723\n414----rcs.size():6[tm0:1507941598720402,tm1:1507941598720974,tm2:1507941598733107(12133),tm3:1507941598733351(12377),tm4:1507941598733383(12409)][tm4-tm0]:12981\nfinish 414 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11701\n415----rcs.size():6[tm0:1507941598769451,tm1:1507941598770082,tm2:1507941598782162(12080),tm3:1507941598782391(12309),tm4:1507941598782424(12342)][tm4-tm0]:12973\nfinish 415 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11810\n416----rcs.size():6[tm0:1507941598812488,tm1:1507941598813077,tm2:1507941598825284(12207),tm3:1507941598825533(12456),tm4:1507941598825569(12492)][tm4-tm0]:13081\nfinish 416 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11722\n417----rcs.size():6[tm0:1507941598859937,tm1:1507941598860527,tm2:1507941598872631(12104),tm3:1507941598872880(12353),tm4:1507941598872914(12387)][tm4-tm0]:12977\nfinish 417 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9937\n418----rcs.size():5[tm0:1507941598903067,tm1:1507941598903636,tm2:1507941598913902(10266),tm3:1507941598914134(10498),tm4:1507941598914169(10533)][tm4-tm0]:11102\nfinish 418 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10434\n419----rcs.size():5[tm0:1507941598948160,tm1:1507941598948767,tm2:1507941598959536(10769),tm3:1507941598959720(10953),tm4:1507941598959748(10981)][tm4-tm0]:11588\nfinish 419 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9972\n420----rcs.size():5[tm0:1507941598989950,tm1:1507941598990514,tm2:1507941599000786(10272),tm3:1507941599000970(10456),tm4:1507941599000994(10480)][tm4-tm0]:11044\nfinish 420 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10079\n421----rcs.size():5[tm0:1507941599031600,tm1:1507941599032212,tm2:1507941599042569(10357),tm3:1507941599042752(10540),tm4:1507941599042776(10564)][tm4-tm0]:11176\nfinish 421 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8218\n422----rcs.size():4[tm0:1507941599076925,tm1:1507941599077502,tm2:1507941599085835(8333),tm3:1507941599085998(8496),tm4:1507941599086016(8514)][tm4-tm0]:9091\nfinish 422 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8230\n423----rcs.size():4[tm0:1507941599126384,tm1:1507941599126967,tm2:1507941599135307(8340),tm3:1507941599135410(8443),tm4:1507941599135428(8461)][tm4-tm0]:9044\nfinish 423 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8294\n424----rcs.size():4[tm0:1507941599170340,tm1:1507941599170876,tm2:1507941599179289(8413),tm3:1507941599179409(8533),tm4:1507941599179429(8553)][tm4-tm0]:9089\nfinish 424 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9707\n425----rcs.size():5[tm0:1507941599213228,tm1:1507941599213932,tm2:1507941599223778(9846),tm3:1507941599224009(10077),tm4:1507941599224036(10104)][tm4-tm0]:10808\nfinish 425 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9616\n426----rcs.size():5[tm0:1507941599256161,tm1:1507941599256758,tm2:1507941599266540(9782),tm3:1507941599266766(10008),tm4:1507941599266791(10033)][tm4-tm0]:10630\nfinish 426 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9699\n427----rcs.size():5[tm0:1507941599301183,tm1:1507941599301785,tm2:1507941599311642(9857),tm3:1507941599311842(10057),tm4:1507941599311864(10079)][tm4-tm0]:10681\nfinish 427 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9760\n428----rcs.size():5[tm0:1507941599342674,tm1:1507941599343330,tm2:1507941599353245(9915),tm3:1507941599353379(10049),tm4:1507941599353402(10072)][tm4-tm0]:10728\nfinish 428 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9545\n429----rcs.size():5[tm0:1507941599383184,tm1:1507941599383906,tm2:1507941599393599(9693),tm3:1507941599393743(9837),tm4:1507941599393769(9863)][tm4-tm0]:10585\nfinish 429 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9687\n430----rcs.size():5[tm0:1507941599427988,tm1:1507941599428567,tm2:1507941599438401(9834),tm3:1507941599438552(9985),tm4:1507941599438582(10015)][tm4-tm0]:10594\nfinish 430 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9619\n431----rcs.size():5[tm0:1507941599479339,tm1:1507941599479887,tm2:1507941599489671(9784),tm3:1507941599489902(10015),tm4:1507941599489925(10038)][tm4-tm0]:10586\nfinish 431 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9721\n432----rcs.size():5[tm0:1507941599520837,tm1:1507941599521409,tm2:1507941599531284(9875),tm3:1507941599531432(10023),tm4:1507941599531458(10049)][tm4-tm0]:10621\nfinish 432 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9703\n433----rcs.size():5[tm0:1507941599561972,tm1:1507941599562547,tm2:1507941599572413(9866),tm3:1507941599572557(10010),tm4:1507941599572582(10035)][tm4-tm0]:10610\nfinish 433 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9644\n434----rcs.size():5[tm0:1507941599602612,tm1:1507941599603187,tm2:1507941599612993(9806),tm3:1507941599613134(9947),tm4:1507941599613186(9999)][tm4-tm0]:10574\nfinish 434 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9705\n435----rcs.size():5[tm0:1507941599643908,tm1:1507941599644617,tm2:1507941599654472(9855),tm3:1507941599654623(10006),tm4:1507941599654647(10030)][tm4-tm0]:10739\nfinish 435 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9541\n436----rcs.size():5[tm0:1507941599685279,tm1:1507941599685870,tm2:1507941599695593(9723),tm3:1507941599695771(9901),tm4:1507941599695806(9936)][tm4-tm0]:10527\nfinish 436 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9804\n437----rcs.size():5[tm0:1507941599730214,tm1:1507941599730781,tm2:1507941599740789(10008),tm3:1507941599740958(10177),tm4:1507941599741058(10277)][tm4-tm0]:10844\nfinish 437 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9678\n438----rcs.size():5[tm0:1507941599771386,tm1:1507941599772033,tm2:1507941599781920(9887),tm3:1507941599782075(10042),tm4:1507941599782096(10063)][tm4-tm0]:10710\nfinish 438 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9560\n439----rcs.size():5[tm0:1507941599812140,tm1:1507941599812727,tm2:1507941599822458(9731),tm3:1507941599822611(9884),tm4:1507941599822646(9919)][tm4-tm0]:10506\nfinish 439 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9721\n440----rcs.size():5[tm0:1507941599852884,tm1:1507941599853444,tm2:1507941599863344(9900),tm3:1507941599863509(10065),tm4:1507941599863540(10096)][tm4-tm0]:10656\nfinish 440 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9627\n441----rcs.size():5[tm0:1507941599893932,tm1:1507941599894544,tm2:1507941599904341(9797),tm3:1507941599904548(10004),tm4:1507941599904580(10036)][tm4-tm0]:10648\nfinish 441 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9715\n442----rcs.size():5[tm0:1507941599934423,tm1:1507941599935041,tm2:1507941599945015(9974),tm3:1507941599945179(10138),tm4:1507941599945212(10171)][tm4-tm0]:10789\nfinish 442 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9604\n443----rcs.size():5[tm0:1507941599976076,tm1:1507941599976707,tm2:1507941599986485(9778),tm3:1507941599986654(9947),tm4:1507941599986686(9979)][tm4-tm0]:10610\nfinish 443 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9778\n444----rcs.size():5[tm0:1507941600017260,tm1:1507941600017959,tm2:1507941600027973(10014),tm3:1507941600028134(10175),tm4:1507941600028243(10284)][tm4-tm0]:10983\nfinish 444 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9927\n445----rcs.size():5[tm0:1507941600062580,tm1:1507941600063132,tm2:1507941600073282(10150),tm3:1507941600073518(10386),tm4:1507941600073552(10420)][tm4-tm0]:10972\nfinish 445 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11393\n446----rcs.size():6[tm0:1507941600105024,tm1:1507941600105571,tm2:1507941600117219(11648),tm3:1507941600117460(11889),tm4:1507941600117500(11929)][tm4-tm0]:12476\nfinish 446 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11316\n447----rcs.size():6[tm0:1507941600155887,tm1:1507941600156458,tm2:1507941600168015(11557),tm3:1507941600168461(12003),tm4:1507941600168504(12046)][tm4-tm0]:12617\nfinish 447 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11573\n448----rcs.size():6[tm0:1507941600209318,tm1:1507941600209989,tm2:1507941600221815(11826),tm3:1507941600222031(12042),tm4:1507941600222059(12070)][tm4-tm0]:12741\nfinish 448 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11673\n449----rcs.size():6[tm0:1507941600253863,tm1:1507941600254437,tm2:1507941600266424(11987),tm3:1507941600266603(12166),tm4:1507941600266646(12209)][tm4-tm0]:12783\nfinish 449 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11615\n450----rcs.size():6[tm0:1507941600297275,tm1:1507941600297896,tm2:1507941600309738(11842),tm3:1507941600309956(12060),tm4:1507941600310029(12133)][tm4-tm0]:12754\nfinish 450 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11487\n451----rcs.size():6[tm0:1507941600338744,tm1:1507941600339317,tm2:1507941600351085(11768),tm3:1507941600351309(11992),tm4:1507941600351340(12023)][tm4-tm0]:12596\nfinish 451 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11445\n452----rcs.size():6[tm0:1507941600383618,tm1:1507941600384279,tm2:1507941600396054(11775),tm3:1507941600396240(11961),tm4:1507941600396268(11989)][tm4-tm0]:12650\nfinish 452 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11602\n453----rcs.size():6[tm0:1507941600426374,tm1:1507941600426944,tm2:1507941600438799(11855),tm3:1507941600438996(12052),tm4:1507941600439038(12094)][tm4-tm0]:12664\nfinish 453 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11377\n454----rcs.size():6[tm0:1507941600469305,tm1:1507941600469902,tm2:1507941600481537(11635),tm3:1507941600481748(11846),tm4:1507941600481776(11874)][tm4-tm0]:12471\nfinish 454 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11750\n455----rcs.size():6[tm0:1507941600515375,tm1:1507941600515950,tm2:1507941600527933(11983),tm3:1507941600528342(12392),tm4:1507941600528415(12465)][tm4-tm0]:13040\nfinish 455 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11416\n456----rcs.size():6[tm0:1507941600562216,tm1:1507941600562821,tm2:1507941600574486(11665),tm3:1507941600574676(11855),tm4:1507941600574705(11884)][tm4-tm0]:12489\nfinish 456 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11338\n457----rcs.size():6[tm0:1507941600605240,tm1:1507941600605824,tm2:1507941600617474(11650),tm3:1507941600617695(11871),tm4:1507941600617730(11906)][tm4-tm0]:12490\nfinish 457 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11505\n458----rcs.size():6[tm0:1507941600651579,tm1:1507941600652210,tm2:1507941600664059(11849),tm3:1507941600664304(12094),tm4:1507941600664337(12127)][tm4-tm0]:12758\nfinish 458 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12004\n459----rcs.size():6[tm0:1507941600698574,tm1:1507941600699177,tm2:1507941600711439(12262),tm3:1507941600711642(12465),tm4:1507941600711682(12505)][tm4-tm0]:13108\nfinish 459 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11554\n460----rcs.size():6[tm0:1507941600742467,tm1:1507941600743079,tm2:1507941600754992(11913),tm3:1507941600755213(12134),tm4:1507941600755257(12178)][tm4-tm0]:12790\nfinish 460 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11492\n461----rcs.size():6[tm0:1507941600785653,tm1:1507941600786244,tm2:1507941600798043(11799),tm3:1507941600798302(12058),tm4:1507941600798344(12100)][tm4-tm0]:12691\nfinish 461 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11561\n462----rcs.size():6[tm0:1507941600838846,tm1:1507941600839481,tm2:1507941600851338(11857),tm3:1507941600851527(12046),tm4:1507941600851565(12084)][tm4-tm0]:12719\nfinish 462 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11660\n463----rcs.size():6[tm0:1507941600881890,tm1:1507941600882529,tm2:1507941600894448(11919),tm3:1507941600894685(12156),tm4:1507941600894726(12197)][tm4-tm0]:12836\nfinish 463 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11384\n464----rcs.size():6[tm0:1507941600925594,tm1:1507941600926183,tm2:1507941600937854(11671),tm3:1507941600938068(11885),tm4:1507941600938112(11929)][tm4-tm0]:12518\nfinish 464 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11621\n465----rcs.size():6[tm0:1507941600969070,tm1:1507941600969706,tm2:1507941600981603(11897),tm3:1507941600981814(12108),tm4:1507941600981855(12149)][tm4-tm0]:12785\nfinish 465 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11523\n466----rcs.size():6[tm0:1507941601012355,tm1:1507941601012935,tm2:1507941601024786(11851),tm3:1507941601025004(12069),tm4:1507941601025039(12104)][tm4-tm0]:12684\nfinish 466 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11616\n467----rcs.size():6[tm0:1507941601057976,tm1:1507941601058552,tm2:1507941601070492(11940),tm3:1507941601070713(12161),tm4:1507941601070744(12192)][tm4-tm0]:12768\nfinish 467 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11800\n468----rcs.size():6[tm0:1507941601101941,tm1:1507941601102546,tm2:1507941601114651(12105),tm3:1507941601114886(12340),tm4:1507941601114932(12386)][tm4-tm0]:12991\nfinish 468 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11630\n469----rcs.size():6[tm0:1507941601145719,tm1:1507941601146297,tm2:1507941601158259(11962),tm3:1507941601158503(12206),tm4:1507941601158549(12252)][tm4-tm0]:12830\nfinish 469 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11640\n470----rcs.size():6[tm0:1507941601189428,tm1:1507941601190028,tm2:1507941601202006(11978),tm3:1507941601202260(12232),tm4:1507941601202304(12276)][tm4-tm0]:12876\nfinish 470 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11747\n471----rcs.size():6[tm0:1507941601232766,tm1:1507941601233626,tm2:1507941601245744(12118),tm3:1507941601245984(12358),tm4:1507941601246026(12400)][tm4-tm0]:13260\nfinish 471 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11631\n472----rcs.size():6[tm0:1507941601276452,tm1:1507941601277094,tm2:1507941601289037(11943),tm3:1507941601289286(12192),tm4:1507941601289329(12235)][tm4-tm0]:12877\nfinish 472 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9996\n473----rcs.size():5[tm0:1507941601320501,tm1:1507941601321071,tm2:1507941601331335(10264),tm3:1507941601331552(10481),tm4:1507941601331588(10517)][tm4-tm0]:11087\nfinish 473 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8516\n474----rcs.size():4[tm0:1507941601362019,tm1:1507941601362635,tm2:1507941601371338(8703),tm3:1507941601371508(8873),tm4:1507941601371538(8903)][tm4-tm0]:9519\nfinish 474 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9666\n475----rcs.size():5[tm0:1507941601402488,tm1:1507941601403072,tm2:1507941601412959(9887),tm3:1507941601413198(10126),tm4:1507941601413229(10157)][tm4-tm0]:10741\nfinish 475 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9815\n476----rcs.size():5[tm0:1507941601443985,tm1:1507941601444589,tm2:1507941601454666(10077),tm3:1507941601454880(10291),tm4:1507941601454912(10323)][tm4-tm0]:10927\nfinish 476 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11647\n477----rcs.size():6[tm0:1507941601489636,tm1:1507941601490246,tm2:1507941601502124(11878),tm3:1507941601502376(12130),tm4:1507941601502410(12164)][tm4-tm0]:12774\nfinish 477 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11487\n478----rcs.size():6[tm0:1507941601532446,tm1:1507941601533286,tm2:1507941601545042(11756),tm3:1507941601545296(12010),tm4:1507941601545332(12046)][tm4-tm0]:12886\nfinish 478 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11663\n479----rcs.size():6[tm0:1507941601576275,tm1:1507941601576883,tm2:1507941601588831(11948),tm3:1507941601589083(12200),tm4:1507941601589122(12239)][tm4-tm0]:12847\nfinish 479 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11543\n480----rcs.size():6[tm0:1507941601623476,tm1:1507941601624105,tm2:1507941601635964(11859),tm3:1507941601636179(12074),tm4:1507941601636216(12111)][tm4-tm0]:12740\nfinish 480 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11697\n481----rcs.size():6[tm0:1507941601667054,tm1:1507941601667802,tm2:1507941601679768(11966),tm3:1507941601679975(12173),tm4:1507941601680004(12202)][tm4-tm0]:12950\nfinish 481 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11883\n482----rcs.size():6[tm0:1507941601710315,tm1:1507941601710855,tm2:1507941601723019(12164),tm3:1507941601723229(12374),tm4:1507941601723257(12402)][tm4-tm0]:12942\nfinish 482 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11543\n483----rcs.size():6[tm0:1507941601753796,tm1:1507941601754491,tm2:1507941601766298(11807),tm3:1507941601766495(12004),tm4:1507941601766533(12042)][tm4-tm0]:12737\nfinish 483 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12162\n484----rcs.size():6[tm0:1507941601802183,tm1:1507941601802926,tm2:1507941601815549(12623),tm3:1507941601815741(12815),tm4:1507941601815773(12847)][tm4-tm0]:13590\nfinish 484 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11961\n485----rcs.size():6[tm0:1507941601854302,tm1:1507941601855118,tm2:1507941601867519(12401),tm3:1507941601867776(12658),tm4:1507941601867922(12804)][tm4-tm0]:13620\nfinish 485 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12377\n486----rcs.size():6[tm0:1507941601905046,tm1:1507941601905795,tm2:1507941601918683(12888),tm3:1507941601918933(13138),tm4:1507941601918982(13187)][tm4-tm0]:13936\nfinish 486 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12090\n487----rcs.size():6[tm0:1507941601959685,tm1:1507941601960287,tm2:1507941601972676(12389),tm3:1507941601972985(12698),tm4:1507941601973044(12757)][tm4-tm0]:13359\nfinish 487 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12170\n488----rcs.size():6[tm0:1507941602012204,tm1:1507941602012804,tm2:1507941602025300(12496),tm3:1507941602025505(12701),tm4:1507941602025571(12767)][tm4-tm0]:13367\nfinish 488 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:12005\n489----rcs.size():6[tm0:1507941602063988,tm1:1507941602064563,tm2:1507941602076911(12348),tm3:1507941602077189(12626),tm4:1507941602077235(12672)][tm4-tm0]:13247\nfinish 489 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12055\n490----rcs.size():6[tm0:1507941602113025,tm1:1507941602113775,tm2:1507941602126238(12463),tm3:1507941602126430(12655),tm4:1507941602126461(12686)][tm4-tm0]:13436\nfinish 490 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12094\n491----rcs.size():6[tm0:1507941602167789,tm1:1507941602168606,tm2:1507941602181159(12553),tm3:1507941602181378(12772),tm4:1507941602181424(12818)][tm4-tm0]:13635\nfinish 491 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11787\n492----rcs.size():6[tm0:1507941602218353,tm1:1507941602218916,tm2:1507941602231064(12148),tm3:1507941602231473(12557),tm4:1507941602231541(12625)][tm4-tm0]:13188\nfinish 492 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:12000\n493----rcs.size():6[tm0:1507941602272475,tm1:1507941602273024,tm2:1507941602285379(12355),tm3:1507941602285587(12563),tm4:1507941602285630(12606)][tm4-tm0]:13155\nfinish 493 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11860\n494----rcs.size():6[tm0:1507941602316770,tm1:1507941602317430,tm2:1507941602329656(12226),tm3:1507941602329905(12475),tm4:1507941602330047(12617)][tm4-tm0]:13277\nfinish 494 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11854\n495----rcs.size():6[tm0:1507941602362082,tm1:1507941602362659,tm2:1507941602374863(12204),tm3:1507941602375183(12524),tm4:1507941602375335(12676)][tm4-tm0]:13253\nfinish 495 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11827\n496----rcs.size():6[tm0:1507941602412658,tm1:1507941602413247,tm2:1507941602425427(12180),tm3:1507941602425647(12400),tm4:1507941602425694(12447)][tm4-tm0]:13036\nfinish 496 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11832\n497----rcs.size():6[tm0:1507941602462409,tm1:1507941602463125,tm2:1507941602475323(12198),tm3:1507941602475535(12410),tm4:1507941602475567(12442)][tm4-tm0]:13158\nfinish 497 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11804\n498----rcs.size():6[tm0:1507941602510038,tm1:1507941602510607,tm2:1507941602522763(12156),tm3:1507941602522989(12382),tm4:1507941602523038(12431)][tm4-tm0]:13000\nfinish 498 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:11\n(incpp)call encode cost time:tmd-tmc:11803\n499----rcs.size():6[tm0:1507941602554020,tm1:1507941602554722,tm2:1507941602566847(12125),tm3:1507941602567065(12343),tm4:1507941602567095(12373)][tm4-tm0]:13075\nfinish 499 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11902\n500----rcs.size():6[tm0:1507941602603344,tm1:1507941602603939,tm2:1507941602616187(12248),tm3:1507941602616584(12645),tm4:1507941602616636(12697)][tm4-tm0]:13292\nfinish 500 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11555\n501----rcs.size():6[tm0:1507941602654450,tm1:1507941602655181,tm2:1507941602667024(11843),tm3:1507941602667412(12231),tm4:1507941602667463(12282)][tm4-tm0]:13013\nfinish 501 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:10\n(incpp)call encode cost time:tmd-tmc:11685\n502----rcs.size():6[tm0:1507941602706607,tm1:1507941602707250,tm2:1507941602719243(11993),tm3:1507941602719503(12253),tm4:1507941602719532(12282)][tm4-tm0]:12925\nfinish 502 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9590\n503----rcs.size():5[tm0:1507941602749474,tm1:1507941602750119,tm2:1507941602759878(9759),tm3:1507941602760091(9972),tm4:1507941602760123(10004)][tm4-tm0]:10649\nfinish 503 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9801\n504----rcs.size():5[tm0:1507941602789581,tm1:1507941602790288,tm2:1507941602800238(9950),tm3:1507941602800397(10109),tm4:1507941602800419(10131)][tm4-tm0]:10838\nfinish 504 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9670\n505----rcs.size():5[tm0:1507941602829977,tm1:1507941602830633,tm2:1507941602840481(9848),tm3:1507941602840618(9985),tm4:1507941602840641(10008)][tm4-tm0]:10664\nfinish 505 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9648\n506----rcs.size():5[tm0:1507941602870871,tm1:1507941602871435,tm2:1507941602881238(9803),tm3:1507941602881398(9963),tm4:1507941602881422(9987)][tm4-tm0]:10551\nfinish 506 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9914\n507----rcs.size():5[tm0:1507941602913588,tm1:1507941602914168,tm2:1507941602924236(10068),tm3:1507941602924388(10220),tm4:1507941602924413(10245)][tm4-tm0]:10825\nfinish 507 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9605\n508----rcs.size():5[tm0:1507941602955323,tm1:1507941602956012,tm2:1507941602965758(9746),tm3:1507941602965945(9933),tm4:1507941602965973(9961)][tm4-tm0]:10650\nfinish 508 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9740\n509----rcs.size():5[tm0:1507941602999678,tm1:1507941603000415,tm2:1507941603010357(9942),tm3:1507941603010522(10107),tm4:1507941603010547(10132)][tm4-tm0]:10869\nfinish 509 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9459\n510----rcs.size():5[tm0:1507941603043441,tm1:1507941603044173,tm2:1507941603053823(9650),tm3:1507941603053986(9813),tm4:1507941603054011(9838)][tm4-tm0]:10570\nfinish 510 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9662\n511----rcs.size():5[tm0:1507941603084841,tm1:1507941603085467,tm2:1507941603095275(9808),tm3:1507941603095448(9981),tm4:1507941603095483(10016)][tm4-tm0]:10642\nfinish 511 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9481\n512----rcs.size():5[tm0:1507941603125322,tm1:1507941603125929,tm2:1507941603135571(9642),tm3:1507941603135735(9806),tm4:1507941603135760(9831)][tm4-tm0]:10438\nfinish 512 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9608\n513----rcs.size():5[tm0:1507941603166821,tm1:1507941603167492,tm2:1507941603177248(9756),tm3:1507941603177492(10000),tm4:1507941603177542(10050)][tm4-tm0]:10721\nfinish 513 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9532\n514----rcs.size():5[tm0:1507941603211381,tm1:1507941603212046,tm2:1507941603221742(9696),tm3:1507941603221921(9875),tm4:1507941603222016(9970)][tm4-tm0]:10635\nfinish 514 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8281\n515----rcs.size():4[tm0:1507941603251643,tm1:1507941603252253,tm2:1507941603260689(8436),tm3:1507941603260867(8614),tm4:1507941603260955(8702)][tm4-tm0]:9312\nfinish 515 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9699\n516----rcs.size():5[tm0:1507941603290347,tm1:1507941603291046,tm2:1507941603300932(9886),tm3:1507941603301182(10136),tm4:1507941603301202(10156)][tm4-tm0]:10855\nfinish 516 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9725\n517----rcs.size():5[tm0:1507941603330589,tm1:1507941603331161,tm2:1507941603341059(9898),tm3:1507941603341318(10157),tm4:1507941603341347(10186)][tm4-tm0]:10758\nfinish 517 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9801\n518----rcs.size():5[tm0:1507941603370745,tm1:1507941603371344,tm2:1507941603381356(10012),tm3:1507941603381584(10240),tm4:1507941603381620(10276)][tm4-tm0]:10875\nfinish 518 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9581\n519----rcs.size():5[tm0:1507941603416049,tm1:1507941603416706,tm2:1507941603426496(9790),tm3:1507941603426666(9960),tm4:1507941603426700(9994)][tm4-tm0]:10651\nfinish 519 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9625\n520----rcs.size():5[tm0:1507941603460638,tm1:1507941603461235,tm2:1507941603471108(9873),tm3:1507941603471314(10079),tm4:1507941603471349(10114)][tm4-tm0]:10711\nfinish 520 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9678\n521----rcs.size():5[tm0:1507941603501468,tm1:1507941603502078,tm2:1507941603511984(9906),tm3:1507941603512235(10157),tm4:1507941603512272(10194)][tm4-tm0]:10804\nfinish 521 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9801\n522----rcs.size():5[tm0:1507941603542016,tm1:1507941603542745,tm2:1507941603552752(10007),tm3:1507941603553000(10255),tm4:1507941603553038(10293)][tm4-tm0]:11022\nfinish 522 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9725\n523----rcs.size():5[tm0:1507941603592111,tm1:1507941603592841,tm2:1507941603602760(9919),tm3:1507941603602958(10117),tm4:1507941603603066(10225)][tm4-tm0]:10955\nfinish 523 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9739\n524----rcs.size():5[tm0:1507941603632892,tm1:1507941603633600,tm2:1507941603643586(9986),tm3:1507941603643750(10150),tm4:1507941603643774(10174)][tm4-tm0]:10882\nfinish 524 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9725\n525----rcs.size():5[tm0:1507941603674107,tm1:1507941603674680,tm2:1507941603684630(9950),tm3:1507941603684824(10144),tm4:1507941603684856(10176)][tm4-tm0]:10749\nfinish 525 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9949\n526----rcs.size():5[tm0:1507941603714517,tm1:1507941603715150,tm2:1507941603725312(10162),tm3:1507941603725475(10325),tm4:1507941603725513(10363)][tm4-tm0]:10996\nfinish 526 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9682\n527----rcs.size():5[tm0:1507941603755705,tm1:1507941603756408,tm2:1507941603766293(9885),tm3:1507941603766580(10172),tm4:1507941603766651(10243)][tm4-tm0]:10946\nfinish 527 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9927\n528----rcs.size():5[tm0:1507941603804498,tm1:1507941603805054,tm2:1507941603815246(10192),tm3:1507941603815423(10369),tm4:1507941603815460(10406)][tm4-tm0]:10962\nfinish 528 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9752\n529----rcs.size():5[tm0:1507941603845645,tm1:1507941603846237,tm2:1507941603856262(10025),tm3:1507941603856470(10233),tm4:1507941603856502(10265)][tm4-tm0]:10857\nfinish 529 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10081\n530----rcs.size():5[tm0:1507941603889566,tm1:1507941603890162,tm2:1507941603900463(10301),tm3:1507941603900652(10490),tm4:1507941603900769(10607)][tm4-tm0]:11203\nfinish 530 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9714\n531----rcs.size():5[tm0:1507941603930154,tm1:1507941603930728,tm2:1507941603940690(9962),tm3:1507941603940868(10140),tm4:1507941603940896(10168)][tm4-tm0]:10742\nfinish 531 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9939\n532----rcs.size():5[tm0:1507941603970792,tm1:1507941603971399,tm2:1507941603981592(10193),tm3:1507941603981782(10383),tm4:1507941603981919(10520)][tm4-tm0]:11127\nfinish 532 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9678\n533----rcs.size():5[tm0:1507941604010925,tm1:1507941604011497,tm2:1507941604021420(9923),tm3:1507941604021628(10131),tm4:1507941604021665(10168)][tm4-tm0]:10740\nfinish 533 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9800\n534----rcs.size():5[tm0:1507941604051728,tm1:1507941604052284,tm2:1507941604062314(10030),tm3:1507941604062518(10234),tm4:1507941604062557(10273)][tm4-tm0]:10829\nfinish 534 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9893\n535----rcs.size():5[tm0:1507941604093078,tm1:1507941604093654,tm2:1507941604103830(10176),tm3:1507941604104001(10347),tm4:1507941604104031(10377)][tm4-tm0]:10953\nfinish 535 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8563\n536----rcs.size():4[tm0:1507941604134933,tm1:1507941604135648,tm2:1507941604144428(8780),tm3:1507941604144619(8971),tm4:1507941604144654(9006)][tm4-tm0]:9721\nfinish 536 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8454\n537----rcs.size():4[tm0:1507941604175874,tm1:1507941604176552,tm2:1507941604185270(8718),tm3:1507941604185447(8895),tm4:1507941604185564(9012)][tm4-tm0]:9690\nfinish 537 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8592\n538----rcs.size():4[tm0:1507941604218002,tm1:1507941604218651,tm2:1507941604227535(8884),tm3:1507941604227679(9028),tm4:1507941604227800(9149)][tm4-tm0]:9798\nfinish 538 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8408\n539----rcs.size():4[tm0:1507941604269436,tm1:1507941604270128,tm2:1507941604278773(8645),tm3:1507941604278957(8829),tm4:1507941604279094(8966)][tm4-tm0]:9658\nfinish 539 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8285\n540----rcs.size():4[tm0:1507941604312616,tm1:1507941604313178,tm2:1507941604321743(8565),tm3:1507941604321918(8740),tm4:1507941604321954(8776)][tm4-tm0]:9338\nfinish 540 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9837\n541----rcs.size():5[tm0:1507941604352513,tm1:1507941604353196,tm2:1507941604363343(10147),tm3:1507941604363577(10381),tm4:1507941604363689(10493)][tm4-tm0]:11176\nfinish 541 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9964\n542----rcs.size():5[tm0:1507941604393456,tm1:1507941604393995,tm2:1507941604404301(10306),tm3:1507941604404500(10505),tm4:1507941604404528(10533)][tm4-tm0]:11072\nfinish 542 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:9958\n543----rcs.size():5[tm0:1507941604438063,tm1:1507941604438608,tm2:1507941604448883(10275),tm3:1507941604449066(10458),tm4:1507941604449106(10498)][tm4-tm0]:11043\nfinish 543 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10289\n544----rcs.size():5[tm0:1507941604481018,tm1:1507941604481734,tm2:1507941604492318(10584),tm3:1507941604492517(10783),tm4:1507941604492560(10826)][tm4-tm0]:11542\nfinish 544 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10064\n545----rcs.size():5[tm0:1507941604522656,tm1:1507941604523363,tm2:1507941604533764(10401),tm3:1507941604533975(10612),tm4:1507941604534122(10759)][tm4-tm0]:11466\nfinish 545 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10269\n546----rcs.size():5[tm0:1507941604564249,tm1:1507941604564805,tm2:1507941604575440(10635),tm3:1507941604575667(10862),tm4:1507941604575818(11013)][tm4-tm0]:11569\nfinish 546 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10011\n547----rcs.size():5[tm0:1507941604608186,tm1:1507941604608722,tm2:1507941604619117(10395),tm3:1507941604619358(10636),tm4:1507941604619507(10785)][tm4-tm0]:11321\nfinish 547 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10184\n548----rcs.size():5[tm0:1507941604650154,tm1:1507941604650790,tm2:1507941604661318(10528),tm3:1507941604661515(10725),tm4:1507941604661545(10755)][tm4-tm0]:11391\nfinish 548 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10103\n549----rcs.size():5[tm0:1507941604691914,tm1:1507941604692490,tm2:1507941604702937(10447),tm3:1507941604703172(10682),tm4:1507941604703205(10715)][tm4-tm0]:11291\nfinish 549 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10129\n550----rcs.size():5[tm0:1507941604734024,tm1:1507941604734730,tm2:1507941604745237(10507),tm3:1507941604745449(10719),tm4:1507941604745500(10770)][tm4-tm0]:11476\nfinish 550 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10100\n551----rcs.size():5[tm0:1507941604774360,tm1:1507941604775052,tm2:1507941604785526(10474),tm3:1507941604785732(10680),tm4:1507941604785778(10726)][tm4-tm0]:11418\nfinish 551 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10112\n552----rcs.size():5[tm0:1507941604819523,tm1:1507941604820164,tm2:1507941604830648(10484),tm3:1507941604830891(10727),tm4:1507941604830946(10782)][tm4-tm0]:11423\nfinish 552 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10095\n553----rcs.size():5[tm0:1507941604860369,tm1:1507941604860988,tm2:1507941604871460(10472),tm3:1507941604871693(10705),tm4:1507941604871743(10755)][tm4-tm0]:11374\nfinish 553 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10044\n554----rcs.size():5[tm0:1507941604902348,tm1:1507941604902957,tm2:1507941604913378(10421),tm3:1507941604913598(10641),tm4:1507941604913767(10810)][tm4-tm0]:11419\nfinish 554 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10334\n555----rcs.size():5[tm0:1507941604945080,tm1:1507941604945695,tm2:1507941604956492(10797),tm3:1507941604956703(11008),tm4:1507941604956746(11051)][tm4-tm0]:11666\nfinish 555 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10021\n556----rcs.size():5[tm0:1507941604989393,tm1:1507941604989965,tm2:1507941605000389(10424),tm3:1507941605000619(10654),tm4:1507941605000665(10700)][tm4-tm0]:11272\nfinish 556 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10430\n557----rcs.size():5[tm0:1507941605030295,tm1:1507941605031009,tm2:1507941605041791(10782),tm3:1507941605041994(10985),tm4:1507941605042024(11015)][tm4-tm0]:11729\nfinish 557 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:10129\n558----rcs.size():5[tm0:1507941605071406,tm1:1507941605071972,tm2:1507941605082479(10507),tm3:1507941605082681(10709),tm4:1507941605082725(10753)][tm4-tm0]:11319\nfinish 558 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:9\n(incpp)call encode cost time:tmd-tmc:10313\n559----rcs.size():5[tm0:1507941605113388,tm1:1507941605114038,tm2:1507941605124790(10752),tm3:1507941605125009(10971),tm4:1507941605125056(11018)][tm4-tm0]:11668\nfinish 559 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8413\n560----rcs.size():4[tm0:1507941605154850,tm1:1507941605155453,tm2:1507941605164083(8630),tm3:1507941605164290(8837),tm4:1507941605164329(8876)][tm4-tm0]:9479\nfinish 560 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8415\n561----rcs.size():4[tm0:1507941605195958,tm1:1507941605196546,tm2:1507941605205227(8681),tm3:1507941605205443(8897),tm4:1507941605205505(8959)][tm4-tm0]:9547\nfinish 561 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8494\n562----rcs.size():4[tm0:1507941605244083,tm1:1507941605244742,tm2:1507941605253463(8721),tm3:1507941605253631(8889),tm4:1507941605253661(8919)][tm4-tm0]:9578\nfinish 562 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8495\n563----rcs.size():4[tm0:1507941605288238,tm1:1507941605288790,tm2:1507941605297496(8706),tm3:1507941605297661(8871),tm4:1507941605297774(8984)][tm4-tm0]:9536\nfinish 563 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8554\n564----rcs.size():4[tm0:1507941605331990,tm1:1507941605332866,tm2:1507941605341718(8852),tm3:1507941605341880(9014),tm4:1507941605342015(9149)][tm4-tm0]:10025\nfinish 564 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8395\n565----rcs.size():4[tm0:1507941605371961,tm1:1507941605372594,tm2:1507941605381227(8633),tm3:1507941605381382(8788),tm4:1507941605381408(8814)][tm4-tm0]:9447\nfinish 565 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:9006\n566----rcs.size():4[tm0:1507941605414019,tm1:1507941605414580,tm2:1507941605423832(9252),tm3:1507941605424007(9427),tm4:1507941605424046(9466)][tm4-tm0]:10027\nfinish 566 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8408\n567----rcs.size():4[tm0:1507941605461396,tm1:1507941605462069,tm2:1507941605470741(8672),tm3:1507941605470918(8849),tm4:1507941605470952(8883)][tm4-tm0]:9556\nfinish 567 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8597\n568----rcs.size():4[tm0:1507941605501528,tm1:1507941605502092,tm2:1507941605510982(8890),tm3:1507941605511176(9084),tm4:1507941605511215(9123)][tm4-tm0]:9687\nfinish 568 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8513\n569----rcs.size():4[tm0:1507941605541773,tm1:1507941605542380,tm2:1507941605551156(8776),tm3:1507941605551301(8921),tm4:1507941605551328(8948)][tm4-tm0]:9555\nfinish 569 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8640\n570----rcs.size():4[tm0:1507941605581846,tm1:1507941605582848,tm2:1507941605591838(8990),tm3:1507941605591994(9146),tm4:1507941605592031(9183)][tm4-tm0]:10185\nfinish 570 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8774\n571----rcs.size():4[tm0:1507941605622425,tm1:1507941605623052,tm2:1507941605632074(9022),tm3:1507941605632238(9186),tm4:1507941605632261(9209)][tm4-tm0]:9836\nfinish 571 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:8\n(incpp)call encode cost time:tmd-tmc:8478\n572----rcs.size():4[tm0:1507941605661434,tm1:1507941605661976,tm2:1507941605670699(8723),tm3:1507941605670865(8889),tm4:1507941605670888(8912)][tm4-tm0]:9454\nfinish 572 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:8522\n573----rcs.size():4[tm0:1507941605701226,tm1:1507941605701780,tm2:1507941605710503(8723),tm3:1507941605710644(8864),tm4:1507941605710668(8888)][tm4-tm0]:9442\nfinish 573 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6891\n574----rcs.size():3[tm0:1507941605742630,tm1:1507941605743224,tm2:1507941605750235(7011),tm3:1507941605750388(7164),tm4:1507941605750407(7183)][tm4-tm0]:7777\nfinish 574 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6966\n575----rcs.size():3[tm0:1507941605780421,tm1:1507941605781009,tm2:1507941605788110(7101),tm3:1507941605788242(7233),tm4:1507941605788260(7251)][tm4-tm0]:7839\nfinish 575 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6887\n576----rcs.size():3[tm0:1507941605821924,tm1:1507941605822480,tm2:1507941605829509(7029),tm3:1507941605829627(7147),tm4:1507941605829658(7178)][tm4-tm0]:7734\nfinish 576 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7021\n577----rcs.size():3[tm0:1507941605861824,tm1:1507941605862449,tm2:1507941605869599(7150),tm3:1507941605869714(7265),tm4:1507941605869798(7349)][tm4-tm0]:7974\nfinish 577 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7120\n578----rcs.size():3[tm0:1507941605900992,tm1:1507941605901545,tm2:1507941605908808(7263),tm3:1507941605908938(7393),tm4:1507941605909020(7475)][tm4-tm0]:8028\nfinish 578 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7027\n579----rcs.size():3[tm0:1507941605943458,tm1:1507941605944047,tm2:1507941605951267(7220),tm3:1507941605951420(7373),tm4:1507941605951456(7409)][tm4-tm0]:7998\nfinish 579 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6976\n580----rcs.size():3[tm0:1507941605988449,tm1:1507941605989011,tm2:1507941605996127(7116),tm3:1507941605996254(7243),tm4:1507941605996273(7262)][tm4-tm0]:7824\nfinish 580 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7070\n581----rcs.size():3[tm0:1507941606035089,tm1:1507941606035727,tm2:1507941606042947(7220),tm3:1507941606043079(7352),tm4:1507941606043109(7382)][tm4-tm0]:8020\nfinish 581 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7154\n582----rcs.size():3[tm0:1507941606081171,tm1:1507941606081705,tm2:1507941606089099(7394),tm3:1507941606089299(7594),tm4:1507941606089321(7616)][tm4-tm0]:8150\nfinish 582 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7025\n583----rcs.size():3[tm0:1507941606123444,tm1:1507941606124052,tm2:1507941606131234(7182),tm3:1507941606131387(7335),tm4:1507941606131414(7362)][tm4-tm0]:7970\nfinish 583 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7147\n584----rcs.size():3[tm0:1507941606163565,tm1:1507941606164166,tm2:1507941606171477(7311),tm3:1507941606171608(7442),tm4:1507941606171656(7490)][tm4-tm0]:8091\nfinish 584 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7112\n585----rcs.size():3[tm0:1507941606209205,tm1:1507941606209793,tm2:1507941606217047(7254),tm3:1507941606217158(7365),tm4:1507941606217195(7402)][tm4-tm0]:7990\nfinish 585 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7081\n586----rcs.size():3[tm0:1507941606252447,tm1:1507941606253083,tm2:1507941606260349(7266),tm3:1507941606260465(7382),tm4:1507941606260497(7414)][tm4-tm0]:8050\nfinish 586 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7045\n587----rcs.size():3[tm0:1507941606299268,tm1:1507941606299906,tm2:1507941606307171(7265),tm3:1507941606307309(7403),tm4:1507941606307402(7496)][tm4-tm0]:8134\nfinish 587 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7096\n588----rcs.size():3[tm0:1507941606341139,tm1:1507941606341700,tm2:1507941606348991(7291),tm3:1507941606349123(7423),tm4:1507941606349156(7456)][tm4-tm0]:8017\nfinish 588 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7159\n589----rcs.size():3[tm0:1507941606381453,tm1:1507941606382285,tm2:1507941606389624(7339),tm3:1507941606389776(7491),tm4:1507941606389805(7520)][tm4-tm0]:8352\nfinish 589 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7033\n590----rcs.size():3[tm0:1507941606419971,tm1:1507941606420591,tm2:1507941606427844(7253),tm3:1507941606427977(7386),tm4:1507941606428009(7418)][tm4-tm0]:8038\nfinish 590 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7481\n591----rcs.size():3[tm0:1507941606463597,tm1:1507941606464215,tm2:1507941606471906(7691),tm3:1507941606472041(7826),tm4:1507941606472070(7855)][tm4-tm0]:8473\nfinish 591 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7073\n592----rcs.size():3[tm0:1507941606502671,tm1:1507941606503285,tm2:1507941606510556(7271),tm3:1507941606510689(7404),tm4:1507941606510719(7434)][tm4-tm0]:8048\nfinish 592 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7081\n593----rcs.size():3[tm0:1507941606543706,tm1:1507941606544355,tm2:1507941606551663(7308),tm3:1507941606551802(7447),tm4:1507941606551831(7476)][tm4-tm0]:8125\nfinish 593 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7093\n594----rcs.size():3[tm0:1507941606582397,tm1:1507941606583220,tm2:1507941606590500(7280),tm3:1507941606590654(7434),tm4:1507941606590689(7469)][tm4-tm0]:8292\nfinish 594 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7048\n595----rcs.size():3[tm0:1507941606621444,tm1:1507941606622035,tm2:1507941606629288(7253),tm3:1507941606629443(7408),tm4:1507941606629472(7437)][tm4-tm0]:8028\nfinish 595 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7286\n596----rcs.size():3[tm0:1507941606660163,tm1:1507941606660817,tm2:1507941606668316(7499),tm3:1507941606668449(7632),tm4:1507941606668472(7655)][tm4-tm0]:8309\nfinish 596 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7121\n597----rcs.size():3[tm0:1507941606707530,tm1:1507941606708136,tm2:1507941606715475(7339),tm3:1507941606715633(7497),tm4:1507941606715667(7531)][tm4-tm0]:8137\nfinish 597 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7220\n598----rcs.size():3[tm0:1507941606756163,tm1:1507941606756781,tm2:1507941606764270(7489),tm3:1507941606764457(7676),tm4:1507941606764492(7711)][tm4-tm0]:8329\nfinish 598 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7088\n599----rcs.size():3[tm0:1507941606801985,tm1:1507941606802580,tm2:1507941606809885(7305),tm3:1507941606810022(7442),tm4:1507941606810045(7465)][tm4-tm0]:8060\nfinish 599 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7035\n600----rcs.size():3[tm0:1507941606840768,tm1:1507941606841314,tm2:1507941606848570(7256),tm3:1507941606848706(7392),tm4:1507941606848727(7413)][tm4-tm0]:7959\nfinish 600 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7251\n601----rcs.size():3[tm0:1507941606879829,tm1:1507941606880443,tm2:1507941606887917(7474),tm3:1507941606888045(7602),tm4:1507941606888080(7637)][tm4-tm0]:8251\nfinish 601 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7231\n602----rcs.size():3[tm0:1507941606922046,tm1:1507941606922657,tm2:1507941606930165(7508),tm3:1507941606930389(7732),tm4:1507941606930424(7767)][tm4-tm0]:8378\nfinish 602 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:7\n(incpp)call encode cost time:tmd-tmc:7364\n603----rcs.size():3[tm0:1507941606963430,tm1:1507941606964024,tm2:1507941606971621(7597),tm3:1507941606971759(7735),tm4:1507941606971782(7758)][tm4-tm0]:8352\nfinish 603 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7177\n604----rcs.size():3[tm0:1507941607002984,tm1:1507941607003547,tm2:1507941607010951(7404),tm3:1507941607011111(7564),tm4:1507941607011131(7584)][tm4-tm0]:8147\nfinish 604 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:7243\n605----rcs.size():3[tm0:1507941607043294,tm1:1507941607043868,tm2:1507941607051320(7452),tm3:1507941607051457(7589),tm4:1507941607051477(7609)][tm4-tm0]:8183\nfinish 605 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6076\n606----rcs.size():2[tm0:1507941607080754,tm1:1507941607081327,tm2:1507941607087568(6241),tm3:1507941607087692(6365),tm4:1507941607087709(6382)][tm4-tm0]:6955\nfinish 606 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5691\n607----rcs.size():2[tm0:1507941607120720,tm1:1507941607121272,tm2:1507941607127120(5848),tm3:1507941607127215(5943),tm4:1507941607127232(5960)][tm4-tm0]:6512\nfinish 607 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5689\n608----rcs.size():2[tm0:1507941607162275,tm1:1507941607162832,tm2:1507941607168695(5863),tm3:1507941607168797(5965),tm4:1507941607168821(5989)][tm4-tm0]:6546\nfinish 608 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5870\n609----rcs.size():2[tm0:1507941607199383,tm1:1507941607200189,tm2:1507941607206273(6084),tm3:1507941607206353(6164),tm4:1507941607206376(6187)][tm4-tm0]:6993\nfinish 609 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5684\n610----rcs.size():2[tm0:1507941607237247,tm1:1507941607237892,tm2:1507941607243782(5890),tm3:1507941607243882(5990),tm4:1507941607243910(6018)][tm4-tm0]:6663\nfinish 610 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5805\n611----rcs.size():2[tm0:1507941607282566,tm1:1507941607283381,tm2:1507941607289370(5989),tm3:1507941607289469(6088),tm4:1507941607289493(6112)][tm4-tm0]:6927\nfinish 611 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5738\n612----rcs.size():2[tm0:1507941607320601,tm1:1507941607321181,tm2:1507941607327118(5937),tm3:1507941607327204(6023),tm4:1507941607327230(6049)][tm4-tm0]:6629\nfinish 612 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5924\n613----rcs.size():2[tm0:1507941607365934,tm1:1507941607366618,tm2:1507941607372737(6119),tm3:1507941607372833(6215),tm4:1507941607372857(6239)][tm4-tm0]:6923\nfinish 613 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5939\n614----rcs.size():2[tm0:1507941607411404,tm1:1507941607412073,tm2:1507941607418231(6158),tm3:1507941607418372(6299),tm4:1507941607418403(6330)][tm4-tm0]:6999\nfinish 614 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5805\n615----rcs.size():2[tm0:1507941607457266,tm1:1507941607457928,tm2:1507941607463966(6038),tm3:1507941607464049(6121),tm4:1507941607464072(6144)][tm4-tm0]:6806\nfinish 615 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5878\n616----rcs.size():2[tm0:1507941607502568,tm1:1507941607503176,tm2:1507941607509260(6084),tm3:1507941607509347(6171),tm4:1507941607509367(6191)][tm4-tm0]:6799\nfinish 616 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5748\n617----rcs.size():2[tm0:1507941607541708,tm1:1507941607542357,tm2:1507941607548336(5979),tm3:1507941607548420(6063),tm4:1507941607548444(6087)][tm4-tm0]:6736\nfinish 617 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:5957\n618----rcs.size():2[tm0:1507941607579809,tm1:1507941607580396,tm2:1507941607586567(6171),tm3:1507941607586669(6273),tm4:1507941607586696(6300)][tm4-tm0]:6887\nfinish 618 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:6\n(incpp)call encode cost time:tmd-tmc:6115\n619----rcs.size():2[tm0:1507941607620647,tm1:1507941607621371,tm2:1507941607627727(6356),tm3:1507941607627826(6455),tm4:1507941607627854(6483)][tm4-tm0]:7207\nfinish 619 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4225\n620----rcs.size():1[tm0:1507941607666405,tm1:1507941607667010,tm2:1507941607671330(4320),tm3:1507941607671414(4404),tm4:1507941607671428(4418)][tm4-tm0]:5023\nfinish 620 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5849\n621----rcs.size():2[tm0:1507941607709709,tm1:1507941607710278,tm2:1507941607716390(6112),tm3:1507941607716475(6197),tm4:1507941607716504(6226)][tm4-tm0]:6795\nfinish 621 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5858\n622----rcs.size():2[tm0:1507941607755386,tm1:1507941607755976,tm2:1507941607762071(6095),tm3:1507941607762229(6253),tm4:1507941607762278(6302)][tm4-tm0]:6892\nfinish 622 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5861\n623----rcs.size():2[tm0:1507941607800568,tm1:1507941607801140,tm2:1507941607807302(6162),tm3:1507941607807392(6252),tm4:1507941607807419(6279)][tm4-tm0]:6851\nfinish 623 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5949\n624----rcs.size():2[tm0:1507941607845531,tm1:1507941607846201,tm2:1507941607852465(6264),tm3:1507941607852565(6364),tm4:1507941607852584(6383)][tm4-tm0]:7053\nfinish 624 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5837\n625----rcs.size():2[tm0:1507941607890450,tm1:1507941607891028,tm2:1507941607897108(6080),tm3:1507941607897226(6198),tm4:1507941607897245(6217)][tm4-tm0]:6795\nfinish 625 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5896\n626----rcs.size():2[tm0:1507941607931392,tm1:1507941607932274,tm2:1507941607938428(6154),tm3:1507941607938532(6258),tm4:1507941607938551(6277)][tm4-tm0]:7159\nfinish 626 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:5\n(incpp)call encode cost time:tmd-tmc:5769\n627----rcs.size():2[tm0:1507941607971386,tm1:1507941607971953,tm2:1507941607978000(6047),tm3:1507941607978115(6162),tm4:1507941607978133(6180)][tm4-tm0]:6747\nfinish 627 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4053\n628----rcs.size():1[tm0:1507941608012167,tm1:1507941608012756,tm2:1507941608016883(4127),tm3:1507941608016975(4219),tm4:1507941608016986(4230)][tm4-tm0]:4819\nfinish 628 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4135\n629----rcs.size():1[tm0:1507941608051519,tm1:1507941608052083,tm2:1507941608056284(4201),tm3:1507941608056360(4277),tm4:1507941608056383(4300)][tm4-tm0]:4864\nfinish 629 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4205\n630----rcs.size():1[tm0:1507941608093963,tm1:1507941608094626,tm2:1507941608098904(4278),tm3:1507941608098968(4342),tm4:1507941608098983(4357)][tm4-tm0]:5020\nfinish 630 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4430\n631----rcs.size():1[tm0:1507941608130211,tm1:1507941608130891,tm2:1507941608135389(4498),tm3:1507941608135460(4569),tm4:1507941608135477(4586)][tm4-tm0]:5266\nfinish 631 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4231\n632----rcs.size():1[tm0:1507941608173277,tm1:1507941608173810,tm2:1507941608178120(4310),tm3:1507941608178224(4414),tm4:1507941608178239(4429)][tm4-tm0]:4962\nfinish 632 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4425\n633----rcs.size():1[tm0:1507941608213742,tm1:1507941608214317,tm2:1507941608218820(4503),tm3:1507941608218876(4559),tm4:1507941608218889(4572)][tm4-tm0]:5147\nfinish 633 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4267\n634----rcs.size():1[tm0:1507941608253561,tm1:1507941608254199,tm2:1507941608258551(4352),tm3:1507941608258608(4409),tm4:1507941608258621(4422)][tm4-tm0]:5060\nfinish 634 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4102\n635----rcs.size():1[tm0:1507941608292382,tm1:1507941608292941,tm2:1507941608297125(4184),tm3:1507941608297199(4258),tm4:1507941608297226(4285)][tm4-tm0]:4844\nfinish 635 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4009\n636----rcs.size():1[tm0:1507941608333155,tm1:1507941608333756,tm2:1507941608337844(4088),tm3:1507941608337934(4178),tm4:1507941608337944(4188)][tm4-tm0]:4789\nfinish 636 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4223\n637----rcs.size():1[tm0:1507941608372376,tm1:1507941608372942,tm2:1507941608377271(4329),tm3:1507941608377346(4404),tm4:1507941608377360(4418)][tm4-tm0]:4984\nfinish 637 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4253\n638----rcs.size():1[tm0:1507941608412026,tm1:1507941608412591,tm2:1507941608416930(4339),tm3:1507941608417003(4412),tm4:1507941608417017(4426)][tm4-tm0]:4991\nfinish 638 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4160\n639----rcs.size():1[tm0:1507941608452026,tm1:1507941608452707,tm2:1507941608456993(4286),tm3:1507941608457064(4357),tm4:1507941608457076(4369)][tm4-tm0]:5050\nfinish 639 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4345\n640----rcs.size():1[tm0:1507941608493231,tm1:1507941608493767,tm2:1507941608498212(4445),tm3:1507941608498284(4517),tm4:1507941608498298(4531)][tm4-tm0]:5067\nfinish 640 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4124\n641----rcs.size():1[tm0:1507941608534712,tm1:1507941608535445,tm2:1507941608539652(4207),tm3:1507941608539706(4261),tm4:1507941608539721(4276)][tm4-tm0]:5009\nfinish 641 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4314\n642----rcs.size():1[tm0:1507941608573441,tm1:1507941608573984,tm2:1507941608578396(4412),tm3:1507941608578451(4467),tm4:1507941608578465(4481)][tm4-tm0]:5024\nfinish 642 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4156\n643----rcs.size():1[tm0:1507941608616791,tm1:1507941608617369,tm2:1507941608621610(4241),tm3:1507941608621668(4299),tm4:1507941608621681(4312)][tm4-tm0]:4890\nfinish 643 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4185\n644----rcs.size():1[tm0:1507941608660187,tm1:1507941608660885,tm2:1507941608665159(4274),tm3:1507941608665244(4359),tm4:1507941608665254(4369)][tm4-tm0]:5067\nfinish 644 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4077\n645----rcs.size():1[tm0:1507941608703804,tm1:1507941608704367,tm2:1507941608708524(4157),tm3:1507941608708594(4227),tm4:1507941608708604(4237)][tm4-tm0]:4800\nfinish 645 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:3\n(incpp)call encode cost time:tmd-tmc:4105\n646----rcs.size():1[tm0:1507941608742608,tm1:1507941608743151,tm2:1507941608747363(4212),tm3:1507941608747434(4283),tm4:1507941608747459(4308)][tm4-tm0]:4851\nfinish 646 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4166\n647----rcs.size():1[tm0:1507941608783970,tm1:1507941608784521,tm2:1507941608788778(4257),tm3:1507941608788833(4312),tm4:1507941608788859(4338)][tm4-tm0]:4889\nfinish 647 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4027\n648----rcs.size():1[tm0:1507941608823094,tm1:1507941608823652,tm2:1507941608827758(4106),tm3:1507941608827835(4183),tm4:1507941608827863(4211)][tm4-tm0]:4769\nfinish 648 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4222\n649----rcs.size():1[tm0:1507941608862435,tm1:1507941608862962,tm2:1507941608867247(4285),tm3:1507941608867321(4359),tm4:1507941608867333(4371)][tm4-tm0]:4898\nfinish 649 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:4\n(incpp)call encode cost time:tmd-tmc:4181\n650----rcs.size():1[tm0:1507941608906268,tm1:1507941608906803,tm2:1507941608911039(4236),tm3:1507941608911135(4332),tm4:1507941608911174(4371)][tm4-tm0]:4906\nfinish 650 frame\n651----rcs.size():0[tm0:1507941608948535,tm1:1507941608949160,tm2:1507941608949160(0),tm3:1507941608949167(7),tm4:1507941608949167(7)][tm4-tm0]:632\nfinish 651 frame\n652----rcs.size():0[tm0:1507941608983822,tm1:1507941608984394,tm2:1507941608984394(0),tm3:1507941608984401(7),tm4:1507941608984401(7)][tm4-tm0]:579\nfinish 652 frame\n653----rcs.size():0[tm0:1507941609020576,tm1:1507941609021188,tm2:1507941609021188(0),tm3:1507941609021195(7),tm4:1507941609021195(7)][tm4-tm0]:619\nfinish 653 frame\n654----rcs.size():0[tm0:1507941609055752,tm1:1507941609056397,tm2:1507941609056397(0),tm3:1507941609056404(7),tm4:1507941609056405(8)][tm4-tm0]:653\nfinish 654 frame\n655----rcs.size():0[tm0:1507941609090647,tm1:1507941609091213,tm2:1507941609091213(0),tm3:1507941609091220(7),tm4:1507941609091220(7)][tm4-tm0]:573\nfinish 655 frame\n656----rcs.size():0[tm0:1507941609124958,tm1:1507941609125506,tm2:1507941609125506(0),tm3:1507941609125513(7),tm4:1507941609125513(7)][tm4-tm0]:555\nfinish 656 frame\n657----rcs.size():0[tm0:1507941609160005,tm1:1507941609160543,tm2:1507941609160543(0),tm3:1507941609160550(7),tm4:1507941609160551(8)][tm4-tm0]:546\nfinish 657 frame\n658----rcs.size():0[tm0:1507941609194863,tm1:1507941609195394,tm2:1507941609195394(0),tm3:1507941609195401(7),tm4:1507941609195402(8)][tm4-tm0]:539\nfinish 658 frame\n659----rcs.size():0[tm0:1507941609229569,tm1:1507941609230146,tm2:1507941609230146(0),tm3:1507941609230152(6),tm4:1507941609230152(6)][tm4-tm0]:583\nfinish 659 frame\n660----rcs.size():0[tm0:1507941609264415,tm1:1507941609265271,tm2:1507941609265271(0),tm3:1507941609265278(7),tm4:1507941609265278(7)][tm4-tm0]:863\nfinish 660 frame\n661----rcs.size():0[tm0:1507941609300097,tm1:1507941609300651,tm2:1507941609300651(0),tm3:1507941609300657(6),tm4:1507941609300657(6)][tm4-tm0]:560\nfinish 661 frame\n662----rcs.size():0[tm0:1507941609335789,tm1:1507941609336343,tm2:1507941609336343(0),tm3:1507941609336350(7),tm4:1507941609336350(7)][tm4-tm0]:561\nfinish 662 frame\n663----rcs.size():0[tm0:1507941609371332,tm1:1507941609371961,tm2:1507941609371961(0),tm3:1507941609371967(6),tm4:1507941609371967(6)][tm4-tm0]:635\nfinish 663 frame\n664----rcs.size():0[tm0:1507941609406495,tm1:1507941609407081,tm2:1507941609407081(0),tm3:1507941609407086(5),tm4:1507941609407087(6)][tm4-tm0]:592\nfinish 664 frame\n665----rcs.size():0[tm0:1507941609442546,tm1:1507941609443175,tm2:1507941609443175(0),tm3:1507941609443181(6),tm4:1507941609443181(6)][tm4-tm0]:635\nfinish 665 frame\n666----rcs.size():0[tm0:1507941609479755,tm1:1507941609480378,tm2:1507941609480378(0),tm3:1507941609480384(6),tm4:1507941609480385(7)][tm4-tm0]:630\nfinish 666 frame\n667----rcs.size():0[tm0:1507941609516212,tm1:1507941609516847,tm2:1507941609516847(0),tm3:1507941609516853(6),tm4:1507941609516853(6)][tm4-tm0]:641\nfinish 667 frame\n668----rcs.size():0[tm0:1507941609551843,tm1:1507941609552505,tm2:1507941609552505(0),tm3:1507941609552512(7),tm4:1507941609552512(7)][tm4-tm0]:669\nfinish 668 frame\n669----rcs.size():0[tm0:1507941609588748,tm1:1507941609589433,tm2:1507941609589433(0),tm3:1507941609589439(6),tm4:1507941609589439(6)][tm4-tm0]:691\nfinish 669 frame\n670----rcs.size():0[tm0:1507941609624764,tm1:1507941609625351,tm2:1507941609625351(0),tm3:1507941609625357(6),tm4:1507941609625358(7)][tm4-tm0]:594\nfinish 670 frame\n671----rcs.size():0[tm0:1507941609660982,tm1:1507941609661648,tm2:1507941609661648(0),tm3:1507941609661655(7),tm4:1507941609661655(7)][tm4-tm0]:673\nfinish 671 frame\n672----rcs.size():0[tm0:1507941609696400,tm1:1507941609696986,tm2:1507941609696986(0),tm3:1507941609696993(7),tm4:1507941609696993(7)][tm4-tm0]:593\nfinish 672 frame\n673----rcs.size():0[tm0:1507941609731795,tm1:1507941609732489,tm2:1507941609732489(0),tm3:1507941609732495(6),tm4:1507941609732495(6)][tm4-tm0]:700\nfinish 673 frame\n674----rcs.size():0[tm0:1507941609769027,tm1:1507941609769609,tm2:1507941609769609(0),tm3:1507941609769615(6),tm4:1507941609769616(7)][tm4-tm0]:589\nfinish 674 frame\n675----rcs.size():0[tm0:1507941609804669,tm1:1507941609805314,tm2:1507941609805314(0),tm3:1507941609805320(6),tm4:1507941609805320(6)][tm4-tm0]:651\nfinish 675 frame\n676----rcs.size():0[tm0:1507941609841041,tm1:1507941609841590,tm2:1507941609841590(0),tm3:1507941609841596(6),tm4:1507941609841596(6)][tm4-tm0]:555\nfinish 676 frame\n677----rcs.size():0[tm0:1507941609876535,tm1:1507941609877126,tm2:1507941609877126(0),tm3:1507941609877131(5),tm4:1507941609877132(6)][tm4-tm0]:597\nfinish 677 frame\n678----rcs.size():0[tm0:1507941609911832,tm1:1507941609912355,tm2:1507941609912356(1),tm3:1507941609912362(7),tm4:1507941609912362(7)][tm4-tm0]:530\nfinish 678 frame\n679----rcs.size():0[tm0:1507941609949863,tm1:1507941609950422,tm2:1507941609950422(0),tm3:1507941609950428(6),tm4:1507941609950428(6)][tm4-tm0]:565\nfinish 679 frame\n"
  },
  {
    "path": "logn10.txt",
    "content": "hahahah0\nhahahah1\nhahahah2\nprocess image cost time:2\n_create_network\nbatch_norm_fn\nbatch_norm_fn\n('feature dimensionality: ', 128)\nbatch_norm_fn\nhahahah\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:782\n(incpp)call encode cost time:tmd-tmc:867998\n1----rcs.size():0[tm0:1507941100617389,tm1:1507941100622825,tm2:1507941100622825(0),tm3:1507941100622834(9),tm4:1507941100622834(9)][tm4-tm0]:5445\nfinish 1 frame\n2----rcs.size():0[tm0:1507941100671180,tm1:1507941100672375,tm2:1507941100672375(0),tm3:1507941100672377(2),tm4:1507941100672377(2)][tm4-tm0]:1197\nfinish 2 frame\n3----rcs.size():0[tm0:1507941100705004,tm1:1507941100705536,tm2:1507941100705536(0),tm3:1507941100705538(2),tm4:1507941100705539(3)][tm4-tm0]:535\nfinish 3 frame\n4----rcs.size():0[tm0:1507941100742160,tm1:1507941100742715,tm2:1507941100742715(0),tm3:1507941100742717(2),tm4:1507941100742717(2)][tm4-tm0]:557\nfinish 4 frame\n5----rcs.size():0[tm0:1507941100780425,tm1:1507941100781564,tm2:1507941100781564(0),tm3:1507941100781566(2),tm4:1507941100781566(2)][tm4-tm0]:1141\nfinish 5 frame\n6----rcs.size():0[tm0:1507941100822370,tm1:1507941100823453,tm2:1507941100823453(0),tm3:1507941100823457(4),tm4:1507941100823457(4)][tm4-tm0]:1087\nfinish 6 frame\n7----rcs.size():0[tm0:1507941100860257,tm1:1507941100860836,tm2:1507941100860836(0),tm3:1507941100860838(2),tm4:1507941100860838(2)][tm4-tm0]:581\nfinish 7 frame\n8----rcs.size():0[tm0:1507941100895449,tm1:1507941100895991,tm2:1507941100895991(0),tm3:1507941100896006(15),tm4:1507941100896007(16)][tm4-tm0]:558\nfinish 8 frame\n9----rcs.size():0[tm0:1507941100931682,tm1:1507941100932279,tm2:1507941100932279(0),tm3:1507941100932281(2),tm4:1507941100932281(2)][tm4-tm0]:599\nfinish 9 frame\n10----rcs.size():0[tm0:1507941100968855,tm1:1507941100969414,tm2:1507941100969414(0),tm3:1507941100969417(3),tm4:1507941100969417(3)][tm4-tm0]:562\nfinish 10 frame\n11----rcs.size():0[tm0:1507941101003870,tm1:1507941101004497,tm2:1507941101004497(0),tm3:1507941101004499(2),tm4:1507941101004499(2)][tm4-tm0]:629\nfinish 11 frame\n12----rcs.size():0[tm0:1507941101039853,tm1:1507941101040446,tm2:1507941101040446(0),tm3:1507941101040448(2),tm4:1507941101040448(2)][tm4-tm0]:595\nfinish 12 frame\n13----rcs.size():0[tm0:1507941101074878,tm1:1507941101075392,tm2:1507941101075392(0),tm3:1507941101075395(3),tm4:1507941101075395(3)][tm4-tm0]:517\nfinish 13 frame\n14----rcs.size():0[tm0:1507941101110151,tm1:1507941101110821,tm2:1507941101110821(0),tm3:1507941101110824(3),tm4:1507941101110824(3)][tm4-tm0]:673\nfinish 14 frame\n15----rcs.size():0[tm0:1507941101145467,tm1:1507941101146079,tm2:1507941101146079(0),tm3:1507941101146081(2),tm4:1507941101146081(2)][tm4-tm0]:614\nfinish 15 frame\n16----rcs.size():0[tm0:1507941101181135,tm1:1507941101181855,tm2:1507941101181855(0),tm3:1507941101181857(2),tm4:1507941101181858(3)][tm4-tm0]:723\nfinish 16 frame\n17----rcs.size():0[tm0:1507941101216131,tm1:1507941101216718,tm2:1507941101216718(0),tm3:1507941101216720(2),tm4:1507941101216721(3)][tm4-tm0]:590\nfinish 17 frame\n18----rcs.size():0[tm0:1507941101251650,tm1:1507941101252307,tm2:1507941101252307(0),tm3:1507941101252309(2),tm4:1507941101252309(2)][tm4-tm0]:659\nfinish 18 frame\n19----rcs.size():0[tm0:1507941101287028,tm1:1507941101287601,tm2:1507941101287601(0),tm3:1507941101287603(2),tm4:1507941101287604(3)][tm4-tm0]:576\nfinish 19 frame\n20----rcs.size():0[tm0:1507941101322463,tm1:1507941101323066,tm2:1507941101323067(1),tm3:1507941101323069(3),tm4:1507941101323069(3)][tm4-tm0]:606\nfinish 20 frame\n21----rcs.size():0[tm0:1507941101356591,tm1:1507941101357170,tm2:1507941101357170(0),tm3:1507941101357173(3),tm4:1507941101357173(3)][tm4-tm0]:582\nfinish 21 frame\n22----rcs.size():0[tm0:1507941101391798,tm1:1507941101392379,tm2:1507941101392379(0),tm3:1507941101392381(2),tm4:1507941101392382(3)][tm4-tm0]:584\nfinish 22 frame\n23----rcs.size():0[tm0:1507941101426365,tm1:1507941101426956,tm2:1507941101426956(0),tm3:1507941101426959(3),tm4:1507941101426959(3)][tm4-tm0]:594\nfinish 23 frame\n24----rcs.size():0[tm0:1507941101461302,tm1:1507941101461893,tm2:1507941101461893(0),tm3:1507941101461895(2),tm4:1507941101461895(2)][tm4-tm0]:593\nfinish 24 frame\n25----rcs.size():0[tm0:1507941101495966,tm1:1507941101496495,tm2:1507941101496495(0),tm3:1507941101496497(2),tm4:1507941101496498(3)][tm4-tm0]:532\nfinish 25 frame\n26----rcs.size():0[tm0:1507941101532546,tm1:1507941101533246,tm2:1507941101533246(0),tm3:1507941101533249(3),tm4:1507941101533249(3)][tm4-tm0]:703\nfinish 26 frame\n27----rcs.size():0[tm0:1507941101569511,tm1:1507941101570059,tm2:1507941101570059(0),tm3:1507941101570062(3),tm4:1507941101570062(3)][tm4-tm0]:551\nfinish 27 frame\n28----rcs.size():0[tm0:1507941101605202,tm1:1507941101605851,tm2:1507941101605851(0),tm3:1507941101605853(2),tm4:1507941101605854(3)][tm4-tm0]:652\nfinish 28 frame\n29----rcs.size():0[tm0:1507941101641454,tm1:1507941101642036,tm2:1507941101642036(0),tm3:1507941101642038(2),tm4:1507941101642038(2)][tm4-tm0]:584\nfinish 29 frame\n30----rcs.size():0[tm0:1507941101676581,tm1:1507941101677104,tm2:1507941101677104(0),tm3:1507941101677106(2),tm4:1507941101677106(2)][tm4-tm0]:525\nfinish 30 frame\n31----rcs.size():0[tm0:1507941101712312,tm1:1507941101712929,tm2:1507941101712929(0),tm3:1507941101712932(3),tm4:1507941101712932(3)][tm4-tm0]:620\nfinish 31 frame\n32----rcs.size():0[tm0:1507941101750044,tm1:1507941101750701,tm2:1507941101750701(0),tm3:1507941101750703(2),tm4:1507941101750704(3)][tm4-tm0]:660\nfinish 32 frame\n33----rcs.size():0[tm0:1507941101785865,tm1:1507941101786473,tm2:1507941101786473(0),tm3:1507941101786475(2),tm4:1507941101786476(3)][tm4-tm0]:611\nfinish 33 frame\n34----rcs.size():0[tm0:1507941101823337,tm1:1507941101824031,tm2:1507941101824031(0),tm3:1507941101824033(2),tm4:1507941101824033(2)][tm4-tm0]:696\nfinish 34 frame\n35----rcs.size():0[tm0:1507941101860432,tm1:1507941101861063,tm2:1507941101861063(0),tm3:1507941101861065(2),tm4:1507941101861065(2)][tm4-tm0]:633\nfinish 35 frame\n36----rcs.size():0[tm0:1507941101896282,tm1:1507941101896860,tm2:1507941101896860(0),tm3:1507941101896862(2),tm4:1507941101896862(2)][tm4-tm0]:580\nfinish 36 frame\n37----rcs.size():0[tm0:1507941101932542,tm1:1507941101933090,tm2:1507941101933090(0),tm3:1507941101933092(2),tm4:1507941101933092(2)][tm4-tm0]:550\nfinish 37 frame\n38----rcs.size():0[tm0:1507941101969186,tm1:1507941101969733,tm2:1507941101969733(0),tm3:1507941101969735(2),tm4:1507941101969735(2)][tm4-tm0]:549\nfinish 38 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16516\n39----rcs.size():1[tm0:1507941102004066,tm1:1507941102004649,tm2:1507941102021246(16597),tm3:1507941102021276(16627),tm4:1507941102021277(16628)][tm4-tm0]:17211\nfinish 39 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16412\n40----rcs.size():1[tm0:1507941102052828,tm1:1507941102053378,tm2:1507941102069891(16513),tm3:1507941102069924(16546),tm4:1507941102069924(16546)][tm4-tm0]:17096\nfinish 40 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16506\n41----rcs.size():1[tm0:1507941102101693,tm1:1507941102102317,tm2:1507941102118906(16589),tm3:1507941102118926(16609),tm4:1507941102118951(16634)][tm4-tm0]:17258\nfinish 41 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16291\n42----rcs.size():1[tm0:1507941102150133,tm1:1507941102150684,tm2:1507941102167046(16362),tm3:1507941102167071(16387),tm4:1507941102167077(16393)][tm4-tm0]:16944\nfinish 42 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16547\n43----rcs.size():1[tm0:1507941102202501,tm1:1507941102203155,tm2:1507941102219795(16640),tm3:1507941102219816(16661),tm4:1507941102219823(16668)][tm4-tm0]:17322\nfinish 43 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16280\n44----rcs.size():1[tm0:1507941102251402,tm1:1507941102252005,tm2:1507941102268398(16393),tm3:1507941102268449(16444),tm4:1507941102268456(16451)][tm4-tm0]:17054\nfinish 44 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16436\n45----rcs.size():1[tm0:1507941102299854,tm1:1507941102300509,tm2:1507941102317042(16533),tm3:1507941102317063(16554),tm4:1507941102317069(16560)][tm4-tm0]:17215\nfinish 45 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16291\n46----rcs.size():1[tm0:1507941102348410,tm1:1507941102349107,tm2:1507941102365537(16430),tm3:1507941102365559(16452),tm4:1507941102365565(16458)][tm4-tm0]:17155\nfinish 46 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16439\n47----rcs.size():1[tm0:1507941102396840,tm1:1507941102397725,tm2:1507941102414257(16532),tm3:1507941102414279(16554),tm4:1507941102414286(16561)][tm4-tm0]:17446\nfinish 47 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16443\n48----rcs.size():1[tm0:1507941102450681,tm1:1507941102451380,tm2:1507941102467924(16544),tm3:1507941102467961(16581),tm4:1507941102467973(16593)][tm4-tm0]:17292\nfinish 48 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16444\n49----rcs.size():1[tm0:1507941102503255,tm1:1507941102503933,tm2:1507941102520465(16532),tm3:1507941102520486(16553),tm4:1507941102520501(16568)][tm4-tm0]:17246\nfinish 49 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16386\n50----rcs.size():1[tm0:1507941102552177,tm1:1507941102552834,tm2:1507941102569310(16476),tm3:1507941102569331(16497),tm4:1507941102569337(16503)][tm4-tm0]:17160\nfinish 50 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16402\n51----rcs.size():1[tm0:1507941102599572,tm1:1507941102600198,tm2:1507941102616751(16553),tm3:1507941102616774(16576),tm4:1507941102616781(16583)][tm4-tm0]:17209\nfinish 51 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16502\n52----rcs.size():1[tm0:1507941102650509,tm1:1507941102651148,tm2:1507941102667790(16642),tm3:1507941102667828(16680),tm4:1507941102667836(16688)][tm4-tm0]:17327\nfinish 52 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16316\n53----rcs.size():1[tm0:1507941102700949,tm1:1507941102701578,tm2:1507941102718001(16423),tm3:1507941102718039(16461),tm4:1507941102718046(16468)][tm4-tm0]:17097\nfinish 53 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16548\n54----rcs.size():1[tm0:1507941102749119,tm1:1507941102749798,tm2:1507941102766432(16634),tm3:1507941102766470(16672),tm4:1507941102766477(16679)][tm4-tm0]:17358\nfinish 54 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16394\n55----rcs.size():1[tm0:1507941102801638,tm1:1507941102802235,tm2:1507941102818739(16504),tm3:1507941102818796(16561),tm4:1507941102818803(16568)][tm4-tm0]:17165\nfinish 55 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16351\n56----rcs.size():1[tm0:1507941102851060,tm1:1507941102851670,tm2:1507941102868114(16444),tm3:1507941102868162(16492),tm4:1507941102868187(16517)][tm4-tm0]:17127\nfinish 56 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16421\n57----rcs.size():1[tm0:1507941102899127,tm1:1507941102899720,tm2:1507941102916251(16531),tm3:1507941102916273(16553),tm4:1507941102916297(16577)][tm4-tm0]:17170\nfinish 57 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16405\n58----rcs.size():1[tm0:1507941102953819,tm1:1507941102954414,tm2:1507941102970909(16495),tm3:1507941102970964(16550),tm4:1507941102970987(16573)][tm4-tm0]:17168\nfinish 58 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16435\n59----rcs.size():1[tm0:1507941103002046,tm1:1507941103002693,tm2:1507941103019207(16514),tm3:1507941103019228(16535),tm4:1507941103019234(16541)][tm4-tm0]:17188\nfinish 59 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16308\n60----rcs.size():1[tm0:1507941103053092,tm1:1507941103053697,tm2:1507941103070087(16390),tm3:1507941103070110(16413),tm4:1507941103070116(16419)][tm4-tm0]:17024\nfinish 60 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16257\n61----rcs.size():1[tm0:1507941103100311,tm1:1507941103100863,tm2:1507941103117197(16334),tm3:1507941103117219(16356),tm4:1507941103117226(16363)][tm4-tm0]:16915\nfinish 61 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:15\n(incpp)call encode cost time:tmd-tmc:16471\n62----rcs.size():1[tm0:1507941103150965,tm1:1507941103151502,tm2:1507941103168073(16571),tm3:1507941103168095(16593),tm4:1507941103168101(16599)][tm4-tm0]:17136\nfinish 62 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:16503\n63----rcs.size():1[tm0:1507941103198669,tm1:1507941103199222,tm2:1507941103215807(16585),tm3:1507941103215829(16607),tm4:1507941103215837(16615)][tm4-tm0]:17168\nfinish 63 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17247\n64----rcs.size():1[tm0:1507941103253183,tm1:1507941103254186,tm2:1507941103271536(17350),tm3:1507941103271579(17393),tm4:1507941103271588(17402)][tm4-tm0]:18405\nfinish 64 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17563\n65----rcs.size():1[tm0:1507941103302854,tm1:1507941103303497,tm2:1507941103321156(17659),tm3:1507941103321183(17686),tm4:1507941103321190(17693)][tm4-tm0]:18336\nfinish 65 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17446\n66----rcs.size():1[tm0:1507941103351782,tm1:1507941103352316,tm2:1507941103369858(17542),tm3:1507941103369884(17568),tm4:1507941103369891(17575)][tm4-tm0]:18109\nfinish 66 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17400\n67----rcs.size():1[tm0:1507941103403004,tm1:1507941103403614,tm2:1507941103421109(17495),tm3:1507941103421133(17519),tm4:1507941103421150(17536)][tm4-tm0]:18146\nfinish 67 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17494\n68----rcs.size():1[tm0:1507941103451628,tm1:1507941103452164,tm2:1507941103469757(17593),tm3:1507941103469800(17636),tm4:1507941103469824(17660)][tm4-tm0]:18196\nfinish 68 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17350\n69----rcs.size():1[tm0:1507941103501225,tm1:1507941103501843,tm2:1507941103519320(17477),tm3:1507941103519361(17518),tm4:1507941103519369(17526)][tm4-tm0]:18144\nfinish 69 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17527\n70----rcs.size():1[tm0:1507941103551950,tm1:1507941103552589,tm2:1507941103570209(17620),tm3:1507941103570269(17680),tm4:1507941103570277(17688)][tm4-tm0]:18327\nfinish 70 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17432\n71----rcs.size():1[tm0:1507941103603016,tm1:1507941103603553,tm2:1507941103621071(17518),tm3:1507941103621114(17561),tm4:1507941103621120(17567)][tm4-tm0]:18104\nfinish 71 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17355\n72----rcs.size():1[tm0:1507941103651283,tm1:1507941103651834,tm2:1507941103669286(17452),tm3:1507941103669311(17477),tm4:1507941103669334(17500)][tm4-tm0]:18051\nfinish 72 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17499\n73----rcs.size():1[tm0:1507941103700775,tm1:1507941103701402,tm2:1507941103719039(17637),tm3:1507941103719064(17662),tm4:1507941103719071(17669)][tm4-tm0]:18296\nfinish 73 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17345\n74----rcs.size():2[tm0:1507941103750490,tm1:1507941103751038,tm2:1507941103768465(17427),tm3:1507941103768496(17458),tm4:1507941103768503(17465)][tm4-tm0]:18013\nfinish 74 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17490\n75----rcs.size():2[tm0:1507941103800101,tm1:1507941103800784,tm2:1507941103818401(17617),tm3:1507941103818451(17667),tm4:1507941103818458(17674)][tm4-tm0]:18357\nfinish 75 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17347\n76----rcs.size():2[tm0:1507941103851032,tm1:1507941103851627,tm2:1507941103869077(17450),tm3:1507941103869114(17487),tm4:1507941103869130(17503)][tm4-tm0]:18098\nfinish 76 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17395\n77----rcs.size():2[tm0:1507941103900828,tm1:1507941103901382,tm2:1507941103918944(17562),tm3:1507941103918986(17604),tm4:1507941103919009(17627)][tm4-tm0]:18181\nfinish 77 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17458\n78----rcs.size():2[tm0:1507941103950105,tm1:1507941103950788,tm2:1507941103968342(17554),tm3:1507941103968380(17592),tm4:1507941103968391(17603)][tm4-tm0]:18286\nfinish 78 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17393\n79----rcs.size():2[tm0:1507941103999771,tm1:1507941104000413,tm2:1507941104017902(17489),tm3:1507941104017940(17527),tm4:1507941104017949(17536)][tm4-tm0]:18178\nfinish 79 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17483\n80----rcs.size():2[tm0:1507941104048850,tm1:1507941104049479,tm2:1507941104067060(17581),tm3:1507941104067098(17619),tm4:1507941104067108(17629)][tm4-tm0]:18258\nfinish 80 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17438\n81----rcs.size():2[tm0:1507941104098090,tm1:1507941104098647,tm2:1507941104116193(17546),tm3:1507941104116235(17588),tm4:1507941104116245(17598)][tm4-tm0]:18155\nfinish 81 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17484\n82----rcs.size():2[tm0:1507941104149049,tm1:1507941104149719,tm2:1507941104167327(17608),tm3:1507941104167366(17647),tm4:1507941104167378(17659)][tm4-tm0]:18329\nfinish 82 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17456\n83----rcs.size():2[tm0:1507941104200877,tm1:1507941104201521,tm2:1507941104219069(17548),tm3:1507941104219108(17587),tm4:1507941104219120(17599)][tm4-tm0]:18243\nfinish 83 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17510\n84----rcs.size():2[tm0:1507941104250125,tm1:1507941104250736,tm2:1507941104268368(17632),tm3:1507941104268441(17705),tm4:1507941104268453(17717)][tm4-tm0]:18328\nfinish 84 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17631\n85----rcs.size():2[tm0:1507941104299643,tm1:1507941104300179,tm2:1507941104317920(17741),tm3:1507941104317976(17797),tm4:1507941104317987(17808)][tm4-tm0]:18344\nfinish 85 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17411\n86----rcs.size():2[tm0:1507941104349426,tm1:1507941104350084,tm2:1507941104367595(17511),tm3:1507941104367669(17585),tm4:1507941104367681(17597)][tm4-tm0]:18255\nfinish 86 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17267\n87----rcs.size():2[tm0:1507941104398977,tm1:1507941104399536,tm2:1507941104416907(17371),tm3:1507941104416949(17413),tm4:1507941104416958(17422)][tm4-tm0]:17981\nfinish 87 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17512\n88----rcs.size():2[tm0:1507941104451618,tm1:1507941104452170,tm2:1507941104469833(17663),tm3:1507941104469909(17739),tm4:1507941104469920(17750)][tm4-tm0]:18302\nfinish 88 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17421\n89----rcs.size():2[tm0:1507941104504952,tm1:1507941104505525,tm2:1507941104523097(17572),tm3:1507941104523182(17657),tm4:1507941104523194(17669)][tm4-tm0]:18242\nfinish 89 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17497\n90----rcs.size():2[tm0:1507941104554524,tm1:1507941104555236,tm2:1507941104572834(17598),tm3:1507941104572909(17673),tm4:1507941104572921(17685)][tm4-tm0]:18397\nfinish 90 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17663\n91----rcs.size():2[tm0:1507941104607553,tm1:1507941104608109,tm2:1507941104625896(17787),tm3:1507941104625969(17860),tm4:1507941104625981(17872)][tm4-tm0]:18428\nfinish 91 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17580\n92----rcs.size():2[tm0:1507941104657599,tm1:1507941104658224,tm2:1507941104675955(17731),tm3:1507941104675999(17775),tm4:1507941104676011(17787)][tm4-tm0]:18412\nfinish 92 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17616\n93----rcs.size():2[tm0:1507941104707419,tm1:1507941104707997,tm2:1507941104725723(17726),tm3:1507941104725782(17785),tm4:1507941104725791(17794)][tm4-tm0]:18372\nfinish 93 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17742\n94----rcs.size():2[tm0:1507941104761697,tm1:1507941104762341,tm2:1507941104780177(17836),tm3:1507941104780238(17897),tm4:1507941104780248(17907)][tm4-tm0]:18551\nfinish 94 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17604\n95----rcs.size():2[tm0:1507941104811233,tm1:1507941104811805,tm2:1507941104829529(17724),tm3:1507941104829589(17784),tm4:1507941104829600(17795)][tm4-tm0]:18367\nfinish 95 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17504\n96----rcs.size():2[tm0:1507941104860065,tm1:1507941104860641,tm2:1507941104878249(17608),tm3:1507941104878294(17653),tm4:1507941104878306(17665)][tm4-tm0]:18241\nfinish 96 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17544\n97----rcs.size():2[tm0:1507941104909342,tm1:1507941104909895,tm2:1507941104927534(17639),tm3:1507941104927580(17685),tm4:1507941104927589(17694)][tm4-tm0]:18247\nfinish 97 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17401\n98----rcs.size():2[tm0:1507941104958269,tm1:1507941104958834,tm2:1507941104976344(17510),tm3:1507941104976389(17555),tm4:1507941104976399(17565)][tm4-tm0]:18130\nfinish 98 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17537\n99----rcs.size():2[tm0:1507941105006782,tm1:1507941105007322,tm2:1507941105024996(17674),tm3:1507941105025058(17736),tm4:1507941105025068(17746)][tm4-tm0]:18286\nfinish 99 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17433\n100----rcs.size():3[tm0:1507941105055319,tm1:1507941105055909,tm2:1507941105073445(17536),tm3:1507941105073515(17606),tm4:1507941105073525(17616)][tm4-tm0]:18206\nfinish 100 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17493\n101----rcs.size():3[tm0:1507941105105031,tm1:1507941105105680,tm2:1507941105123283(17603),tm3:1507941105123359(17679),tm4:1507941105123385(17705)][tm4-tm0]:18354\nfinish 101 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17547\n102----rcs.size():3[tm0:1507941105159897,tm1:1507941105160474,tm2:1507941105178122(17648),tm3:1507941105178204(17730),tm4:1507941105178216(17742)][tm4-tm0]:18319\nfinish 102 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17541\n103----rcs.size():3[tm0:1507941105208108,tm1:1507941105208672,tm2:1507941105226321(17649),tm3:1507941105226403(17731),tm4:1507941105226416(17744)][tm4-tm0]:18308\nfinish 103 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17356\n104----rcs.size():3[tm0:1507941105260530,tm1:1507941105261104,tm2:1507941105278564(17460),tm3:1507941105278638(17534),tm4:1507941105278651(17547)][tm4-tm0]:18121\nfinish 104 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17440\n105----rcs.size():3[tm0:1507941105311475,tm1:1507941105312047,tm2:1507941105329586(17539),tm3:1507941105329641(17594),tm4:1507941105329654(17607)][tm4-tm0]:18179\nfinish 105 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17351\n106----rcs.size():3[tm0:1507941105359628,tm1:1507941105360171,tm2:1507941105377631(17460),tm3:1507941105377690(17519),tm4:1507941105377705(17534)][tm4-tm0]:18077\nfinish 106 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17512\n107----rcs.size():3[tm0:1507941105408977,tm1:1507941105409698,tm2:1507941105427330(17632),tm3:1507941105427406(17708),tm4:1507941105427422(17724)][tm4-tm0]:18445\nfinish 107 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17733\n108----rcs.size():3[tm0:1507941105460694,tm1:1507941105461363,tm2:1507941105479221(17858),tm3:1507941105479283(17920),tm4:1507941105479298(17935)][tm4-tm0]:18604\nfinish 108 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17412\n109----rcs.size():3[tm0:1507941105511120,tm1:1507941105511711,tm2:1507941105529232(17521),tm3:1507941105529293(17582),tm4:1507941105529317(17606)][tm4-tm0]:18197\nfinish 109 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17620\n110----rcs.size():3[tm0:1507941105560551,tm1:1507941105561217,tm2:1507941105578953(17736),tm3:1507941105579016(17799),tm4:1507941105579033(17816)][tm4-tm0]:18482\nfinish 110 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17631\n111----rcs.size():3[tm0:1507941105610627,tm1:1507941105611185,tm2:1507941105628946(17761),tm3:1507941105629028(17843),tm4:1507941105629044(17859)][tm4-tm0]:18417\nfinish 111 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17604\n112----rcs.size():3[tm0:1507941105659871,tm1:1507941105660521,tm2:1507941105678248(17727),tm3:1507941105678311(17790),tm4:1507941105678328(17807)][tm4-tm0]:18457\nfinish 112 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17588\n113----rcs.size():3[tm0:1507941105709006,tm1:1507941105709778,tm2:1507941105727506(17728),tm3:1507941105727589(17811),tm4:1507941105727605(17827)][tm4-tm0]:18599\nfinish 113 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17501\n114----rcs.size():3[tm0:1507941105758084,tm1:1507941105758734,tm2:1507941105776393(17659),tm3:1507941105776493(17759),tm4:1507941105776509(17775)][tm4-tm0]:18425\nfinish 114 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17671\n115----rcs.size():3[tm0:1507941105811905,tm1:1507941105812501,tm2:1507941105830287(17786),tm3:1507941105830369(17868),tm4:1507941105830385(17884)][tm4-tm0]:18480\nfinish 115 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17502\n116----rcs.size():2[tm0:1507941105860142,tm1:1507941105860676,tm2:1507941105878295(17619),tm3:1507941105878400(17724),tm4:1507941105878411(17735)][tm4-tm0]:18269\nfinish 116 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17585\n117\n117----rcs.size():2[tm0:1507941105908170,tm1:1507941105908690,tm2:1507941105926389(17699),tm3:1507941105926472(17782),tm4:1507941105926483(17793)][tm4-tm0]:18313\nfinish 117 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17654\n118----rcs.size():2[tm0:1507941105956652,tm1:1507941105957230,tm2:1507941105975054(17824),tm3:1507941105975101(17871),tm4:1507941105975112(17882)][tm4-tm0]:18460\nfinish 118 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17588\n119----rcs.size():2[tm0:1507941106005110,tm1:1507941106005682,tm2:1507941106023426(17744),tm3:1507941106023491(17809),tm4:1507941106023501(17819)][tm4-tm0]:18391\nfinish 119 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17703\n120----rcs.size():2[tm0:1507941106054678,tm1:1507941106055272,tm2:1507941106073100(17828),tm3:1507941106073161(17889),tm4:1507941106073188(17916)][tm4-tm0]:18510\nfinish 120 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17440\n121----rcs.size():2[tm0:1507941106109393,tm1:1507941106109946,tm2:1507941106127525(17579),tm3:1507941106127593(17647),tm4:1507941106127604(17658)][tm4-tm0]:18211\nfinish 121 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17699\n122----rcs.size():2[tm0:1507941106158514,tm1:1507941106159130,tm2:1507941106176961(17831),tm3:1507941106177011(17881),tm4:1507941106177022(17892)][tm4-tm0]:18508\nfinish 122 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17622\n123----rcs.size():2[tm0:1507941106207855,tm1:1507941106208484,tm2:1507941106226238(17754),tm3:1507941106226296(17812),tm4:1507941106226310(17826)][tm4-tm0]:18455\nfinish 123 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17433\n124----rcs.size():3[tm0:1507941106257567,tm1:1507941106258243,tm2:1507941106275789(17546),tm3:1507941106275896(17653),tm4:1507941106275910(17667)][tm4-tm0]:18343\nfinish 124 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17486\n125----rcs.size():3[tm0:1507941106306874,tm1:1507941106307452,tm2:1507941106325042(17590),tm3:1507941106325162(17710),tm4:1507941106325175(17723)][tm4-tm0]:18301\nfinish 125 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17637\n126----rcs.size():3[tm0:1507941106356797,tm1:1507941106357427,tm2:1507941106375199(17772),tm3:1507941106375276(17849),tm4:1507941106375292(17865)][tm4-tm0]:18495\nfinish 126 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17975\n127----rcs.size():3[tm0:1507941106411642,tm1:1507941106412185,tm2:1507941106430283(18098),tm3:1507941106430364(18179),tm4:1507941106430380(18195)][tm4-tm0]:18738\nfinish 127 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17615\n128----rcs.size():3[tm0:1507941106466190,tm1:1507941106466763,tm2:1507941106484500(17737),tm3:1507941106484564(17801),tm4:1507941106484613(17850)][tm4-tm0]:18423\nfinish 128 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17560\n129----rcs.size():3[tm0:1507941106522751,tm1:1507941106523325,tm2:1507941106541051(17726),tm3:1507941106541115(17790),tm4:1507941106541133(17808)][tm4-tm0]:18382\nfinish 129 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17658\n130----rcs.size():3[tm0:1507941106572631,tm1:1507941106573186,tm2:1507941106590961(17775),tm3:1507941106591065(17879),tm4:1507941106591103(17917)][tm4-tm0]:18472\nfinish 130 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17605\n131----rcs.size():3[tm0:1507941106622110,tm1:1507941106622702,tm2:1507941106640424(17722),tm3:1507941106640510(17808),tm4:1507941106640525(17823)][tm4-tm0]:18415\nfinish 131 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17440\n132----rcs.size():3[tm0:1507941106675415,tm1:1507941106676027,tm2:1507941106693623(17596),tm3:1507941106693704(17677),tm4:1507941106693719(17692)][tm4-tm0]:18304\nfinish 132 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17796\n133----rcs.size():3[tm0:1507941106729473,tm1:1507941106730356,tm2:1507941106748338(17982),tm3:1507941106748422(18066),tm4:1507941106748438(18082)][tm4-tm0]:18965\nfinish 133 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17617\n134----rcs.size():2[tm0:1507941106781632,tm1:1507941106782225,tm2:1507941106799987(17762),tm3:1507941106800058(17833),tm4:1507941106800071(17846)][tm4-tm0]:18439\nfinish 134 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17658\n135----rcs.size():2[tm0:1507941106831325,tm1:1507941106831922,tm2:1507941106849709(17787),tm3:1507941106849782(17860),tm4:1507941106849795(17873)][tm4-tm0]:18470\nfinish 135 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17730\n136----rcs.size():2[tm0:1507941106881445,tm1:1507941106882057,tm2:1507941106899978(17921),tm3:1507941106900035(17978),tm4:1507941106900049(17992)][tm4-tm0]:18604\nfinish 136 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17922\n137----rcs.size():2[tm0:1507941106931296,tm1:1507941106931906,tm2:1507941106949984(18078),tm3:1507941106950042(18136),tm4:1507941106950055(18149)][tm4-tm0]:18759\nfinish 137 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17670\n138----rcs.size():2[tm0:1507941106981500,tm1:1507941106982054,tm2:1507941106999884(17830),tm3:1507941106999991(17937),tm4:1507941107000005(17951)][tm4-tm0]:18505\nfinish 138 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17616\n139----rcs.size():2[tm0:1507941107031503,tm1:1507941107032061,tm2:1507941107049898(17837),tm3:1507941107049987(17926),tm4:1507941107050001(17940)][tm4-tm0]:18498\nfinish 139 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17725\n140----rcs.size():2[tm0:1507941107081725,tm1:1507941107082299,tm2:1507941107100209(17910),tm3:1507941107100284(17985),tm4:1507941107100323(18024)][tm4-tm0]:18598\nfinish 140 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17724\n141----rcs.size():2[tm0:1507941107131832,tm1:1507941107132413,tm2:1507941107150371(17958),tm3:1507941107150430(18017),tm4:1507941107150446(18033)][tm4-tm0]:18614\nfinish 141 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17662\n142----rcs.size():2[tm0:1507941107184323,tm1:1507941107184872,tm2:1507941107202768(17896),tm3:1507941107202828(17956),tm4:1507941107202844(17972)][tm4-tm0]:18521\nfinish 142 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17668\n143----rcs.size():2[tm0:1507941107234270,tm1:1507941107234835,tm2:1507941107252670(17835),tm3:1507941107252731(17896),tm4:1507941107252747(17912)][tm4-tm0]:18477\nfinish 143 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17635\n144----rcs.size():3[tm0:1507941107284373,tm1:1507941107284928,tm2:1507941107302787(17859),tm3:1507941107302873(17945),tm4:1507941107302884(17956)][tm4-tm0]:18511\nfinish 144 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17718\n145----rcs.size():3[tm0:1507941107334262,tm1:1507941107334816,tm2:1507941107352705(17889),tm3:1507941107352810(17994),tm4:1507941107352822(18006)][tm4-tm0]:18560\nfinish 145 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17502\n146----rcs.size():3[tm0:1507941107384529,tm1:1507941107385149,tm2:1507941107402802(17653),tm3:1507941107402892(17743),tm4:1507941107402907(17758)][tm4-tm0]:18378\nfinish 146 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17732\n147----rcs.size():4[tm0:1507941107434776,tm1:1507941107435396,tm2:1507941107453276(17880),tm3:1507941107453366(17970),tm4:1507941107453381(17985)][tm4-tm0]:18605\nfinish 147 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17712\n148----rcs.size():4[tm0:1507941107484947,tm1:1507941107485506,tm2:1507941107503418(17912),tm3:1507941107503513(18007),tm4:1507941107503526(18020)][tm4-tm0]:18579\nfinish 148 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17791\n149----rcs.size():4[tm0:1507941107535355,tm1:1507941107535968,tm2:1507941107553947(17979),tm3:1507941107554028(18060),tm4:1507941107554048(18080)][tm4-tm0]:18693\nfinish 149 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17651\n150----rcs.size():4[tm0:1507941107585158,tm1:1507941107585731,tm2:1507941107603574(17843),tm3:1507941107603670(17939),tm4:1507941107603690(17959)][tm4-tm0]:18532\nfinish 150 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17619\n151----rcs.size():4[tm0:1507941107633797,tm1:1507941107634390,tm2:1507941107652176(17786),tm3:1507941107652270(17880),tm4:1507941107652287(17897)][tm4-tm0]:18490\nfinish 151 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17640\n152----rcs.size():3[tm0:1507941107682665,tm1:1507941107683219,tm2:1507941107701013(17794),tm3:1507941107701127(17908),tm4:1507941107701155(17936)][tm4-tm0]:18490\nfinish 152 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17590\n153----rcs.size():3[tm0:1507941107731832,tm1:1507941107732448,tm2:1507941107750197(17749),tm3:1507941107750275(17827),tm4:1507941107750293(17845)][tm4-tm0]:18461\nfinish 153 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17897\n154----rcs.size():3[tm0:1507941107781072,tm1:1507941107781760,tm2:1507941107799817(18057),tm3:1507941107799916(18156),tm4:1507941107799937(18177)][tm4-tm0]:18865\nfinish 154 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17755\n155----rcs.size():4[tm0:1507941107830408,tm1:1507941107831112,tm2:1507941107849166(18054),tm3:1507941107849269(18157),tm4:1507941107849292(18180)][tm4-tm0]:18884\nfinish 155 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17802\n156----rcs.size():5[tm0:1507941107880315,tm1:1507941107881003,tm2:1507941107899012(18009),tm3:1507941107899106(18103),tm4:1507941107899128(18125)][tm4-tm0]:18813\nfinish 156 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17683\n157----rcs.size():5[tm0:1507941107929681,tm1:1507941107930389,tm2:1507941107948281(17892),tm3:1507941107948411(18022),tm4:1507941107948433(18044)][tm4-tm0]:18752\nfinish 157 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17885\n158----rcs.size():5[tm0:1507941107978621,tm1:1507941107979183,tm2:1507941107997523(18340),tm3:1507941107997639(18456),tm4:1507941107997663(18480)][tm4-tm0]:19042\nfinish 158 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18122\n159----rcs.size():5[tm0:1507941108028003,tm1:1507941108028563,tm2:1507941108046867(18304),tm3:1507941108046982(18419),tm4:1507941108047007(18444)][tm4-tm0]:19004\nfinish 159 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17869\n160----rcs.size():5[tm0:1507941108077549,tm1:1507941108078152,tm2:1507941108096197(18045),tm3:1507941108096323(18171),tm4:1507941108096349(18197)][tm4-tm0]:18800\nfinish 160 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17727\n161----rcs.size():5[tm0:1507941108130965,tm1:1507941108131641,tm2:1507941108149564(17923),tm3:1507941108149680(18039),tm4:1507941108149703(18062)][tm4-tm0]:18738\nfinish 161 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17621\n162----rcs.size():5[tm0:1507941108183222,tm1:1507941108183794,tm2:1507941108201631(17837),tm3:1507941108201750(17956),tm4:1507941108201776(17982)][tm4-tm0]:18554\nfinish 162 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17567\n163----rcs.size():5[tm0:1507941108232545,tm1:1507941108233170,tm2:1507941108250925(17755),tm3:1507941108251064(17894),tm4:1507941108251089(17919)][tm4-tm0]:18544\nfinish 163 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17672\n164----rcs.size():5[tm0:1507941108281839,tm1:1507941108282527,tm2:1507941108300383(17856),tm3:1507941108300487(17960),tm4:1507941108300516(17989)][tm4-tm0]:18677\nfinish 164 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17792\n165----rcs.size():5[tm0:1507941108331835,tm1:1507941108332469,tm2:1507941108350450(17981),tm3:1507941108350583(18114),tm4:1507941108350659(18190)][tm4-tm0]:18824\nfinish 165 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17878\n166----rcs.size():5[tm0:1507941108381958,tm1:1507941108382559,tm2:1507941108400636(18077),tm3:1507941108400744(18185),tm4:1507941108400826(18267)][tm4-tm0]:18868\nfinish 166 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17774\n167----rcs.size():5[tm0:1507941108434913,tm1:1507941108435477,tm2:1507941108453462(17985),tm3:1507941108453589(18112),tm4:1507941108453672(18195)][tm4-tm0]:18759\nfinish 167 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17694\n168----rcs.size():5[tm0:1507941108488831,tm1:1507941108489447,tm2:1507941108507331(17884),tm3:1507941108507479(18032),tm4:1507941108507506(18059)][tm4-tm0]:18675\nfinish 168 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17948\n169----rcs.size():5[tm0:1507941108543850,tm1:1507941108544471,tm2:1507941108562649(18178),tm3:1507941108562776(18305),tm4:1507941108562803(18332)][tm4-tm0]:18953\nfinish 169 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17991\n170----rcs.size():5[tm0:1507941108593076,tm1:1507941108593657,tm2:1507941108611885(18228),tm3:1507941108611996(18339),tm4:1507941108612017(18360)][tm4-tm0]:18941\nfinish 170 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17787\n171----rcs.size():5[tm0:1507941108647451,tm1:1507941108648030,tm2:1507941108666059(18029),tm3:1507941108666200(18170),tm4:1507941108666228(18198)][tm4-tm0]:18777\nfinish 171 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17825\n172----rcs.size():5[tm0:1507941108697329,tm1:1507941108697889,tm2:1507941108715920(18031),tm3:1507941108716068(18179),tm4:1507941108716095(18206)][tm4-tm0]:18766\nfinish 172 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17810\n173----rcs.size():5[tm0:1507941108746679,tm1:1507941108747414,tm2:1507941108765448(18034),tm3:1507941108765581(18167),tm4:1507941108765602(18188)][tm4-tm0]:18923\nfinish 173 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17926\n174----rcs.size():5[tm0:1507941108796486,tm1:1507941108797163,tm2:1507941108815385(18222),tm3:1507941108815517(18354),tm4:1507941108815539(18376)][tm4-tm0]:19053\nfinish 174 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17777\n175----rcs.size():5[tm0:1507941108851730,tm1:1507941108852371,tm2:1507941108870364(17993),tm3:1507941108870498(18127),tm4:1507941108870527(18156)][tm4-tm0]:18797\nfinish 175 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17766\n176----rcs.size():5[tm0:1507941108901216,tm1:1507941108901830,tm2:1507941108919804(17974),tm3:1507941108919945(18115),tm4:1507941108919974(18144)][tm4-tm0]:18758\nfinish 176 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17690\n177----rcs.size():5[tm0:1507941108950890,tm1:1507941108951509,tm2:1507941108969397(17888),tm3:1507941108969515(18006),tm4:1507941108969536(18027)][tm4-tm0]:18646\nfinish 177 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18042\n178----rcs.size():5[tm0:1507941109003637,tm1:1507941109004256,tm2:1507941109022551(18295),tm3:1507941109022691(18435),tm4:1507941109022719(18463)][tm4-tm0]:19082\nfinish 178 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17781\n179----rcs.size():5[tm0:1507941109053669,tm1:1507941109054346,tm2:1507941109072363(18017),tm3:1507941109072521(18175),tm4:1507941109072550(18204)][tm4-tm0]:18881\nfinish 179 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17881\n180----rcs.size():5[tm0:1507941109103793,tm1:1507941109104434,tm2:1507941109122591(18157),tm3:1507941109122746(18312),tm4:1507941109122773(18339)][tm4-tm0]:18980\nfinish 180 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17921\n181----rcs.size():5[tm0:1507941109153529,tm1:1507941109154147,tm2:1507941109172372(18225),tm3:1507941109172545(18398),tm4:1507941109172576(18429)][tm4-tm0]:19047\nfinish 181 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18003\n182----rcs.size():5[tm0:1507941109203526,tm1:1507941109204183,tm2:1507941109222446(18263),tm3:1507941109222572(18389),tm4:1507941109222607(18424)][tm4-tm0]:19081\nfinish 182 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17950\n183----rcs.size():5[tm0:1507941109253119,tm1:1507941109253700,tm2:1507941109271921(18221),tm3:1507941109272065(18365),tm4:1507941109272087(18387)][tm4-tm0]:18968\nfinish 183 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17931\n184----rcs.size():6[tm0:1507941109302825,tm1:1507941109303461,tm2:1507941109321649(18188),tm3:1507941109321807(18346),tm4:1507941109321835(18374)][tm4-tm0]:19010\nfinish 184 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17892\n185----rcs.size():6[tm0:1507941109352510,tm1:1507941109353091,tm2:1507941109371287(18196),tm3:1507941109371472(18381),tm4:1507941109371507(18416)][tm4-tm0]:18997\nfinish 185 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18024\n186----rcs.size():6[tm0:1507941109401972,tm1:1507941109402551,tm2:1507941109420884(18333),tm3:1507941109421045(18494),tm4:1507941109421080(18529)][tm4-tm0]:19108\nfinish 186 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17943\n187----rcs.size():6[tm0:1507941109451692,tm1:1507941109452290,tm2:1507941109470577(18287),tm3:1507941109470745(18455),tm4:1507941109470781(18491)][tm4-tm0]:19089\nfinish 187 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17832\n188----rcs.size():6[tm0:1507941109501543,tm1:1507941109502181,tm2:1507941109520278(18097),tm3:1507941109520444(18263),tm4:1507941109520470(18289)][tm4-tm0]:18927\nfinish 188 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17796\n189----rcs.size():6[tm0:1507941109551832,tm1:1507941109552444,tm2:1507941109570499(18055),tm3:1507941109570704(18260),tm4:1507941109570815(18371)][tm4-tm0]:18983\nfinish 189 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18041\n190----rcs.size():6[tm0:1507941109601028,tm1:1507941109601638,tm2:1507941109619949(18311),tm3:1507941109620110(18472),tm4:1507941109620135(18497)][tm4-tm0]:19107\nfinish 190 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17840\n191----rcs.size():6[tm0:1507941109649938,tm1:1507941109650520,tm2:1507941109668632(18112),tm3:1507941109668795(18275),tm4:1507941109668821(18301)][tm4-tm0]:18883\nfinish 191 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18000\n192----rcs.size():6[tm0:1507941109698896,tm1:1507941109699482,tm2:1507941109717741(18259),tm3:1507941109717921(18439),tm4:1507941109717948(18466)][tm4-tm0]:19052\nfinish 192 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18023\n193----rcs.size():6[tm0:1507941109748554,tm1:1507941109749134,tm2:1507941109767491(18357),tm3:1507941109767646(18512),tm4:1507941109767674(18540)][tm4-tm0]:19120\nfinish 193 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17904\n194----rcs.size():6[tm0:1507941109798023,tm1:1507941109798618,tm2:1507941109816826(18208),tm3:1507941109817007(18389),tm4:1507941109817051(18433)][tm4-tm0]:19028\nfinish 194 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18109\n195----rcs.size():6[tm0:1507941109849125,tm1:1507941109849834,tm2:1507941109868259(18425),tm3:1507941109868426(18592),tm4:1507941109868548(18714)][tm4-tm0]:19423\nfinish 195 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18123\n196----rcs.size():6[tm0:1507941109899025,tm1:1507941109899655,tm2:1507941109918084(18429),tm3:1507941109918330(18675),tm4:1507941109918368(18713)][tm4-tm0]:19343\nfinish 196 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18263\n197----rcs.size():6[tm0:1507941109950633,tm1:1507941109951199,tm2:1507941109969756(18557),tm3:1507941109969922(18723),tm4:1507941109969958(18759)][tm4-tm0]:19325\nfinish 197 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18053\n198----rcs.size():6[tm0:1507941110000927,tm1:1507941110001494,tm2:1507941110019846(18352),tm3:1507941110020028(18534),tm4:1507941110020064(18570)][tm4-tm0]:19137\nfinish 198 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18246\n199----rcs.size():6[tm0:1507941110051117,tm1:1507941110051804,tm2:1507941110070399(18595),tm3:1507941110070630(18826),tm4:1507941110070666(18862)][tm4-tm0]:19549\nfinish 199 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18098\n200----rcs.size():6[tm0:1507941110101382,tm1:1507941110101964,tm2:1507941110120411(18447),tm3:1507941110120594(18630),tm4:1507941110120622(18658)][tm4-tm0]:19240\nfinish 200 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18094\n201----rcs.size():6[tm0:1507941110148955,tm1:1507941110149524,tm2:1507941110167939(18415),tm3:1507941110168120(18596),tm4:1507941110168159(18635)][tm4-tm0]:19204\nfinish 201 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18539\n202----rcs.size():6[tm0:1507941110197793,tm1:1507941110198379,tm2:1507941110217297(18918),tm3:1507941110217486(19107),tm4:1507941110217524(19145)][tm4-tm0]:19731\nfinish 202 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18191\n203----rcs.size():6[tm0:1507941110249761,tm1:1507941110250330,tm2:1507941110268847(18517),tm3:1507941110269036(18706),tm4:1507941110269076(18746)][tm4-tm0]:19315\nfinish 203 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18442\n204----rcs.size():6[tm0:1507941110299854,tm1:1507941110300496,tm2:1507941110319304(18808),tm3:1507941110319514(19018),tm4:1507941110319564(19068)][tm4-tm0]:19710\nfinish 204 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18275\n205----rcs.size():6[tm0:1507941110349225,tm1:1507941110349816,tm2:1507941110368433(18617),tm3:1507941110368632(18816),tm4:1507941110368671(18855)][tm4-tm0]:19446\nfinish 205 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18286\n206----rcs.size():6[tm0:1507941110398767,tm1:1507941110399360,tm2:1507941110418009(18649),tm3:1507941110418229(18869),tm4:1507941110418269(18909)][tm4-tm0]:19502\nfinish 206 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18337\n207----rcs.size():6[tm0:1507941110448332,tm1:1507941110448943,tm2:1507941110467684(18741),tm3:1507941110467890(18947),tm4:1507941110467920(18977)][tm4-tm0]:19588\nfinish 207 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18301\n208----rcs.size():6[tm0:1507941110500294,tm1:1507941110500839,tm2:1507941110519524(18685),tm3:1507941110519737(18898),tm4:1507941110519768(18929)][tm4-tm0]:19474\nfinish 208 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18530\n209----rcs.size():6[tm0:1507941110549940,tm1:1507941110550596,tm2:1507941110569500(18904),tm3:1507941110569697(19101),tm4:1507941110569727(19131)][tm4-tm0]:19787\nfinish 209 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18280\n210----rcs.size():7[tm0:1507941110599549,tm1:1507941110600174,tm2:1507941110618824(18650),tm3:1507941110619020(18846),tm4:1507941110619049(18875)][tm4-tm0]:19500\nfinish 210 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18458\n211----rcs.size():7[tm0:1507941110649195,tm1:1507941110649792,tm2:1507941110668668(18876),tm3:1507941110668868(19076),tm4:1507941110668898(19106)][tm4-tm0]:19703\nfinish 211 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18478\n212----rcs.size():7[tm0:1507941110699050,tm1:1507941110699660,tm2:1507941110718561(18901),tm3:1507941110718783(19123),tm4:1507941110718829(19169)][tm4-tm0]:19779\nfinish 212 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18432\n213----rcs.size():7[tm0:1507941110749105,tm1:1507941110749693,tm2:1507941110768607(18914),tm3:1507941110768815(19122),tm4:1507941110768848(19155)][tm4-tm0]:19743\nfinish 213 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18511\n214----rcs.size():7[tm0:1507941110798878,tm1:1507941110799486,tm2:1507941110818406(18920),tm3:1507941110818643(19157),tm4:1507941110818688(19202)][tm4-tm0]:19810\nfinish 214 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18689\n215----rcs.size():7[tm0:1507941110849147,tm1:1507941110849814,tm2:1507941110868981(19167),tm3:1507941110869211(19397),tm4:1507941110869358(19544)][tm4-tm0]:20211\nfinish 215 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18536\n216----rcs.size():7[tm0:1507941110899876,tm1:1507941110900584,tm2:1507941110919594(19010),tm3:1507941110919831(19247),tm4:1507941110919876(19292)][tm4-tm0]:20000\nfinish 216 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18627\n217----rcs.size():7[tm0:1507941110949734,tm1:1507941110950360,tm2:1507941110969470(19110),tm3:1507941110969685(19325),tm4:1507941110969728(19368)][tm4-tm0]:19994\nfinish 217 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18580\n218----rcs.size():7[tm0:1507941111000197,tm1:1507941111000801,tm2:1507941111019863(19062),tm3:1507941111020097(19296),tm4:1507941111020151(19350)][tm4-tm0]:19954\nfinish 218 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19316\n219----rcs.size():6[tm0:1507941111050680,tm1:1507941111051389,tm2:1507941111071266(19877),tm3:1507941111071493(20104),tm4:1507941111071535(20146)][tm4-tm0]:20855\nfinish 219 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18747\n220----rcs.size():6[tm0:1507941111103109,tm1:1507941111104104,tm2:1507941111123387(19283),tm3:1507941111123592(19488),tm4:1507941111123638(19534)][tm4-tm0]:20529\nfinish 220 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18449\n221----rcs.size():6[tm0:1507941111154031,tm1:1507941111154627,tm2:1507941111173540(18913),tm3:1507941111173754(19127),tm4:1507941111173815(19188)][tm4-tm0]:19784\nfinish 221 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18605\n222----rcs.size():6[tm0:1507941111204648,tm1:1507941111205357,tm2:1507941111224433(19076),tm3:1507941111224633(19276),tm4:1507941111224692(19335)][tm4-tm0]:20044\nfinish 222 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19309\n223----rcs.size():6[tm0:1507941111254487,tm1:1507941111255046,tm2:1507941111275077(20031),tm3:1507941111275290(20244),tm4:1507941111275336(20290)][tm4-tm0]:20849\nfinish 223 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18562\n224----rcs.size():6[tm0:1507941111306290,tm1:1507941111307291,tm2:1507941111326322(19031),tm3:1507941111326525(19234),tm4:1507941111326556(19265)][tm4-tm0]:20266\nfinish 224 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19492\n225----rcs.size():6[tm0:1507941111359652,tm1:1507941111360364,tm2:1507941111380653(20289),tm3:1507941111380864(20500),tm4:1507941111380894(20530)][tm4-tm0]:21242\nfinish 225 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19299\n226----rcs.size():7[tm0:1507941111411556,tm1:1507941111412698,tm2:1507941111432889(20191),tm3:1507941111433134(20436),tm4:1507941111433179(20481)][tm4-tm0]:21623\nfinish 226 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19347\n227----rcs.size():7[tm0:1507941111466969,tm1:1507941111467864,tm2:1507941111488178(20314),tm3:1507941111488415(20551),tm4:1507941111488467(20603)][tm4-tm0]:21498\nfinish 227 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19213\n228----rcs.size():7[tm0:1507941111522933,tm1:1507941111523942,tm2:1507941111544147(20205),tm3:1507941111544400(20458),tm4:1507941111544451(20509)][tm4-tm0]:21518\nfinish 228 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19320\n229----rcs.size():7[tm0:1507941111576114,tm1:1507941111577171,tm2:1507941111596990(19819),tm3:1507941111597238(20067),tm4:1507941111597306(20135)][tm4-tm0]:21192\nfinish 229 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18560\n230----rcs.size():8[tm0:1507941111629140,tm1:1507941111629802,tm2:1507941111648824(19022),tm3:1507941111649108(19306),tm4:1507941111649279(19477)][tm4-tm0]:20139\nfinish 230 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19364\n231----rcs.size():8[tm0:1507941111680354,tm1:1507941111680928,tm2:1507941111700996(20068),tm3:1507941111701276(20348),tm4:1507941111701335(20407)][tm4-tm0]:20981\nfinish 231 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19423\n232----rcs.size():8[tm0:1507941111733694,tm1:1507941111734735,tm2:1507941111755076(20341),tm3:1507941111755369(20634),tm4:1507941111755553(20818)][tm4-tm0]:21859\nfinish 232 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19296\n233----rcs.size():8[tm0:1507941111787160,tm1:1507941111788170,tm2:1507941111808340(20170),tm3:1507941111808593(20423),tm4:1507941111808650(20480)][tm4-tm0]:21490\nfinish 233 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19659\n234----rcs.size():8[tm0:1507941111840336,tm1:1507941111841271,tm2:1507941111862047(20776),tm3:1507941111862309(21038),tm4:1507941111862370(21099)][tm4-tm0]:22034\nfinish 234 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19808\n235----rcs.size():8[tm0:1507941111893234,tm1:1507941111894166,tm2:1507941111914869(20703),tm3:1507941111915112(20946),tm4:1507941111915162(20996)][tm4-tm0]:21928\nfinish 235 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19575\n236----rcs.size():8[tm0:1507941111946109,tm1:1507941111947141,tm2:1507941111967706(20565),tm3:1507941111967952(20811),tm4:1507941111967990(20849)][tm4-tm0]:21881\nfinish 236 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19622\n237----rcs.size():8[tm0:1507941111999182,tm1:1507941112000194,tm2:1507941112020851(20657),tm3:1507941112021107(20913),tm4:1507941112021176(20982)][tm4-tm0]:21994\nfinish 237 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19299\n238----rcs.size():8[tm0:1507941112052304,tm1:1507941112053335,tm2:1507941112073769(20434),tm3:1507941112074042(20707),tm4:1507941112074099(20764)][tm4-tm0]:21795\nfinish 238 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18008\n239----rcs.size():7[tm0:1507941112105717,tm1:1507941112106715,tm2:1507941112124984(18269),tm3:1507941112125265(18550),tm4:1507941112125312(18597)][tm4-tm0]:19595\nfinish 239 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17812\n240----rcs.size():7[tm0:1507941112155556,tm1:1507941112156285,tm2:1507941112174366(18081),tm3:1507941112174571(18286),tm4:1507941112174625(18340)][tm4-tm0]:19069\nfinish 240 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18318\n241----rcs.size():7[tm0:1507941112208715,tm1:1507941112209443,tm2:1507941112228069(18626),tm3:1507941112228299(18856),tm4:1507941112228346(18903)][tm4-tm0]:19631\nfinish 241 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18241\n242----rcs.size():7[tm0:1507941112260917,tm1:1507941112261605,tm2:1507941112280295(18690),tm3:1507941112280535(18930),tm4:1507941112280583(18978)][tm4-tm0]:19666\nfinish 242 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18148\n243----rcs.size():7[tm0:1507941112310856,tm1:1507941112311526,tm2:1507941112330152(18626),tm3:1507941112330379(18853),tm4:1507941112330424(18898)][tm4-tm0]:19568\nfinish 243 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18125\n244----rcs.size():7[tm0:1507941112361097,tm1:1507941112362198,tm2:1507941112380675(18477),tm3:1507941112380901(18703),tm4:1507941112380945(18747)][tm4-tm0]:19848\nfinish 244 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18062\n245----rcs.size():7[tm0:1507941112411632,tm1:1507941112412518,tm2:1507941112430857(18339),tm3:1507941112431101(18583),tm4:1507941112431155(18637)][tm4-tm0]:19523\nfinish 245 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18026\n246----rcs.size():7[tm0:1507941112461303,tm1:1507941112462212,tm2:1507941112480524(18312),tm3:1507941112480753(18541),tm4:1507941112480799(18587)][tm4-tm0]:19496\nfinish 246 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17988\n247----rcs.size():7[tm0:1507941112511166,tm1:1507941112511953,tm2:1507941112530353(18400),tm3:1507941112530580(18627),tm4:1507941112530627(18674)][tm4-tm0]:19461\nfinish 247 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18206\n248----rcs.size():7[tm0:1507941112560862,tm1:1507941112561536,tm2:1507941112580294(18758),tm3:1507941112580522(18986),tm4:1507941112580554(19018)][tm4-tm0]:19692\nfinish 248 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18433\n249----rcs.size():7[tm0:1507941112611306,tm1:1507941112612057,tm2:1507941112630944(18887),tm3:1507941112631172(19115),tm4:1507941112631206(19149)][tm4-tm0]:19900\nfinish 249 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18200\n250----rcs.size():7[tm0:1507941112661493,tm1:1507941112662487,tm2:1507941112680993(18506),tm3:1507941112681222(18735),tm4:1507941112681268(18781)][tm4-tm0]:19775\nfinish 250 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18295\n251----rcs.size():7[tm0:1507941112709857,tm1:1507941112710435,tm2:1507941112728986(18551),tm3:1507941112729213(18778),tm4:1507941112729246(18811)][tm4-tm0]:19389\nfinish 251 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18224\n252----rcs.size():7[tm0:1507941112759086,tm1:1507941112759663,tm2:1507941112778178(18515),tm3:1507941112778448(18785),tm4:1507941112778481(18818)][tm4-tm0]:19395\nfinish 252 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18449\n253----rcs.size():7[tm0:1507941112810707,tm1:1507941112811285,tm2:1507941112830031(18746),tm3:1507941112830284(18999),tm4:1507941112830330(19045)][tm4-tm0]:19623\nfinish 253 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18439\n254----rcs.size():7[tm0:1507941112860719,tm1:1507941112861318,tm2:1507941112880041(18723),tm3:1507941112880291(18973),tm4:1507941112880343(19025)][tm4-tm0]:19624\nfinish 254 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18005\n255----rcs.size():7[tm0:1507941112911013,tm1:1507941112911596,tm2:1507941112930114(18518),tm3:1507941112930380(18784),tm4:1507941112930430(18834)][tm4-tm0]:19417\nfinish 255 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18084\n256----rcs.size():7[tm0:1507941112965228,tm1:1507941112965800,tm2:1507941112984215(18415),tm3:1507941112984447(18647),tm4:1507941112984480(18680)][tm4-tm0]:19252\nfinish 256 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18364\n257----rcs.size():7[tm0:1507941113014762,tm1:1507941113015299,tm2:1507941113034043(18744),tm3:1507941113034285(18986),tm4:1507941113034331(19032)][tm4-tm0]:19569\nfinish 257 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18131\n258----rcs.size():7[tm0:1507941113065375,tm1:1507941113065929,tm2:1507941113084468(18539),tm3:1507941113084708(18779),tm4:1507941113084741(18812)][tm4-tm0]:19366\nfinish 258 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18043\n259----rcs.size():7[tm0:1507941113119356,tm1:1507941113120007,tm2:1507941113138379(18372),tm3:1507941113138630(18623),tm4:1507941113138676(18669)][tm4-tm0]:19320\nfinish 259 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18695\n260----rcs.size():7[tm0:1507941113169365,tm1:1507941113170008,tm2:1507941113189074(19066),tm3:1507941113189346(19338),tm4:1507941113189395(19387)][tm4-tm0]:20030\nfinish 260 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18078\n261----rcs.size():7[tm0:1507941113221107,tm1:1507941113221682,tm2:1507941113240070(18388),tm3:1507941113240334(18652),tm4:1507941113240381(18699)][tm4-tm0]:19274\nfinish 261 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18207\n262----rcs.size():7[tm0:1507941113275385,tm1:1507941113275976,tm2:1507941113294518(18542),tm3:1507941113294794(18818),tm4:1507941113294846(18870)][tm4-tm0]:19461\nfinish 262 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18576\n263----rcs.size():7[tm0:1507941113324873,tm1:1507941113325596,tm2:1507941113344579(18983),tm3:1507941113344843(19247),tm4:1507941113345024(19428)][tm4-tm0]:20151\nfinish 263 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18548\n264----rcs.size():7[tm0:1507941113374600,tm1:1507941113375213,tm2:1507941113394175(18962),tm3:1507941113394445(19232),tm4:1507941113394495(19282)][tm4-tm0]:19895\nfinish 264 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18305\n265----rcs.size():7[tm0:1507941113425027,tm1:1507941113425644,tm2:1507941113444345(18701),tm3:1507941113444616(18972),tm4:1507941113444668(19024)][tm4-tm0]:19641\nfinish 265 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19085\n266----rcs.size():7[tm0:1507941113474812,tm1:1507941113475410,tm2:1507941113495050(19640),tm3:1507941113495630(20220),tm4:1507941113495723(20313)][tm4-tm0]:20911\nfinish 266 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18257\n267----rcs.size():7[tm0:1507941113532278,tm1:1507941113532832,tm2:1507941113551522(18690),tm3:1507941113551798(18966),tm4:1507941113551846(19014)][tm4-tm0]:19568\nfinish 267 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18259\n268----rcs.size():7[tm0:1507941113582271,tm1:1507941113582846,tm2:1507941113601477(18631),tm3:1507941113601738(18892),tm4:1507941113601784(18938)][tm4-tm0]:19513\nfinish 268 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18228\n269----rcs.size():7[tm0:1507941113631053,tm1:1507941113631655,tm2:1507941113650321(18666),tm3:1507941113650595(18940),tm4:1507941113650629(18974)][tm4-tm0]:19576\nfinish 269 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17754\n270----rcs.size():6[tm0:1507941113680391,tm1:1507941113680925,tm2:1507941113698978(18053),tm3:1507941113699244(18319),tm4:1507941113699282(18357)][tm4-tm0]:18891\nfinish 270 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17761\n271----rcs.size():6[tm0:1507941113729262,tm1:1507941113729836,tm2:1507941113747811(17975),tm3:1507941113748019(18183),tm4:1507941113748049(18213)][tm4-tm0]:18787\nfinish 271 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17658\n272----rcs.size():6[tm0:1507941113781507,tm1:1507941113782056,tm2:1507941113799944(17888),tm3:1507941113800164(18108),tm4:1507941113800203(18147)][tm4-tm0]:18696\nfinish 272 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17552\n273----rcs.size():6[tm0:1507941113830789,tm1:1507941113831417,tm2:1507941113849193(17776),tm3:1507941113849392(17975),tm4:1507941113849431(18014)][tm4-tm0]:18642\nfinish 273 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17860\n274----rcs.size():6[tm0:1507941113880525,tm1:1507941113881133,tm2:1507941113899248(18115),tm3:1507941113899460(18327),tm4:1507941113899515(18382)][tm4-tm0]:18990\nfinish 274 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17915\n275----rcs.size():6[tm0:1507941113929569,tm1:1507941113930269,tm2:1507941113948446(18177),tm3:1507941113948661(18392),tm4:1507941113948788(18519)][tm4-tm0]:19219\nfinish 275 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17913\n276----rcs.size():6[tm0:1507941113981821,tm1:1507941113982478,tm2:1507941114000616(18138),tm3:1507941114000827(18349),tm4:1507941114000871(18393)][tm4-tm0]:19050\nfinish 276 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17879\n277----rcs.size():6[tm0:1507941114031393,tm1:1507941114032090,tm2:1507941114050231(18141),tm3:1507941114050469(18379),tm4:1507941114050498(18408)][tm4-tm0]:19105\nfinish 277 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17801\n278----rcs.size():6[tm0:1507941114080512,tm1:1507941114081083,tm2:1507941114099209(18126),tm3:1507941114099415(18332),tm4:1507941114099461(18378)][tm4-tm0]:18949\nfinish 278 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17671\n279----rcs.size():6[tm0:1507941114129712,tm1:1507941114130323,tm2:1507941114148266(17943),tm3:1507941114148495(18172),tm4:1507941114148541(18218)][tm4-tm0]:18829\nfinish 279 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17889\n280----rcs.size():6[tm0:1507941114178627,tm1:1507941114179529,tm2:1507941114197799(18270),tm3:1507941114198028(18499),tm4:1507941114198170(18641)][tm4-tm0]:19543\nfinish 280 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17987\n281----rcs.size():6[tm0:1507941114227996,tm1:1507941114228817,tm2:1507941114247096(18279),tm3:1507941114247353(18536),tm4:1507941114247404(18587)][tm4-tm0]:19408\nfinish 281 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18071\n282----rcs.size():6[tm0:1507941114280644,tm1:1507941114281222,tm2:1507941114299566(18344),tm3:1507941114299821(18599),tm4:1507941114299868(18646)][tm4-tm0]:19224\nfinish 282 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18131\n283----rcs.size():7[tm0:1507941114329532,tm1:1507941114330332,tm2:1507941114348746(18414),tm3:1507941114349032(18700),tm4:1507941114349188(18856)][tm4-tm0]:19656\nfinish 283 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18100\n284----rcs.size():7[tm0:1507941114379027,tm1:1507941114379766,tm2:1507941114398095(18329),tm3:1507941114398403(18637),tm4:1507941114398562(18796)][tm4-tm0]:19535\nfinish 284 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18171\n285----rcs.size():7[tm0:1507941114429034,tm1:1507941114429802,tm2:1507941114448282(18480),tm3:1507941114448569(18767),tm4:1507941114448604(18802)][tm4-tm0]:19570\nfinish 285 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17972\n286----rcs.size():7[tm0:1507941114480695,tm1:1507941114481289,tm2:1507941114499538(18249),tm3:1507941114499820(18531),tm4:1507941114499852(18563)][tm4-tm0]:19157\nfinish 286 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17821\n287----rcs.size():7[tm0:1507941114530023,tm1:1507941114530615,tm2:1507941114548686(18071),tm3:1507941114548983(18368),tm4:1507941114549023(18408)][tm4-tm0]:19000\nfinish 287 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17833\n288----rcs.size():7[tm0:1507941114579259,tm1:1507941114579901,tm2:1507941114598064(18163),tm3:1507941114598367(18466),tm4:1507941114598403(18502)][tm4-tm0]:19144\nfinish 288 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17974\n289----rcs.size():7[tm0:1507941114633215,tm1:1507941114633794,tm2:1507941114652047(18253),tm3:1507941114652289(18495),tm4:1507941114652323(18529)][tm4-tm0]:19108\nfinish 289 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17967\n290----rcs.size():7[tm0:1507941114683866,tm1:1507941114684403,tm2:1507941114702666(18263),tm3:1507941114702923(18520),tm4:1507941114702956(18553)][tm4-tm0]:19090\nfinish 290 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17918\n291----rcs.size():7[tm0:1507941114731973,tm1:1507941114732545,tm2:1507941114750744(18199),tm3:1507941114750992(18447),tm4:1507941114751026(18481)][tm4-tm0]:19053\nfinish 291 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18105\n292----rcs.size():7[tm0:1507941114780894,tm1:1507941114781526,tm2:1507941114799926(18400),tm3:1507941114800184(18658),tm4:1507941114800235(18709)][tm4-tm0]:19341\nfinish 292 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17768\n293----rcs.size():6[tm0:1507941114829830,tm1:1507941114830462,tm2:1507941114848514(18052),tm3:1507941114848768(18306),tm4:1507941114848801(18339)][tm4-tm0]:18971\nfinish 293 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18124\n294----rcs.size():6[tm0:1507941114879071,tm1:1507941114879736,tm2:1507941114898167(18431),tm3:1507941114898463(18727),tm4:1507941114898494(18758)][tm4-tm0]:19423\nfinish 294 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18065\n295----rcs.size():6[tm0:1507941114927747,tm1:1507941114928582,tm2:1507941114946983(18401),tm3:1507941114947264(18682),tm4:1507941114947299(18717)][tm4-tm0]:19552\nfinish 295 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17978\n296----rcs.size():6[tm0:1507941114977702,tm1:1507941114978506,tm2:1507941114996821(18315),tm3:1507941114997165(18659),tm4:1507941114997204(18698)][tm4-tm0]:19502\nfinish 296 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17944\n297----rcs.size():6[tm0:1507941115030440,tm1:1507941115031013,tm2:1507941115049292(18279),tm3:1507941115049549(18536),tm4:1507941115049585(18572)][tm4-tm0]:19145\nfinish 297 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18359\n298----rcs.size():6[tm0:1507941115080014,tm1:1507941115080593,tm2:1507941115099324(18731),tm3:1507941115099576(18983),tm4:1507941115099627(19034)][tm4-tm0]:19613\nfinish 298 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17915\n299----rcs.size():6[tm0:1507941115129457,tm1:1507941115130031,tm2:1507941115148259(18228),tm3:1507941115148512(18481),tm4:1507941115148560(18529)][tm4-tm0]:19103\nfinish 299 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18019\n300----rcs.size():6[tm0:1507941115178592,tm1:1507941115179226,tm2:1507941115197569(18343),tm3:1507941115197828(18602),tm4:1507941115197879(18653)][tm4-tm0]:19287\nfinish 300 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18142\n301----rcs.size():6[tm0:1507941115229259,tm1:1507941115230070,tm2:1507941115248607(18537),tm3:1507941115248903(18833),tm4:1507941115248969(18899)][tm4-tm0]:19710\nfinish 301 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18168\n302----rcs.size():6[tm0:1507941115280614,tm1:1507941115281234,tm2:1507941115299750(18516),tm3:1507941115299996(18762),tm4:1507941115300191(18957)][tm4-tm0]:19577\nfinish 302 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18163\n303----rcs.size():6[tm0:1507941115330232,tm1:1507941115330803,tm2:1507941115349383(18580),tm3:1507941115349646(18843),tm4:1507941115349815(19012)][tm4-tm0]:19583\nfinish 303 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18231\n304----rcs.size():6[tm0:1507941115379478,tm1:1507941115380128,tm2:1507941115398807(18679),tm3:1507941115399053(18925),tm4:1507941115399107(18979)][tm4-tm0]:19629\nfinish 304 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18140\n305----rcs.size():6[tm0:1507941115428659,tm1:1507941115429348,tm2:1507941115447865(18517),tm3:1507941115448111(18763),tm4:1507941115448175(18827)][tm4-tm0]:19516\nfinish 305 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18287\n306----rcs.size():6[tm0:1507941115477662,tm1:1507941115478563,tm2:1507941115497260(18697),tm3:1507941115497522(18959),tm4:1507941115497579(19016)][tm4-tm0]:19917\nfinish 306 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18134\n307----rcs.size():6[tm0:1507941115526963,tm1:1507941115527637,tm2:1507941115546490(18853),tm3:1507941115546757(19120),tm4:1507941115546812(19175)][tm4-tm0]:19849\nfinish 307 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18152\n308----rcs.size():6[tm0:1507941115579363,tm1:1507941115580049,tm2:1507941115598576(18527),tm3:1507941115598845(18796),tm4:1507941115598896(18847)][tm4-tm0]:19533\nfinish 308 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18070\n309----rcs.size():7[tm0:1507941115627866,tm1:1507941115628634,tm2:1507941115647169(18535),tm3:1507941115647465(18831),tm4:1507941115647522(18888)][tm4-tm0]:19656\nfinish 309 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18081\n310----rcs.size():7[tm0:1507941115680873,tm1:1507941115681467,tm2:1507941115699950(18483),tm3:1507941115700261(18794),tm4:1507941115700320(18853)][tm4-tm0]:19447\nfinish 310 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18100\n311----rcs.size():7[tm0:1507941115729581,tm1:1507941115730304,tm2:1507941115748773(18469),tm3:1507941115749072(18768),tm4:1507941115749110(18806)][tm4-tm0]:19529\nfinish 311 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18377\n312----rcs.size():7[tm0:1507941115778979,tm1:1507941115779674,tm2:1507941115798490(18816),tm3:1507941115798777(19103),tm4:1507941115798837(19163)][tm4-tm0]:19858\nfinish 312 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18200\n313----rcs.size():8[tm0:1507941115828022,tm1:1507941115828723,tm2:1507941115847348(18625),tm3:1507941115847692(18969),tm4:1507941115847766(19043)][tm4-tm0]:19744\nfinish 313 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18261\n314----rcs.size():8[tm0:1507941115881668,tm1:1507941115882263,tm2:1507941115900926(18663),tm3:1507941115901247(18984),tm4:1507941115901313(19050)][tm4-tm0]:19645\nfinish 314 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18395\n315----rcs.size():8[tm0:1507941115935465,tm1:1507941115936218,tm2:1507941115954999(18781),tm3:1507941115955324(19106),tm4:1507941115955526(19308)][tm4-tm0]:20061\nfinish 315 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18397\n316----rcs.size():8[tm0:1507941115990444,tm1:1507941115991178,tm2:1507941116010039(18861),tm3:1507941116010359(19181),tm4:1507941116010566(19388)][tm4-tm0]:20122\nfinish 316 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18544\n317----rcs.size():8[tm0:1507941116040484,tm1:1507941116041119,tm2:1507941116060309(19190),tm3:1507941116060628(19509),tm4:1507941116060702(19583)][tm4-tm0]:20218\nfinish 317 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18462\n318----rcs.size():8[tm0:1507941116091239,tm1:1507941116091878,tm2:1507941116110798(18920),tm3:1507941116111111(19233),tm4:1507941116111187(19309)][tm4-tm0]:19948\nfinish 318 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18611\n319----rcs.size():8[tm0:1507941116140689,tm1:1507941116141385,tm2:1507941116160454(19069),tm3:1507941116160752(19367),tm4:1507941116160819(19434)][tm4-tm0]:20130\nfinish 319 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18657\n320----rcs.size():8[tm0:1507941116190098,tm1:1507941116190697,tm2:1507941116209871(19174),tm3:1507941116210177(19480),tm4:1507941116210221(19524)][tm4-tm0]:20123\nfinish 320 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18647\n321----rcs.size():8[tm0:1507941116239959,tm1:1507941116240646,tm2:1507941116259856(19210),tm3:1507941116260162(19516),tm4:1507941116260204(19558)][tm4-tm0]:20245\nfinish 321 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18504\n322----rcs.size():8[tm0:1507941116290026,tm1:1507941116290574,tm2:1507941116309594(19020),tm3:1507941116309884(19310),tm4:1507941116309928(19354)][tm4-tm0]:19902\nfinish 322 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18575\n323----rcs.size():8[tm0:1507941116343988,tm1:1507941116344703,tm2:1507941116363909(19206),tm3:1507941116364281(19578),tm4:1507941116364325(19622)][tm4-tm0]:20337\nfinish 323 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18680\n324----rcs.size():8[tm0:1507941116394565,tm1:1507941116395378,tm2:1507941116414704(19326),tm3:1507941116415031(19653),tm4:1507941116415074(19696)][tm4-tm0]:20509\nfinish 324 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18423\n325----rcs.size():8[tm0:1507941116444672,tm1:1507941116445341,tm2:1507941116464351(19010),tm3:1507941116464676(19335),tm4:1507941116464930(19589)][tm4-tm0]:20258\nfinish 325 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18623\n326----rcs.size():8[tm0:1507941116494970,tm1:1507941116495651,tm2:1507941116514907(19256),tm3:1507941116515242(19591),tm4:1507941116515484(19833)][tm4-tm0]:20514\nfinish 326 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18753\n327----rcs.size():8[tm0:1507941116545060,tm1:1507941116545740,tm2:1507941116565108(19368),tm3:1507941116565479(19739),tm4:1507941116565555(19815)][tm4-tm0]:20495\nfinish 327 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18814\n328----rcs.size():7[tm0:1507941116598511,tm1:1507941116599113,tm2:1507941116618529(19416),tm3:1507941116618872(19759),tm4:1507941116619084(19971)][tm4-tm0]:20573\nfinish 328 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18677\n329----rcs.size():8[tm0:1507941116649088,tm1:1507941116649656,tm2:1507941116668988(19332),tm3:1507941116669325(19669),tm4:1507941116669392(19736)][tm4-tm0]:20304\nfinish 329 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19060\n330----rcs.size():7[tm0:1507941116698999,tm1:1507941116699606,tm2:1507941116719358(19752),tm3:1507941116719710(20104),tm4:1507941116719772(20166)][tm4-tm0]:20773\nfinish 330 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19420\n331----rcs.size():7[tm0:1507941116749217,tm1:1507941116749851,tm2:1507941116769889(20038),tm3:1507941116770231(20380),tm4:1507941116770288(20437)][tm4-tm0]:21071\nfinish 331 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19587\n332----rcs.size():6[tm0:1507941116800050,tm1:1507941116800987,tm2:1507941116821535(20548),tm3:1507941116821816(20829),tm4:1507941116821869(20882)][tm4-tm0]:21819\nfinish 332 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19644\n333----rcs.size():6[tm0:1507941116852161,tm1:1507941116853153,tm2:1507941116873705(20552),tm3:1507941116873966(20813),tm4:1507941116874025(20872)][tm4-tm0]:21864\nfinish 333 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19490\n334----rcs.size():7[tm0:1507941116904831,tm1:1507941116905799,tm2:1507941116926310(20511),tm3:1507941116926673(20874),tm4:1507941116926881(21082)][tm4-tm0]:22050\nfinish 334 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19722\n335----rcs.size():7[tm0:1507941116957293,tm1:1507941116958246,tm2:1507941116978909(20663),tm3:1507941116979222(20976),tm4:1507941116979282(21036)][tm4-tm0]:21989\nfinish 335 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19119\n336----rcs.size():6[tm0:1507941117009908,tm1:1507941117010979,tm2:1507941117030929(19950),tm3:1507941117031214(20235),tm4:1507941117031250(20271)][tm4-tm0]:21342\nfinish 336 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19382\n337----rcs.size():7[tm0:1507941117060411,tm1:1507941117061197,tm2:1507941117081567(20370),tm3:1507941117081917(20720),tm4:1507941117081957(20760)][tm4-tm0]:21546\nfinish 337 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19313\n338----rcs.size():6[tm0:1507941117112210,tm1:1507941117113128,tm2:1507941117133868(20740),tm3:1507941117134229(21101),tm4:1507941117134284(21156)][tm4-tm0]:22074\nfinish 338 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19216\n339----rcs.size():6[tm0:1507941117163830,tm1:1507941117164825,tm2:1507941117185206(20381),tm3:1507941117185534(20709),tm4:1507941117185587(20762)][tm4-tm0]:21757\nfinish 339 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19625\n340----rcs.size():7[tm0:1507941117216355,tm1:1507941117217354,tm2:1507941117238435(21081),tm3:1507941117238788(21434),tm4:1507941117238850(21496)][tm4-tm0]:22495\nfinish 340 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19333\n341----rcs.size():6[tm0:1507941117271777,tm1:1507941117272707,tm2:1507941117293027(20320),tm3:1507941117293338(20631),tm4:1507941117293396(20689)][tm4-tm0]:21619\nfinish 341 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19624\n342----rcs.size():6[tm0:1507941117329553,tm1:1507941117330509,tm2:1507941117351394(20885),tm3:1507941117351639(21130),tm4:1507941117351674(21165)][tm4-tm0]:22121\nfinish 342 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19220\n343----rcs.size():6[tm0:1507941117383171,tm1:1507941117384096,tm2:1507941117404487(20391),tm3:1507941117404761(20665),tm4:1507941117404798(20702)][tm4-tm0]:21627\nfinish 343 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19621\n344----rcs.size():6[tm0:1507941117435385,tm1:1507941117436372,tm2:1507941117457273(20901),tm3:1507941117457515(21143),tm4:1507941117457551(21179)][tm4-tm0]:22166\nfinish 344 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19925\n345----rcs.size():6[tm0:1507941117490417,tm1:1507941117491379,tm2:1507941117512678(21299),tm3:1507941117512929(21550),tm4:1507941117512981(21602)][tm4-tm0]:22564\nfinish 345 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19805\n346----rcs.size():6[tm0:1507941117543866,tm1:1507941117545129,tm2:1507941117566468(21339),tm3:1507941117566716(21587),tm4:1507941117566768(21639)][tm4-tm0]:22902\nfinish 346 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19781\n347----rcs.size():6[tm0:1507941117598076,tm1:1507941117599031,tm2:1507941117620203(21172),tm3:1507941117620437(21406),tm4:1507941117620490(21459)][tm4-tm0]:22414\nfinish 347 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19757\n348----rcs.size():6[tm0:1507941117651864,tm1:1507941117652849,tm2:1507941117673947(21098),tm3:1507941117674293(21444),tm4:1507941117674344(21495)][tm4-tm0]:22480\nfinish 348 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:20032\n349----rcs.size():6[tm0:1507941117705025,tm1:1507941117705942,tm2:1507941117727508(21566),tm3:1507941117727761(21819),tm4:1507941117727816(21874)][tm4-tm0]:22791\nfinish 349 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19900\n350----rcs.size():6[tm0:1507941117760768,tm1:1507941117761993,tm2:1507941117783500(21507),tm3:1507941117783757(21764),tm4:1507941117783811(21818)][tm4-tm0]:23043\nfinish 350 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19847\n351----rcs.size():6[tm0:1507941117812759,tm1:1507941117813641,tm2:1507941117834883(21242),tm3:1507941117835163(21522),tm4:1507941117835347(21706)][tm4-tm0]:22588\nfinish 351 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19643\n352----rcs.size():6[tm0:1507941117865647,tm1:1507941117866678,tm2:1507941117887421(20743),tm3:1507941117887765(21087),tm4:1507941117887798(21120)][tm4-tm0]:22151\nfinish 352 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19617\n353----rcs.size():6[tm0:1507941117917254,tm1:1507941117918235,tm2:1507941117939367(21132),tm3:1507941117939711(21476),tm4:1507941117939884(21649)][tm4-tm0]:22630\nfinish 353 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18141\n354----rcs.size():5[tm0:1507941117972489,tm1:1507941117973435,tm2:1507941117991945(18510),tm3:1507941117992235(18800),tm4:1507941117992286(18851)][tm4-tm0]:19797\nfinish 354 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18784\n355----rcs.size():6[tm0:1507941118023561,tm1:1507941118024099,tm2:1507941118043304(19205),tm3:1507941118043691(19592),tm4:1507941118043745(19646)][tm4-tm0]:20184\nfinish 355 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18439\n356----rcs.size():6[tm0:1507941118077781,tm1:1507941118078388,tm2:1507941118097256(18868),tm3:1507941118097568(19180),tm4:1507941118097612(19224)][tm4-tm0]:19831\nfinish 356 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18267\n357----rcs.size():6[tm0:1507941118131467,tm1:1507941118132081,tm2:1507941118150720(18639),tm3:1507941118151042(18961),tm4:1507941118151194(19113)][tm4-tm0]:19727\nfinish 357 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18223\n358----rcs.size():6[tm0:1507941118184553,tm1:1507941118185129,tm2:1507941118203785(18656),tm3:1507941118203996(18867),tm4:1507941118204029(18900)][tm4-tm0]:19476\nfinish 358 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18195\n359----rcs.size():6[tm0:1507941118233224,tm1:1507941118233808,tm2:1507941118252390(18582),tm3:1507941118252723(18915),tm4:1507941118252770(18962)][tm4-tm0]:19546\nfinish 359 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18372\n360----rcs.size():6[tm0:1507941118283630,tm1:1507941118284200,tm2:1507941118302952(18752),tm3:1507941118303177(18977),tm4:1507941118303223(19023)][tm4-tm0]:19593\nfinish 360 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18318\n361----rcs.size():6[tm0:1507941118333576,tm1:1507941118334208,tm2:1507941118352909(18701),tm3:1507941118353169(18961),tm4:1507941118353215(19007)][tm4-tm0]:19639\nfinish 361 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18229\n362----rcs.size():6[tm0:1507941118382915,tm1:1507941118383454,tm2:1507941118402103(18649),tm3:1507941118402327(18873),tm4:1507941118402360(18906)][tm4-tm0]:19445\nfinish 362 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18475\n363----rcs.size():6[tm0:1507941118433106,tm1:1507941118433684,tm2:1507941118452625(18941),tm3:1507941118452829(19145),tm4:1507941118452878(19194)][tm4-tm0]:19772\nfinish 363 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18603\n364----rcs.size():6[tm0:1507941118483677,tm1:1507941118484300,tm2:1507941118503375(19075),tm3:1507941118503578(19278),tm4:1507941118503611(19311)][tm4-tm0]:19934\nfinish 364 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18576\n365----rcs.size():6[tm0:1507941118534285,tm1:1507941118534897,tm2:1507941118553946(19049),tm3:1507941118554182(19285),tm4:1507941118554224(19327)][tm4-tm0]:19939\nfinish 365 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18741\n366----rcs.size():6[tm0:1507941118584523,tm1:1507941118585092,tm2:1507941118604459(19367),tm3:1507941118604687(19595),tm4:1507941118604728(19636)][tm4-tm0]:20205\nfinish 366 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18330\n367----rcs.size():6[tm0:1507941118635251,tm1:1507941118635916,tm2:1507941118654706(18790),tm3:1507941118654947(19031),tm4:1507941118654989(19073)][tm4-tm0]:19738\nfinish 367 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18421\n368----rcs.size():6[tm0:1507941118685547,tm1:1507941118686163,tm2:1507941118705035(18872),tm3:1507941118705277(19114),tm4:1507941118705320(19157)][tm4-tm0]:19773\nfinish 368 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18574\n369----rcs.size():6[tm0:1507941118735997,tm1:1507941118736698,tm2:1507941118755753(19055),tm3:1507941118756054(19356),tm4:1507941118756203(19505)][tm4-tm0]:20206\nfinish 369 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17840\n370----rcs.size():5[tm0:1507941118786875,tm1:1507941118787533,tm2:1507941118805632(18099),tm3:1507941118805838(18305),tm4:1507941118805946(18413)][tm4-tm0]:19071\nfinish 370 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17825\n371----rcs.size():5[tm0:1507941118838769,tm1:1507941118839415,tm2:1507941118857469(18054),tm3:1507941118857623(18208),tm4:1507941118857661(18246)][tm4-tm0]:18892\nfinish 371 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18055\n372----rcs.size():5[tm0:1507941118891725,tm1:1507941118892306,tm2:1507941118910621(18315),tm3:1507941118910795(18489),tm4:1507941118910909(18603)][tm4-tm0]:19184\nfinish 372 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17953\n373----rcs.size():5[tm0:1507941118946065,tm1:1507941118946603,tm2:1507941118964815(18212),tm3:1507941118964978(18375),tm4:1507941118965003(18400)][tm4-tm0]:18938\nfinish 373 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17994\n374----rcs.size():5[tm0:1507941118995088,tm1:1507941118995712,tm2:1507941119013968(18256),tm3:1507941119014125(18413),tm4:1507941119014225(18513)][tm4-tm0]:19137\nfinish 374 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17843\n375----rcs.size():5[tm0:1507941119044681,tm1:1507941119045390,tm2:1507941119063479(18089),tm3:1507941119063637(18247),tm4:1507941119063675(18285)][tm4-tm0]:18994\nfinish 375 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17929\n376----rcs.size():5[tm0:1507941119095305,tm1:1507941119095870,tm2:1507941119114063(18193),tm3:1507941119114283(18413),tm4:1507941119114321(18451)][tm4-tm0]:19016\nfinish 376 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18007\n377----rcs.size():5[tm0:1507941119148979,tm1:1507941119149551,tm2:1507941119167846(18295),tm3:1507941119168004(18453),tm4:1507941119168040(18489)][tm4-tm0]:19061\nfinish 377 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17984\n378----rcs.size():5[tm0:1507941119200348,tm1:1507941119200935,tm2:1507941119219216(18281),tm3:1507941119219373(18438),tm4:1507941119219400(18465)][tm4-tm0]:19052\nfinish 378 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17873\n379----rcs.size():5[tm0:1507941119251446,tm1:1507941119252047,tm2:1507941119270198(18151),tm3:1507941119270375(18328),tm4:1507941119270411(18364)][tm4-tm0]:18965\nfinish 379 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17974\n380----rcs.size():5[tm0:1507941119300728,tm1:1507941119301309,tm2:1507941119319512(18203),tm3:1507941119319699(18390),tm4:1507941119319723(18414)][tm4-tm0]:18995\nfinish 380 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17979\n381----rcs.size():5[tm0:1507941119349881,tm1:1507941119350439,tm2:1507941119368675(18236),tm3:1507941119368841(18402),tm4:1507941119368956(18517)][tm4-tm0]:19075\nfinish 381 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18019\n382----rcs.size():5[tm0:1507941119398891,tm1:1507941119399429,tm2:1507941119417714(18285),tm3:1507941119417896(18467),tm4:1507941119417936(18507)][tm4-tm0]:19045\nfinish 382 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17923\n383----rcs.size():5[tm0:1507941119449367,tm1:1507941119449920,tm2:1507941119468133(18213),tm3:1507941119468372(18452),tm4:1507941119468399(18479)][tm4-tm0]:19032\nfinish 383 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17984\n384----rcs.size():5[tm0:1507941119500348,tm1:1507941119500903,tm2:1507941119519205(18302),tm3:1507941119519380(18477),tm4:1507941119519405(18502)][tm4-tm0]:19057\nfinish 384 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18242\n385----rcs.size():5[tm0:1507941119550263,tm1:1507941119550864,tm2:1507941119569457(18593),tm3:1507941119569658(18794),tm4:1507941119569786(18922)][tm4-tm0]:19523\nfinish 385 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17888\n386----rcs.size():5[tm0:1507941119600300,tm1:1507941119600903,tm2:1507941119619082(18179),tm3:1507941119619279(18376),tm4:1507941119619320(18417)][tm4-tm0]:19020\nfinish 386 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18151\n387----rcs.size():5[tm0:1507941119649990,tm1:1507941119650600,tm2:1507941119669085(18485),tm3:1507941119669266(18666),tm4:1507941119669308(18708)][tm4-tm0]:19318\nfinish 387 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18048\n388----rcs.size():5[tm0:1507941119700417,tm1:1507941119700970,tm2:1507941119719348(18378),tm3:1507941119719536(18566),tm4:1507941119719565(18595)][tm4-tm0]:19148\nfinish 388 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17960\n389----rcs.size():5[tm0:1507941119750225,tm1:1507941119750794,tm2:1507941119769058(18264),tm3:1507941119769238(18444),tm4:1507941119769266(18472)][tm4-tm0]:19041\nfinish 389 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18265\n390----rcs.size():5[tm0:1507941119801231,tm1:1507941119801782,tm2:1507941119820437(18655),tm3:1507941119820609(18827),tm4:1507941119820636(18854)][tm4-tm0]:19405\nfinish 390 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18178\n391----rcs.size():5[tm0:1507941119851726,tm1:1507941119852381,tm2:1507941119870937(18556),tm3:1507941119871113(18732),tm4:1507941119871160(18779)][tm4-tm0]:19434\nfinish 391 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18241\n392----rcs.size():5[tm0:1507941119901734,tm1:1507941119902407,tm2:1507941119920981(18574),tm3:1507941119921168(18761),tm4:1507941119921228(18821)][tm4-tm0]:19494\nfinish 392 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18154\n393----rcs.size():6[tm0:1507941119952086,tm1:1507941119952805,tm2:1507941119971268(18463),tm3:1507941119971516(18711),tm4:1507941119971556(18751)][tm4-tm0]:19470\nfinish 393 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18370\n394----rcs.size():6[tm0:1507941120002075,tm1:1507941120002746,tm2:1507941120021487(18741),tm3:1507941120021722(18976),tm4:1507941120021764(19018)][tm4-tm0]:19689\nfinish 394 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18254\n395----rcs.size():6[tm0:1507941120052156,tm1:1507941120052748,tm2:1507941120071338(18590),tm3:1507941120071572(18824),tm4:1507941120071604(18856)][tm4-tm0]:19448\nfinish 395 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18303\n396----rcs.size():6[tm0:1507941120102829,tm1:1507941120103383,tm2:1507941120122101(18718),tm3:1507941120122311(18928),tm4:1507941120122343(18960)][tm4-tm0]:19514\nfinish 396 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18185\n397----rcs.size():6[tm0:1507941120153200,tm1:1507941120153797,tm2:1507941120172356(18559),tm3:1507941120172558(18761),tm4:1507941120172591(18794)][tm4-tm0]:19391\nfinish 397 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18251\n398----rcs.size():6[tm0:1507941120203249,tm1:1507941120203817,tm2:1507941120222457(18640),tm3:1507941120222661(18844),tm4:1507941120222693(18876)][tm4-tm0]:19444\nfinish 398 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18197\n399----rcs.size():6[tm0:1507941120253554,tm1:1507941120254152,tm2:1507941120272722(18570),tm3:1507941120272944(18792),tm4:1507941120272976(18824)][tm4-tm0]:19422\nfinish 399 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18058\n400----rcs.size():6[tm0:1507941120303580,tm1:1507941120304261,tm2:1507941120322680(18419),tm3:1507941120322948(18687),tm4:1507941120322988(18727)][tm4-tm0]:19408\nfinish 400 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18586\n401----rcs.size():6[tm0:1507941120355590,tm1:1507941120356269,tm2:1507941120375365(19096),tm3:1507941120375610(19341),tm4:1507941120375644(19375)][tm4-tm0]:20054\nfinish 401 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18453\n402----rcs.size():6[tm0:1507941120405392,tm1:1507941120406093,tm2:1507941120425033(18940),tm3:1507941120425257(19164),tm4:1507941120425290(19197)][tm4-tm0]:19898\nfinish 402 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18247\n403----rcs.size():6[tm0:1507941120455352,tm1:1507941120455910,tm2:1507941120474646(18736),tm3:1507941120474875(18965),tm4:1507941120474927(19017)][tm4-tm0]:19575\nfinish 403 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18415\n404----rcs.size():6[tm0:1507941120504964,tm1:1507941120505544,tm2:1507941120524421(18877),tm3:1507941120524645(19101),tm4:1507941120524678(19134)][tm4-tm0]:19714\nfinish 404 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18617\n405----rcs.size():6[tm0:1507941120555991,tm1:1507941120556565,tm2:1507941120575673(19108),tm3:1507941120575887(19322),tm4:1507941120575934(19369)][tm4-tm0]:19943\nfinish 405 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18674\n406----rcs.size():6[tm0:1507941120606182,tm1:1507941120606848,tm2:1507941120626006(19158),tm3:1507941120626256(19408),tm4:1507941120626307(19459)][tm4-tm0]:20125\nfinish 406 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18962\n407----rcs.size():6[tm0:1507941120656507,tm1:1507941120657226,tm2:1507941120676741(19515),tm3:1507941120676989(19763),tm4:1507941120677037(19811)][tm4-tm0]:20530\nfinish 407 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18812\n408----rcs.size():6[tm0:1507941120707522,tm1:1507941120708225,tm2:1507941120727533(19308),tm3:1507941120727767(19542),tm4:1507941120727815(19590)][tm4-tm0]:20293\nfinish 408 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19012\n409----rcs.size():6[tm0:1507941120758298,tm1:1507941120758913,tm2:1507941120778396(19483),tm3:1507941120778620(19707),tm4:1507941120778671(19758)][tm4-tm0]:20373\nfinish 409 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18618\n410----rcs.size():6[tm0:1507941120809385,tm1:1507941120810073,tm2:1507941120829493(19420),tm3:1507941120829761(19688),tm4:1507941120829810(19737)][tm4-tm0]:20425\nfinish 410 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19903\n411----rcs.size():6[tm0:1507941120860590,tm1:1507941120861272,tm2:1507941120882220(20948),tm3:1507941120882462(21190),tm4:1507941120882510(21238)][tm4-tm0]:21920\nfinish 411 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19617\n412----rcs.size():6[tm0:1507941120914366,tm1:1507941120915424,tm2:1507941120935940(20516),tm3:1507941120936179(20755),tm4:1507941120936229(20805)][tm4-tm0]:21863\nfinish 412 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19257\n413----rcs.size():6[tm0:1507941120967890,tm1:1507941120968995,tm2:1507941120989208(20213),tm3:1507941120989484(20489),tm4:1507941120989532(20537)][tm4-tm0]:21642\nfinish 413 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18806\n414----rcs.size():6[tm0:1507941121020932,tm1:1507941121021972,tm2:1507941121041272(19300),tm3:1507941121041534(19562),tm4:1507941121041584(19612)][tm4-tm0]:20652\nfinish 414 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18997\n415----rcs.size():6[tm0:1507941121072190,tm1:1507941121072907,tm2:1507941121092426(19519),tm3:1507941121092690(19783),tm4:1507941121092736(19829)][tm4-tm0]:20546\nfinish 415 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:20143\n416----rcs.size():6[tm0:1507941121123348,tm1:1507941121124050,tm2:1507941121144998(20948),tm3:1507941121145259(21209),tm4:1507941121145309(21259)][tm4-tm0]:21961\nfinish 416 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19485\n417----rcs.size():6[tm0:1507941121176705,tm1:1507941121177940,tm2:1507941121198451(20511),tm3:1507941121198682(20742),tm4:1507941121198728(20788)][tm4-tm0]:22023\nfinish 417 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19536\n418----rcs.size():5[tm0:1507941121230469,tm1:1507941121231489,tm2:1507941121251969(20480),tm3:1507941121252232(20743),tm4:1507941121252273(20784)][tm4-tm0]:21804\nfinish 418 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19439\n419----rcs.size():5[tm0:1507941121283959,tm1:1507941121284863,tm2:1507941121305304(20441),tm3:1507941121305517(20654),tm4:1507941121305560(20697)][tm4-tm0]:21601\nfinish 419 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18647\n420----rcs.size():5[tm0:1507941121337476,tm1:1507941121338650,tm2:1507941121357893(19243),tm3:1507941121358068(19418),tm4:1507941121358094(19444)][tm4-tm0]:20618\nfinish 420 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18474\n421----rcs.size():5[tm0:1507941121392833,tm1:1507941121393515,tm2:1507941121412543(19028),tm3:1507941121412734(19219),tm4:1507941121412771(19256)][tm4-tm0]:19938\nfinish 421 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17907\n422----rcs.size():4[tm0:1507941121443702,tm1:1507941121444443,tm2:1507941121462600(18157),tm3:1507941121462795(18352),tm4:1507941121462821(18378)][tm4-tm0]:19119\nfinish 422 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17784\n423----rcs.size():4[tm0:1507941121493879,tm1:1507941121494584,tm2:1507941121512605(18021),tm3:1507941121512733(18149),tm4:1507941121512752(18168)][tm4-tm0]:18873\nfinish 423 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17875\n424----rcs.size():4[tm0:1507941121543907,tm1:1507941121544618,tm2:1507941121562772(18154),tm3:1507941121562896(18278),tm4:1507941121562923(18305)][tm4-tm0]:19016\nfinish 424 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17765\n425----rcs.size():5[tm0:1507941121593331,tm1:1507941121594265,tm2:1507941121612279(18014),tm3:1507941121612501(18236),tm4:1507941121612527(18262)][tm4-tm0]:19196\nfinish 425 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17763\n426----rcs.size():5[tm0:1507941121643496,tm1:1507941121644259,tm2:1507941121662276(18017),tm3:1507941121662503(18244),tm4:1507941121662530(18271)][tm4-tm0]:19034\nfinish 426 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17925\n427----rcs.size():5[tm0:1507941121693038,tm1:1507941121693776,tm2:1507941121711989(18213),tm3:1507941121712209(18433),tm4:1507941121712241(18465)][tm4-tm0]:19203\nfinish 427 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17783\n428----rcs.size():5[tm0:1507941121746381,tm1:1507941121747050,tm2:1507941121765099(18049),tm3:1507941121765257(18207),tm4:1507941121765287(18237)][tm4-tm0]:18906\nfinish 428 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17594\n429----rcs.size():5[tm0:1507941121795587,tm1:1507941121796291,tm2:1507941121814131(17840),tm3:1507941121814307(18016),tm4:1507941121814339(18048)][tm4-tm0]:18752\nfinish 429 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17834\n430----rcs.size():5[tm0:1507941121845139,tm1:1507941121845882,tm2:1507941121863951(18069),tm3:1507941121864103(18221),tm4:1507941121864134(18252)][tm4-tm0]:18995\nfinish 430 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17759\n431----rcs.size():5[tm0:1507941121895622,tm1:1507941121896274,tm2:1507941121914323(18049),tm3:1507941121914541(18267),tm4:1507941121914565(18291)][tm4-tm0]:18943\nfinish 431 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17840\n432----rcs.size():5[tm0:1507941121950000,tm1:1507941121950513,tm2:1507941121968611(18098),tm3:1507941121968768(18255),tm4:1507941121968804(18291)][tm4-tm0]:18804\nfinish 432 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17999\n433----rcs.size():5[tm0:1507941121999601,tm1:1507941122000293,tm2:1507941122018579(18286),tm3:1507941122018738(18445),tm4:1507941122018770(18477)][tm4-tm0]:19169\nfinish 433 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17762\n434----rcs.size():5[tm0:1507941122049458,tm1:1507941122050150,tm2:1507941122068169(18019),tm3:1507941122068326(18176),tm4:1507941122068351(18201)][tm4-tm0]:18893\nfinish 434 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17742\n435----rcs.size():5[tm0:1507941122102491,tm1:1507941122103082,tm2:1507941122121082(18000),tm3:1507941122121255(18173),tm4:1507941122121288(18206)][tm4-tm0]:18797\nfinish 435 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17790\n436----rcs.size():5[tm0:1507941122153366,tm1:1507941122154059,tm2:1507941122172127(18068),tm3:1507941122172293(18234),tm4:1507941122172320(18261)][tm4-tm0]:18954\nfinish 436 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18035\n437----rcs.size():5[tm0:1507941122203968,tm1:1507941122204685,tm2:1507941122223034(18349),tm3:1507941122223190(18505),tm4:1507941122223216(18531)][tm4-tm0]:19248\nfinish 437 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17808\n438----rcs.size():5[tm0:1507941122253792,tm1:1507941122254486,tm2:1507941122272563(18077),tm3:1507941122272747(18261),tm4:1507941122272782(18296)][tm4-tm0]:18990\nfinish 438 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17850\n439----rcs.size():5[tm0:1507941122303265,tm1:1507941122303879,tm2:1507941122322066(18187),tm3:1507941122322259(18380),tm4:1507941122322296(18417)][tm4-tm0]:19031\nfinish 439 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17880\n440----rcs.size():5[tm0:1507941122353349,tm1:1507941122353981,tm2:1507941122372164(18183),tm3:1507941122372337(18356),tm4:1507941122372362(18381)][tm4-tm0]:19013\nfinish 440 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17971\n441----rcs.size():5[tm0:1507941122403199,tm1:1507941122403908,tm2:1507941122422203(18295),tm3:1507941122422357(18449),tm4:1507941122422392(18484)][tm4-tm0]:19193\nfinish 441 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18108\n442----rcs.size():5[tm0:1507941122455953,tm1:1507941122456668,tm2:1507941122475083(18415),tm3:1507941122475259(18591),tm4:1507941122475285(18617)][tm4-tm0]:19332\nfinish 442 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18024\n443----rcs.size():5[tm0:1507941122511014,tm1:1507941122511698,tm2:1507941122530075(18377),tm3:1507941122530261(18563),tm4:1507941122530298(18600)][tm4-tm0]:19284\nfinish 443 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18211\n444----rcs.size():5[tm0:1507941122563679,tm1:1507941122564473,tm2:1507941122583000(18527),tm3:1507941122583187(18714),tm4:1507941122583222(18749)][tm4-tm0]:19543\nfinish 444 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18004\n445----rcs.size():5[tm0:1507941122613812,tm1:1507941122614588,tm2:1507941122632915(18327),tm3:1507941122633182(18594),tm4:1507941122633218(18630)][tm4-tm0]:19406\nfinish 445 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17971\n446----rcs.size():6[tm0:1507941122664224,tm1:1507941122664939,tm2:1507941122683236(18297),tm3:1507941122683502(18563),tm4:1507941122683537(18598)][tm4-tm0]:19313\nfinish 446 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18019\n447----rcs.size():6[tm0:1507941122715055,tm1:1507941122715703,tm2:1507941122733999(18296),tm3:1507941122734297(18594),tm4:1507941122734331(18628)][tm4-tm0]:19276\nfinish 447 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18246\n448----rcs.size():6[tm0:1507941122765479,tm1:1507941122766118,tm2:1507941122784818(18700),tm3:1507941122785057(18939),tm4:1507941122785098(18980)][tm4-tm0]:19619\nfinish 448 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18199\n449----rcs.size():6[tm0:1507941122815992,tm1:1507941122816662,tm2:1507941122835237(18575),tm3:1507941122835429(18767),tm4:1507941122835459(18797)][tm4-tm0]:19467\nfinish 449 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18638\n450----rcs.size():6[tm0:1507941122866283,tm1:1507941122866962,tm2:1507941122885960(18998),tm3:1507941122886150(19188),tm4:1507941122886180(19218)][tm4-tm0]:19897\nfinish 450 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18363\n451----rcs.size():6[tm0:1507941122915385,tm1:1507941122916042,tm2:1507941122934854(18812),tm3:1507941122935035(18993),tm4:1507941122935076(19034)][tm4-tm0]:19691\nfinish 451 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18219\n452----rcs.size():6[tm0:1507941122965297,tm1:1507941122965917,tm2:1507941122984552(18635),tm3:1507941122984785(18868),tm4:1507941122984815(18898)][tm4-tm0]:19518\nfinish 452 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18429\n453----rcs.size():6[tm0:1507941123015786,tm1:1507941123016446,tm2:1507941123035251(18805),tm3:1507941123035436(18990),tm4:1507941123035495(19049)][tm4-tm0]:19709\nfinish 453 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18323\n454----rcs.size():6[tm0:1507941123065424,tm1:1507941123066062,tm2:1507941123084797(18735),tm3:1507941123084990(18928),tm4:1507941123085018(18956)][tm4-tm0]:19594\nfinish 454 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18306\n455----rcs.size():6[tm0:1507941123115613,tm1:1507941123116311,tm2:1507941123134952(18641),tm3:1507941123135167(18856),tm4:1507941123135212(18901)][tm4-tm0]:19599\nfinish 455 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18374\n456----rcs.size():6[tm0:1507941123165966,tm1:1507941123166666,tm2:1507941123185413(18747),tm3:1507941123185622(18956),tm4:1507941123185651(18985)][tm4-tm0]:19685\nfinish 456 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18352\n457----rcs.size():6[tm0:1507941123216626,tm1:1507941123217286,tm2:1507941123236024(18738),tm3:1507941123236298(19012),tm4:1507941123236359(19073)][tm4-tm0]:19733\nfinish 457 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18437\n458----rcs.size():6[tm0:1507941123266799,tm1:1507941123267518,tm2:1507941123286369(18851),tm3:1507941123286576(19058),tm4:1507941123286618(19100)][tm4-tm0]:19819\nfinish 458 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18452\n459----rcs.size():6[tm0:1507941123317249,tm1:1507941123317961,tm2:1507941123336900(18939),tm3:1507941123337108(19147),tm4:1507941123337160(19199)][tm4-tm0]:19911\nfinish 459 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18279\n460----rcs.size():6[tm0:1507941123371664,tm1:1507941123372265,tm2:1507941123390998(18733),tm3:1507941123391244(18979),tm4:1507941123391282(19017)][tm4-tm0]:19618\nfinish 460 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18660\n461----rcs.size():6[tm0:1507941123424475,tm1:1507941123425135,tm2:1507941123444189(19054),tm3:1507941123444384(19249),tm4:1507941123444430(19295)][tm4-tm0]:19955\nfinish 461 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18757\n462----rcs.size():6[tm0:1507941123474983,tm1:1507941123475559,tm2:1507941123494723(19164),tm3:1507941123494919(19360),tm4:1507941123494983(19424)][tm4-tm0]:20000\nfinish 462 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18381\n463----rcs.size():6[tm0:1507941123525543,tm1:1507941123526334,tm2:1507941123545330(18996),tm3:1507941123545564(19230),tm4:1507941123545608(19274)][tm4-tm0]:20065\nfinish 463 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18413\n464----rcs.size():6[tm0:1507941123576308,tm1:1507941123577109,tm2:1507941123596079(18970),tm3:1507941123596307(19198),tm4:1507941123596357(19248)][tm4-tm0]:20049\nfinish 464 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18290\n465----rcs.size():6[tm0:1507941123627038,tm1:1507941123627826,tm2:1507941123646584(18758),tm3:1507941123646802(18976),tm4:1507941123646847(19021)][tm4-tm0]:19809\nfinish 465 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18522\n466----rcs.size():6[tm0:1507941123676943,tm1:1507941123677626,tm2:1507941123696630(19004),tm3:1507941123696863(19237),tm4:1507941123696907(19281)][tm4-tm0]:19964\nfinish 466 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18573\n467----rcs.size():6[tm0:1507941123727654,tm1:1507941123728411,tm2:1507941123747438(19027),tm3:1507941123747647(19236),tm4:1507941123747694(19283)][tm4-tm0]:20040\nfinish 467 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18507\n468----rcs.size():6[tm0:1507941123780504,tm1:1507941123781206,tm2:1507941123800165(18959),tm3:1507941123800391(19185),tm4:1507941123800424(19218)][tm4-tm0]:19920\nfinish 468 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18668\n469----rcs.size():6[tm0:1507941123830605,tm1:1507941123831188,tm2:1507941123850351(19163),tm3:1507941123850576(19388),tm4:1507941123850733(19545)][tm4-tm0]:20128\nfinish 469 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18375\n470----rcs.size():6[tm0:1507941123880948,tm1:1507941123881489,tm2:1507941123900384(18895),tm3:1507941123900617(19128),tm4:1507941123900666(19177)][tm4-tm0]:19718\nfinish 470 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18617\n471----rcs.size():6[tm0:1507941123931839,tm1:1507941123932457,tm2:1507941123951559(19102),tm3:1507941123951774(19317),tm4:1507941123951819(19362)][tm4-tm0]:19980\nfinish 471 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18422\n472----rcs.size():6[tm0:1507941123981956,tm1:1507941123982483,tm2:1507941124001384(18901),tm3:1507941124001599(19116),tm4:1507941124001738(19255)][tm4-tm0]:19782\nfinish 472 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18566\n473----rcs.size():5[tm0:1507941124032109,tm1:1507941124032693,tm2:1507941124051744(19051),tm3:1507941124051974(19281),tm4:1507941124052101(19408)][tm4-tm0]:19992\nfinish 473 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18167\n474----rcs.size():4[tm0:1507941124082464,tm1:1507941124083060,tm2:1507941124101539(18479),tm3:1507941124101725(18665),tm4:1507941124101756(18696)][tm4-tm0]:19292\nfinish 474 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18063\n475----rcs.size():5[tm0:1507941124131444,tm1:1507941124131978,tm2:1507941124150371(18393),tm3:1507941124150580(18602),tm4:1507941124150603(18625)][tm4-tm0]:19159\nfinish 475 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18410\n476----rcs.size():5[tm0:1507941124180858,tm1:1507941124181375,tm2:1507941124200164(18789),tm3:1507941124200362(18987),tm4:1507941124200397(19022)][tm4-tm0]:19539\nfinish 476 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18229\n477----rcs.size():6[tm0:1507941124230079,tm1:1507941124230614,tm2:1507941124249199(18585),tm3:1507941124249426(18812),tm4:1507941124249452(18838)][tm4-tm0]:19373\nfinish 477 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18302\n478----rcs.size():6[tm0:1507941124280261,tm1:1507941124280825,tm2:1507941124299486(18661),tm3:1507941124299725(18900),tm4:1507941124299843(19018)][tm4-tm0]:19582\nfinish 478 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18403\n479----rcs.size():6[tm0:1507941124330737,tm1:1507941124331336,tm2:1507941124350152(18816),tm3:1507941124350394(19058),tm4:1507941124350525(19189)][tm4-tm0]:19788\nfinish 479 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18087\n480----rcs.size():6[tm0:1507941124381424,tm1:1507941124381997,tm2:1507941124400449(18452),tm3:1507941124400631(18634),tm4:1507941124400758(18761)][tm4-tm0]:19334\nfinish 480 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18410\n481----rcs.size():6[tm0:1507941124431018,tm1:1507941124431572,tm2:1507941124450408(18836),tm3:1507941124450607(19035),tm4:1507941124450735(19163)][tm4-tm0]:19717\nfinish 481 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18371\n482----rcs.size():6[tm0:1507941124480844,tm1:1507941124481381,tm2:1507941124500221(18840),tm3:1507941124500443(19062),tm4:1507941124500581(19200)][tm4-tm0]:19737\nfinish 482 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18328\n483----rcs.size():6[tm0:1507941124530904,tm1:1507941124531493,tm2:1507941124550213(18720),tm3:1507941124550420(18927),tm4:1507941124550549(19056)][tm4-tm0]:19645\nfinish 483 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18474\n484----rcs.size():6[tm0:1507941124581448,tm1:1507941124582046,tm2:1507941124600959(18913),tm3:1507941124601167(19121),tm4:1507941124601199(19153)][tm4-tm0]:19751\nfinish 484 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18387\n485----rcs.size():6[tm0:1507941124632628,tm1:1507941124633163,tm2:1507941124652033(18870),tm3:1507941124652293(19130),tm4:1507941124652334(19171)][tm4-tm0]:19706\nfinish 485 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18418\n486----rcs.size():6[tm0:1507941124683693,tm1:1507941124684247,tm2:1507941124703185(18938),tm3:1507941124703406(19159),tm4:1507941124703447(19200)][tm4-tm0]:19754\nfinish 486 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18477\n487----rcs.size():6[tm0:1507941124734408,tm1:1507941124734965,tm2:1507941124753857(18892),tm3:1507941124754063(19098),tm4:1507941124754105(19140)][tm4-tm0]:19697\nfinish 487 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18269\n488----rcs.size():6[tm0:1507941124784883,tm1:1507941124785510,tm2:1507941124804198(18688),tm3:1507941124804406(18896),tm4:1507941124804436(18926)][tm4-tm0]:19553\nfinish 488 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18472\n489----rcs.size():6[tm0:1507941124836158,tm1:1507941124836734,tm2:1507941124855656(18922),tm3:1507941124855848(19114),tm4:1507941124855879(19145)][tm4-tm0]:19721\nfinish 489 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18566\n490----rcs.size():6[tm0:1507941124886737,tm1:1507941124887337,tm2:1507941124906375(19038),tm3:1507941124906602(19265),tm4:1507941124906645(19308)][tm4-tm0]:19908\nfinish 490 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18648\n491----rcs.size():6[tm0:1507941124937520,tm1:1507941124938157,tm2:1507941124957280(19123),tm3:1507941124957476(19319),tm4:1507941124957521(19364)][tm4-tm0]:20001\nfinish 491 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18475\n492----rcs.size():6[tm0:1507941124987931,tm1:1507941124988475,tm2:1507941125007468(18993),tm3:1507941125007700(19225),tm4:1507941125007744(19269)][tm4-tm0]:19813\nfinish 492 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19058\n493----rcs.size():6[tm0:1507941125040829,tm1:1507941125041426,tm2:1507941125060997(19571),tm3:1507941125061222(19796),tm4:1507941125061269(19843)][tm4-tm0]:20440\nfinish 493 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19012\n494----rcs.size():6[tm0:1507941125091532,tm1:1507941125092106,tm2:1507941125111743(19637),tm3:1507941125111984(19878),tm4:1507941125112017(19911)][tm4-tm0]:20485\nfinish 494 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18758\n495----rcs.size():6[tm0:1507941125146300,tm1:1507941125146856,tm2:1507941125166181(19325),tm3:1507941125166454(19598),tm4:1507941125166502(19646)][tm4-tm0]:20202\nfinish 495 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19446\n496----rcs.size():6[tm0:1507941125197520,tm1:1507941125198245,tm2:1507941125218309(20064),tm3:1507941125218551(20306),tm4:1507941125218595(20350)][tm4-tm0]:21075\nfinish 496 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19269\n497----rcs.size():6[tm0:1507941125252982,tm1:1507941125253917,tm2:1507941125274050(20133),tm3:1507941125274285(20368),tm4:1507941125274320(20403)][tm4-tm0]:21338\nfinish 497 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19687\n498----rcs.size():6[tm0:1507941125306040,tm1:1507941125306995,tm2:1507941125327513(20518),tm3:1507941125327725(20730),tm4:1507941125327771(20776)][tm4-tm0]:21731\nfinish 498 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18631\n499----rcs.size():6[tm0:1507941125361391,tm1:1507941125362374,tm2:1507941125381415(19041),tm3:1507941125381661(19287),tm4:1507941125381704(19330)][tm4-tm0]:20313\nfinish 499 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18872\n500----rcs.size():6[tm0:1507941125412671,tm1:1507941125413253,tm2:1507941125432691(19438),tm3:1507941125432921(19668),tm4:1507941125432964(19711)][tm4-tm0]:20293\nfinish 500 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18455\n501----rcs.size():6[tm0:1507941125461936,tm1:1507941125462548,tm2:1507941125481413(18865),tm3:1507941125481657(19109),tm4:1507941125481697(19149)][tm4-tm0]:19761\nfinish 501 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18642\n502----rcs.size():6[tm0:1507941125511670,tm1:1507941125512240,tm2:1507941125531418(19178),tm3:1507941125531700(19460),tm4:1507941125531740(19500)][tm4-tm0]:20070\nfinish 502 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17617\n503----rcs.size():5[tm0:1507941125561838,tm1:1507941125562402,tm2:1507941125580279(17877),tm3:1507941125580490(18088),tm4:1507941125580516(18114)][tm4-tm0]:18678\nfinish 503 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17843\n504----rcs.size():5[tm0:1507941125610420,tm1:1507941125610971,tm2:1507941125629102(18131),tm3:1507941125629296(18325),tm4:1507941125629330(18359)][tm4-tm0]:18910\nfinish 504 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17936\n505----rcs.size():5[tm0:1507941125659459,tm1:1507941125660097,tm2:1507941125678343(18246),tm3:1507941125678507(18410),tm4:1507941125678532(18435)][tm4-tm0]:19073\nfinish 505 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18103\n506----rcs.size():5[tm0:1507941125708554,tm1:1507941125709105,tm2:1507941125727720(18615),tm3:1507941125727883(18778),tm4:1507941125727917(18812)][tm4-tm0]:19363\nfinish 506 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18112\n507----rcs.size():5[tm0:1507941125757922,tm1:1507941125758597,tm2:1507941125777019(18422),tm3:1507941125777210(18613),tm4:1507941125777244(18647)][tm4-tm0]:19322\nfinish 507 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17840\n508----rcs.size():5[tm0:1507941125811432,tm1:1507941125812118,tm2:1507941125830184(18066),tm3:1507941125830353(18235),tm4:1507941125830387(18269)][tm4-tm0]:18955\nfinish 508 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17783\n509----rcs.size():5[tm0:1507941125860345,tm1:1507941125861008,tm2:1507941125879088(18080),tm3:1507941125879285(18277),tm4:1507941125879319(18311)][tm4-tm0]:18974\nfinish 509 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17908\n510----rcs.size():5[tm0:1507941125909311,tm1:1507941125910182,tm2:1507941125928392(18210),tm3:1507941125928584(18402),tm4:1507941125928617(18435)][tm4-tm0]:19306\nfinish 510 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18018\n511----rcs.size():5[tm0:1507941125958838,tm1:1507941125959764,tm2:1507941125978125(18361),tm3:1507941125978294(18530),tm4:1507941125978333(18569)][tm4-tm0]:19495\nfinish 511 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17806\n512----rcs.size():5[tm0:1507941126011608,tm1:1507941126012258,tm2:1507941126030325(18067),tm3:1507941126030503(18245),tm4:1507941126030530(18272)][tm4-tm0]:18922\nfinish 512 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17817\n513----rcs.size():5[tm0:1507941126061309,tm1:1507941126061991,tm2:1507941126080088(18097),tm3:1507941126080336(18345),tm4:1507941126080362(18371)][tm4-tm0]:19053\nfinish 513 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17899\n514----rcs.size():5[tm0:1507941126110233,tm1:1507941126110933,tm2:1507941126129155(18222),tm3:1507941126129319(18386),tm4:1507941126129358(18425)][tm4-tm0]:19125\nfinish 514 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18178\n515----rcs.size():4[tm0:1507941126159471,tm1:1507941126160060,tm2:1507941126178672(18612),tm3:1507941126178820(18760),tm4:1507941126178842(18782)][tm4-tm0]:19371\nfinish 515 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18518\n516----rcs.size():5[tm0:1507941126207629,tm1:1507941126208203,tm2:1507941126227029(18826),tm3:1507941126227268(19065),tm4:1507941126227290(19087)][tm4-tm0]:19661\nfinish 516 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18097\n517----rcs.size():5[tm0:1507941126261008,tm1:1507941126261632,tm2:1507941126280029(18397),tm3:1507941126280274(18642),tm4:1507941126280372(18740)][tm4-tm0]:19364\nfinish 517 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18178\n518----rcs.size():5[tm0:1507941126310140,tm1:1507941126310851,tm2:1507941126329410(18559),tm3:1507941126329660(18809),tm4:1507941126329702(18851)][tm4-tm0]:19562\nfinish 518 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18115\n519----rcs.size():5[tm0:1507941126359920,tm1:1507941126360536,tm2:1507941126379051(18515),tm3:1507941126379220(18684),tm4:1507941126379257(18721)][tm4-tm0]:19337\nfinish 519 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18061\n520----rcs.size():5[tm0:1507941126409593,tm1:1507941126410227,tm2:1507941126428651(18424),tm3:1507941126428823(18596),tm4:1507941126428860(18633)][tm4-tm0]:19267\nfinish 520 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18237\n521----rcs.size():5[tm0:1507941126458596,tm1:1507941126459438,tm2:1507941126478171(18733),tm3:1507941126478428(18990),tm4:1507941126478467(19029)][tm4-tm0]:19871\nfinish 521 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18064\n522----rcs.size():5[tm0:1507941126510866,tm1:1507941126511437,tm2:1507941126529883(18446),tm3:1507941126530157(18720),tm4:1507941126530196(18759)][tm4-tm0]:19330\nfinish 522 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18254\n523----rcs.size():5[tm0:1507941126561054,tm1:1507941126561629,tm2:1507941126580195(18566),tm3:1507941126580381(18752),tm4:1507941126580416(18787)][tm4-tm0]:19362\nfinish 523 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:17974\n524----rcs.size():5[tm0:1507941126610993,tm1:1507941126611607,tm2:1507941126629902(18295),tm3:1507941126630064(18457),tm4:1507941126630100(18493)][tm4-tm0]:19107\nfinish 524 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:17963\n525----rcs.size():5[tm0:1507941126660176,tm1:1507941126660761,tm2:1507941126679078(18317),tm3:1507941126679283(18522),tm4:1507941126679321(18560)][tm4-tm0]:19145\nfinish 525 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18277\n526----rcs.size():5[tm0:1507941126709709,tm1:1507941126710356,tm2:1507941126729005(18649),tm3:1507941126729213(18857),tm4:1507941126729250(18894)][tm4-tm0]:19541\nfinish 526 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18344\n527----rcs.size():5[tm0:1507941126758817,tm1:1507941126759570,tm2:1507941126778302(18732),tm3:1507941126778474(18904),tm4:1507941126778500(18930)][tm4-tm0]:19683\nfinish 527 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18760\n528----rcs.size():5[tm0:1507941126807907,tm1:1507941126808462,tm2:1507941126827725(19263),tm3:1507941126827889(19427),tm4:1507941126827930(19468)][tm4-tm0]:20023\nfinish 528 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18456\n529----rcs.size():5[tm0:1507941126858004,tm1:1507941126858672,tm2:1507941126877821(19149),tm3:1507941126877987(19315),tm4:1507941126878029(19357)][tm4-tm0]:20025\nfinish 529 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18290\n530----rcs.size():5[tm0:1507941126908416,tm1:1507941126909273,tm2:1507941126927995(18722),tm3:1507941126928217(18944),tm4:1507941126928253(18980)][tm4-tm0]:19837\nfinish 530 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18344\n531----rcs.size():5[tm0:1507941126961846,tm1:1507941126962483,tm2:1507941126981295(18812),tm3:1507941126981497(19014),tm4:1507941126981539(19056)][tm4-tm0]:19693\nfinish 531 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18486\n532----rcs.size():5[tm0:1507941127011734,tm1:1507941127012309,tm2:1507941127031264(18955),tm3:1507941127031471(19162),tm4:1507941127031510(19201)][tm4-tm0]:19776\nfinish 532 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18266\n533----rcs.size():5[tm0:1507941127061655,tm1:1507941127062224,tm2:1507941127080913(18689),tm3:1507941127081118(18894),tm4:1507941127081182(18958)][tm4-tm0]:19527\nfinish 533 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18422\n534----rcs.size():5[tm0:1507941127111002,tm1:1507941127111731,tm2:1507941127130560(18829),tm3:1507941127130767(19036),tm4:1507941127130810(19079)][tm4-tm0]:19808\nfinish 534 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18487\n535----rcs.size():5[tm0:1507941127161017,tm1:1507941127161659,tm2:1507941127180637(18978),tm3:1507941127180826(19167),tm4:1507941127180866(19207)][tm4-tm0]:19849\nfinish 535 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18739\n536----rcs.size():4[tm0:1507941127211389,tm1:1507941127212096,tm2:1507941127231341(19245),tm3:1507941127231518(19422),tm4:1507941127231552(19456)][tm4-tm0]:20163\nfinish 536 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18562\n537----rcs.size():4[tm0:1507941127262055,tm1:1507941127262750,tm2:1507941127281744(18994),tm3:1507941127281894(19144),tm4:1507941127281930(19180)][tm4-tm0]:19875\nfinish 537 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18486\n538----rcs.size():4[tm0:1507941127312095,tm1:1507941127312869,tm2:1507941127331846(18977),tm3:1507941127332012(19143),tm4:1507941127332049(19180)][tm4-tm0]:19954\nfinish 538 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18665\n539----rcs.size():4[tm0:1507941127362114,tm1:1507941127362783,tm2:1507941127382015(19232),tm3:1507941127382184(19401),tm4:1507941127382220(19437)][tm4-tm0]:20106\nfinish 539 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18572\n540----rcs.size():4[tm0:1507941127412464,tm1:1507941127413129,tm2:1507941127432150(19021),tm3:1507941127432305(19176),tm4:1507941127432341(19212)][tm4-tm0]:19877\nfinish 540 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18451\n541----rcs.size():5[tm0:1507941127466552,tm1:1507941127467284,tm2:1507941127486187(18903),tm3:1507941127486395(19111),tm4:1507941127486437(19153)][tm4-tm0]:19885\nfinish 541 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18865\n542----rcs.size():5[tm0:1507941127517054,tm1:1507941127517787,tm2:1507941127537205(19418),tm3:1507941127537398(19611),tm4:1507941127537445(19658)][tm4-tm0]:20391\nfinish 542 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18641\n543----rcs.size():5[tm0:1507941127570669,tm1:1507941127571339,tm2:1507941127590506(19167),tm3:1507941127590706(19367),tm4:1507941127590747(19408)][tm4-tm0]:20078\nfinish 543 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18803\n544----rcs.size():5[tm0:1507941127622198,tm1:1507941127622817,tm2:1507941127642168(19351),tm3:1507941127642368(19551),tm4:1507941127642411(19594)][tm4-tm0]:20213\nfinish 544 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19009\n545----rcs.size():5[tm0:1507941127672488,tm1:1507941127673166,tm2:1507941127692692(19526),tm3:1507941127692897(19731),tm4:1507941127692944(19778)][tm4-tm0]:20456\nfinish 545 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19170\n546----rcs.size():5[tm0:1507941127722988,tm1:1507941127723688,tm2:1507941127743462(19774),tm3:1507941127743666(19978),tm4:1507941127743714(20026)][tm4-tm0]:20726\nfinish 546 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19169\n547----rcs.size():5[tm0:1507941127773956,tm1:1507941127774674,tm2:1507941127794404(19730),tm3:1507941127794628(19954),tm4:1507941127794662(19988)][tm4-tm0]:20706\nfinish 547 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19774\n548----rcs.size():5[tm0:1507941127824127,tm1:1507941127824679,tm2:1507941127845060(20381),tm3:1507941127845267(20588),tm4:1507941127845313(20634)][tm4-tm0]:21186\nfinish 548 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19424\n549----rcs.size():5[tm0:1507941127875818,tm1:1507941127876803,tm2:1507941127897235(20432),tm3:1507941127897429(20626),tm4:1507941127897459(20656)][tm4-tm0]:21641\nfinish 549 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19311\n550----rcs.size():5[tm0:1507941127930409,tm1:1507941127931276,tm2:1507941127951492(20216),tm3:1507941127951685(20409),tm4:1507941127951721(20445)][tm4-tm0]:21312\nfinish 550 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19665\n551----rcs.size():5[tm0:1507941127980917,tm1:1507941127981913,tm2:1507941128002617(20704),tm3:1507941128002808(20895),tm4:1507941128002862(20949)][tm4-tm0]:21945\nfinish 551 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19345\n552----rcs.size():5[tm0:1507941128033224,tm1:1507941128034220,tm2:1507941128054669(20449),tm3:1507941128054895(20675),tm4:1507941128054948(20728)][tm4-tm0]:21724\nfinish 552 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19463\n553----rcs.size():5[tm0:1507941128085557,tm1:1507941128086506,tm2:1507941128107002(20496),tm3:1507941128107219(20713),tm4:1507941128107270(20764)][tm4-tm0]:21713\nfinish 553 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19751\n554----rcs.size():5[tm0:1507941128141049,tm1:1507941128141960,tm2:1507941128163131(21171),tm3:1507941128163350(21390),tm4:1507941128163417(21457)][tm4-tm0]:22368\nfinish 554 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19627\n555----rcs.size():5[tm0:1507941128194110,tm1:1507941128195131,tm2:1507941128216176(21045),tm3:1507941128216372(21241),tm4:1507941128216420(21289)][tm4-tm0]:22310\nfinish 555 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19279\n556----rcs.size():5[tm0:1507941128247309,tm1:1507941128248370,tm2:1507941128268790(20420),tm3:1507941128269005(20635),tm4:1507941128269049(20679)][tm4-tm0]:21740\nfinish 556 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19211\n557----rcs.size():5[tm0:1507941128300049,tm1:1507941128301008,tm2:1507941128321117(20109),tm3:1507941128321348(20340),tm4:1507941128321393(20385)][tm4-tm0]:21344\nfinish 557 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18973\n558----rcs.size():5[tm0:1507941128352040,tm1:1507941128353045,tm2:1507941128372569(19524),tm3:1507941128372781(19736),tm4:1507941128372825(19780)][tm4-tm0]:20785\nfinish 558 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19754\n559----rcs.size():5[tm0:1507941128402891,tm1:1507941128403539,tm2:1507941128424177(20638),tm3:1507941128424384(20845),tm4:1507941128424427(20888)][tm4-tm0]:21536\nfinish 559 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18852\n560----rcs.size():4[tm0:1507941128455271,tm1:1507941128456183,tm2:1507941128475480(19297),tm3:1507941128475682(19499),tm4:1507941128475803(19620)][tm4-tm0]:20532\nfinish 560 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18776\n561----rcs.size():4[tm0:1507941128505199,tm1:1507941128505874,tm2:1507941128525126(19252),tm3:1507941128525305(19431),tm4:1507941128525341(19467)][tm4-tm0]:20142\nfinish 561 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18982\n562----rcs.size():4[tm0:1507941128555415,tm1:1507941128556067,tm2:1507941128575606(19539),tm3:1507941128575764(19697),tm4:1507941128575799(19732)][tm4-tm0]:20384\nfinish 562 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18870\n563----rcs.size():4[tm0:1507941128605874,tm1:1507941128606508,tm2:1507941128625887(19379),tm3:1507941128626043(19535),tm4:1507941128626068(19560)][tm4-tm0]:20194\nfinish 563 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19086\n564----rcs.size():4[tm0:1507941128655899,tm1:1507941128656595,tm2:1507941128676201(19606),tm3:1507941128676357(19762),tm4:1507941128676413(19818)][tm4-tm0]:20514\nfinish 564 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18849\n565----rcs.size():4[tm0:1507941128706610,tm1:1507941128707163,tm2:1507941128726534(19371),tm3:1507941128726691(19528),tm4:1507941128726733(19570)][tm4-tm0]:20123\nfinish 565 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18894\n566----rcs.size():4[tm0:1507941128756560,tm1:1507941128757113,tm2:1507941128776507(19394),tm3:1507941128776665(19552),tm4:1507941128776692(19579)][tm4-tm0]:20132\nfinish 566 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19141\n567----rcs.size():4[tm0:1507941128806639,tm1:1507941128807358,tm2:1507941128827064(19706),tm3:1507941128827211(19853),tm4:1507941128827265(19907)][tm4-tm0]:20626\nfinish 567 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19138\n568----rcs.size():4[tm0:1507941128856969,tm1:1507941128857691,tm2:1507941128877351(19660),tm3:1507941128877511(19820),tm4:1507941128877552(19861)][tm4-tm0]:20583\nfinish 568 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18754\n569----rcs.size():4[tm0:1507941128912696,tm1:1507941128913435,tm2:1507941128932649(19214),tm3:1507941128932806(19371),tm4:1507941128932844(19409)][tm4-tm0]:20148\nfinish 569 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18198\n570----rcs.size():4[tm0:1507941128962208,tm1:1507941128962801,tm2:1507941128981446(18645),tm3:1507941128981608(18807),tm4:1507941128981633(18832)][tm4-tm0]:19425\nfinish 570 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18688\n571----rcs.size():4[tm0:1507941129011905,tm1:1507941129012596,tm2:1507941129031821(19225),tm3:1507941129031985(19389),tm4:1507941129032020(19424)][tm4-tm0]:20115\nfinish 571 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18869\n572----rcs.size():4[tm0:1507941129066849,tm1:1507941129067465,tm2:1507941129086963(19498),tm3:1507941129087112(19647),tm4:1507941129087194(19729)][tm4-tm0]:20345\nfinish 572 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18791\n573----rcs.size():4[tm0:1507941129122821,tm1:1507941129123364,tm2:1507941129142671(19307),tm3:1507941129142836(19472),tm4:1507941129142870(19506)][tm4-tm0]:20049\nfinish 573 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18624\n574----rcs.size():3[tm0:1507941129173686,tm1:1507941129174277,tm2:1507941129193262(18985),tm3:1507941129193431(19154),tm4:1507941129193459(19182)][tm4-tm0]:19773\nfinish 574 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18245\n575----rcs.size():3[tm0:1507941129228102,tm1:1507941129228625,tm2:1507941129247279(18654),tm3:1507941129247403(18778),tm4:1507941129247431(18806)][tm4-tm0]:19329\nfinish 575 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18079\n576----rcs.size():3[tm0:1507941129281202,tm1:1507941129281838,tm2:1507941129300260(18422),tm3:1507941129300373(18535),tm4:1507941129300403(18565)][tm4-tm0]:19201\nfinish 576 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18193\n577----rcs.size():3[tm0:1507941129330274,tm1:1507941129330978,tm2:1507941129349545(18567),tm3:1507941129349682(18704),tm4:1507941129349705(18727)][tm4-tm0]:19431\nfinish 577 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18150\n578----rcs.size():3[tm0:1507941129383214,tm1:1507941129383887,tm2:1507941129402473(18586),tm3:1507941129402620(18733),tm4:1507941129402650(18763)][tm4-tm0]:19436\nfinish 578 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18273\n579----rcs.size():3[tm0:1507941129433153,tm1:1507941129433861,tm2:1507941129452584(18723),tm3:1507941129452731(18870),tm4:1507941129452823(18962)][tm4-tm0]:19670\nfinish 579 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18201\n580----rcs.size():3[tm0:1507941129483120,tm1:1507941129483753,tm2:1507941129502357(18604),tm3:1507941129502489(18736),tm4:1507941129502522(18769)][tm4-tm0]:19402\nfinish 580 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18424\n581----rcs.size():3[tm0:1507941129532823,tm1:1507941129533512,tm2:1507941129552403(18891),tm3:1507941129552518(19006),tm4:1507941129552539(19027)][tm4-tm0]:19716\nfinish 581 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18220\n582----rcs.size():3[tm0:1507941129586180,tm1:1507941129586794,tm2:1507941129605442(18648),tm3:1507941129605559(18765),tm4:1507941129605597(18803)][tm4-tm0]:19417\nfinish 582 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18199\n583----rcs.size():3[tm0:1507941129635298,tm1:1507941129636007,tm2:1507941129654587(18580),tm3:1507941129654739(18732),tm4:1507941129654773(18766)][tm4-tm0]:19475\nfinish 583 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18219\n584----rcs.size():3[tm0:1507941129685153,tm1:1507941129685705,tm2:1507941129704398(18693),tm3:1507941129704534(18829),tm4:1507941129704581(18876)][tm4-tm0]:19428\nfinish 584 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18375\n585----rcs.size():3[tm0:1507941129734575,tm1:1507941129735247,tm2:1507941129754003(18756),tm3:1507941129754121(18874),tm4:1507941129754166(18919)][tm4-tm0]:19591\nfinish 585 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18210\n586----rcs.size():3[tm0:1507941129785210,tm1:1507941129785910,tm2:1507941129804541(18631),tm3:1507941129804680(18770),tm4:1507941129804713(18803)][tm4-tm0]:19503\nfinish 586 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18440\n587----rcs.size():3[tm0:1507941129834948,tm1:1507941129835618,tm2:1507941129854544(18926),tm3:1507941129854700(19082),tm4:1507941129854723(19105)][tm4-tm0]:19775\nfinish 587 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18290\n588----rcs.size():3[tm0:1507941129884977,tm1:1507941129885541,tm2:1507941129904275(18734),tm3:1507941129904421(18880),tm4:1507941129904453(18912)][tm4-tm0]:19476\nfinish 588 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18321\n589----rcs.size():3[tm0:1507941129935151,tm1:1507941129935843,tm2:1507941129954611(18768),tm3:1507941129954753(18910),tm4:1507941129954787(18944)][tm4-tm0]:19636\nfinish 589 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18404\n590----rcs.size():3[tm0:1507941129984478,tm1:1507941129985174,tm2:1507941130004024(18850),tm3:1507941130004177(19003),tm4:1507941130004213(19039)][tm4-tm0]:19735\nfinish 590 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18638\n591----rcs.size():3[tm0:1507941130034744,tm1:1507941130035456,tm2:1507941130054601(19145),tm3:1507941130054739(19283),tm4:1507941130054775(19319)][tm4-tm0]:20031\nfinish 591 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18340\n592----rcs.size():3[tm0:1507941130084673,tm1:1507941130085311,tm2:1507941130104074(18763),tm3:1507941130104223(18912),tm4:1507941130104256(18945)][tm4-tm0]:19583\nfinish 592 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18528\n593----rcs.size():3[tm0:1507941130134927,tm1:1507941130135627,tm2:1507941130154623(18996),tm3:1507941130154748(19121),tm4:1507941130154771(19144)][tm4-tm0]:19844\nfinish 593 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18298\n594----rcs.size():3[tm0:1507941130185010,tm1:1507941130185647,tm2:1507941130204444(18797),tm3:1507941130204603(18956),tm4:1507941130204714(19067)][tm4-tm0]:19704\nfinish 594 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18404\n595----rcs.size():3[tm0:1507941130234406,tm1:1507941130234977,tm2:1507941130253860(18883),tm3:1507941130253986(19009),tm4:1507941130254009(19032)][tm4-tm0]:19603\nfinish 595 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18771\n596----rcs.size():3[tm0:1507941130288796,tm1:1507941130289361,tm2:1507941130308663(19302),tm3:1507941130308784(19423),tm4:1507941130308807(19446)][tm4-tm0]:20011\nfinish 596 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18673\n597----rcs.size():3[tm0:1507941130341443,tm1:1507941130342333,tm2:1507941130361564(19231),tm3:1507941130361687(19354),tm4:1507941130361710(19377)][tm4-tm0]:20267\nfinish 597 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18608\n598----rcs.size():3[tm0:1507941130395579,tm1:1507941130396174,tm2:1507941130415288(19114),tm3:1507941130415448(19274),tm4:1507941130415484(19310)][tm4-tm0]:19905\nfinish 598 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18623\n599----rcs.size():3[tm0:1507941130449022,tm1:1507941130449587,tm2:1507941130468968(19381),tm3:1507941130469145(19558),tm4:1507941130469180(19593)][tm4-tm0]:20158\nfinish 599 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18651\n600----rcs.size():3[tm0:1507941130500363,tm1:1507941130500936,tm2:1507941130520108(19172),tm3:1507941130520278(19342),tm4:1507941130520316(19380)][tm4-tm0]:19953\nfinish 600 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18815\n601----rcs.size():3[tm0:1507941130549658,tm1:1507941130550357,tm2:1507941130569799(19442),tm3:1507941130569927(19570),tm4:1507941130569965(19608)][tm4-tm0]:20307\nfinish 601 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18840\n602----rcs.size():3[tm0:1507941130602334,tm1:1507941130602892,tm2:1507941130622369(19477),tm3:1507941130622501(19609),tm4:1507941130622537(19645)][tm4-tm0]:20203\nfinish 602 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18716\n603----rcs.size():3[tm0:1507941130652254,tm1:1507941130652811,tm2:1507941130672151(19340),tm3:1507941130672281(19470),tm4:1507941130672304(19493)][tm4-tm0]:20050\nfinish 603 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18759\n604----rcs.size():3[tm0:1507941130701419,tm1:1507941130701996,tm2:1507941130721343(19347),tm3:1507941130721470(19474),tm4:1507941130721492(19496)][tm4-tm0]:20073\nfinish 604 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18877\n605----rcs.size():3[tm0:1507941130751309,tm1:1507941130751928,tm2:1507941130771402(19474),tm3:1507941130771530(19602),tm4:1507941130771562(19634)][tm4-tm0]:20253\nfinish 605 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18812\n606----rcs.size():2[tm0:1507941130801776,tm1:1507941130802424,tm2:1507941130821871(19447),tm3:1507941130821990(19566),tm4:1507941130822016(19592)][tm4-tm0]:20240\nfinish 606 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18764\n607----rcs.size():2[tm0:1507941130851531,tm1:1507941130852046,tm2:1507941130871473(19427),tm3:1507941130871552(19506),tm4:1507941130871569(19523)][tm4-tm0]:20038\nfinish 607 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19612\n608----rcs.size():2[tm0:1507941130902390,tm1:1507941130902906,tm2:1507941130923481(20575),tm3:1507941130923565(20659),tm4:1507941130923591(20685)][tm4-tm0]:21201\nfinish 608 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19593\n609----rcs.size():2[tm0:1507941130958028,tm1:1507941130959306,tm2:1507941130980226(20920),tm3:1507941130980304(20998),tm4:1507941130980322(21016)][tm4-tm0]:22294\nfinish 609 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19831\n610----rcs.size():2[tm0:1507941131011386,tm1:1507941131012370,tm2:1507941131033479(21109),tm3:1507941131033563(21193),tm4:1507941131033582(21212)][tm4-tm0]:22196\nfinish 610 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19761\n611----rcs.size():2[tm0:1507941131063995,tm1:1507941131065023,tm2:1507941131086190(21167),tm3:1507941131086275(21252),tm4:1507941131086303(21280)][tm4-tm0]:22308\nfinish 611 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19537\n612----rcs.size():2[tm0:1507941131118049,tm1:1507941131119116,tm2:1507941131140258(21142),tm3:1507941131140342(21226),tm4:1507941131140369(21253)][tm4-tm0]:22320\nfinish 612 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:20221\n613----rcs.size():2[tm0:1507941131170685,tm1:1507941131171624,tm2:1507941131193163(21539),tm3:1507941131193265(21641),tm4:1507941131193292(21668)][tm4-tm0]:22607\nfinish 613 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19768\n614----rcs.size():2[tm0:1507941131224789,tm1:1507941131225993,tm2:1507941131247534(21541),tm3:1507941131247634(21641),tm4:1507941131247728(21735)][tm4-tm0]:22939\nfinish 614 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19863\n615----rcs.size():2[tm0:1507941131279239,tm1:1507941131280172,tm2:1507941131301498(21326),tm3:1507941131301597(21425),tm4:1507941131301615(21443)][tm4-tm0]:22376\nfinish 615 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19525\n616----rcs.size():2[tm0:1507941131333316,tm1:1507941131334194,tm2:1507941131355101(20907),tm3:1507941131355212(21018),tm4:1507941131355231(21037)][tm4-tm0]:21915\nfinish 616 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:20231\n617----rcs.size():2[tm0:1507941131386389,tm1:1507941131387345,tm2:1507941131409239(21894),tm3:1507941131409325(21980),tm4:1507941131409354(22009)][tm4-tm0]:22965\nfinish 617 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19577\n618----rcs.size():2[tm0:1507941131440480,tm1:1507941131441556,tm2:1507941131463167(21611),tm3:1507941131463254(21698),tm4:1507941131463275(21719)][tm4-tm0]:22795\nfinish 618 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:20184\n619----rcs.size():2[tm0:1507941131494946,tm1:1507941131495895,tm2:1507941131518590(22695),tm3:1507941131518695(22800),tm4:1507941131518792(22897)][tm4-tm0]:23846\nfinish 619 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18500\n620----rcs.size():1[tm0:1507941131548969,tm1:1507941131550307,tm2:1507941131569301(18994),tm3:1507941131569376(19069),tm4:1507941131569388(19081)][tm4-tm0]:20419\nfinish 620 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:20129\n621----rcs.size():2[tm0:1507941131599501,tm1:1507941131600099,tm2:1507941131623101(23002),tm3:1507941131623197(23098),tm4:1507941131623216(23117)][tm4-tm0]:23715\nfinish 621 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:20085\n622----rcs.size():2[tm0:1507941131653383,tm1:1507941131654675,tm2:1507941131677093(22418),tm3:1507941131677189(22514),tm4:1507941131677210(22535)][tm4-tm0]:23827\nfinish 622 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:20097\n623----rcs.size():2[tm0:1507941131707861,tm1:1507941131709609,tm2:1507941131732095(22486),tm3:1507941131732191(22582),tm4:1507941131732210(22601)][tm4-tm0]:24349\nfinish 623 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:20382\n624----rcs.size():2[tm0:1507941131762685,tm1:1507941131764023,tm2:1507941131787058(23035),tm3:1507941131787174(23151),tm4:1507941131787207(23184)][tm4-tm0]:24522\nfinish 624 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:20355\n625----rcs.size():2[tm0:1507941131819531,tm1:1507941131820924,tm2:1507941131843718(22794),tm3:1507941131843822(22898),tm4:1507941131843856(22932)][tm4-tm0]:24325\nfinish 625 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:20097\n626----rcs.size():2[tm0:1507941131875367,tm1:1507941131876794,tm2:1507941131899236(22442),tm3:1507941131899343(22549),tm4:1507941131899377(22583)][tm4-tm0]:24010\nfinish 626 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19713\n627----rcs.size():2[tm0:1507941131930880,tm1:1507941131932333,tm2:1507941131953827(21494),tm3:1507941131953915(21582),tm4:1507941131953947(21614)][tm4-tm0]:23067\nfinish 627 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19043\n628----rcs.size():1[tm0:1507941131985758,tm1:1507941131986761,tm2:1507941132006413(19652),tm3:1507941132006494(19733),tm4:1507941132006510(19749)][tm4-tm0]:20752\nfinish 628 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18505\n629----rcs.size():1[tm0:1507941132036995,tm1:1507941132037597,tm2:1507941132056671(19074),tm3:1507941132056742(19145),tm4:1507941132056757(19160)][tm4-tm0]:19762\nfinish 629 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18550\n630----rcs.size():1[tm0:1507941132087633,tm1:1507941132088233,tm2:1507941132107334(19101),tm3:1507941132107391(19158),tm4:1507941132107406(19173)][tm4-tm0]:19773\nfinish 630 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18439\n631----rcs.size():1[tm0:1507941132141776,tm1:1507941132142500,tm2:1507941132161523(19023),tm3:1507941132161595(19095),tm4:1507941132161609(19109)][tm4-tm0]:19833\nfinish 631 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18830\n632----rcs.size():1[tm0:1507941132196187,tm1:1507941132196818,tm2:1507941132216228(19410),tm3:1507941132216301(19483),tm4:1507941132216316(19498)][tm4-tm0]:20129\nfinish 632 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18706\n633----rcs.size():1[tm0:1507941132251297,tm1:1507941132251816,tm2:1507941132271253(19437),tm3:1507941132271327(19511),tm4:1507941132271372(19556)][tm4-tm0]:20075\nfinish 633 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19009\n634----rcs.size():1[tm0:1507941132306270,tm1:1507941132306845,tm2:1507941132326588(19743),tm3:1507941132326645(19800),tm4:1507941132326660(19815)][tm4-tm0]:20390\nfinish 634 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19320\n635----rcs.size():1[tm0:1507941132357309,tm1:1507941132357921,tm2:1507941132378135(20214),tm3:1507941132378202(20281),tm4:1507941132378214(20293)][tm4-tm0]:20905\nfinish 635 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18331\n636----rcs.size():1[tm0:1507941132411025,tm1:1507941132411531,tm2:1507941132430562(19031),tm3:1507941132430637(19106),tm4:1507941132430653(19122)][tm4-tm0]:19628\nfinish 636 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19022\n637----rcs.size():1[tm0:1507941132462933,tm1:1507941132463484,tm2:1507941132483322(19838),tm3:1507941132483382(19898),tm4:1507941132483399(19915)][tm4-tm0]:20466\nfinish 637 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19061\n638----rcs.size():1[tm0:1507941132516959,tm1:1507941132517484,tm2:1507941132537309(19825),tm3:1507941132537376(19892),tm4:1507941132537391(19907)][tm4-tm0]:20432\nfinish 638 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18968\n639----rcs.size():1[tm0:1507941132573360,tm1:1507941132573881,tm2:1507941132593761(19880),tm3:1507941132593818(19937),tm4:1507941132593834(19953)][tm4-tm0]:20474\nfinish 639 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19079\n640----rcs.size():1[tm0:1507941132629598,tm1:1507941132630159,tm2:1507941132650080(19921),tm3:1507941132650148(19989),tm4:1507941132650166(20007)][tm4-tm0]:20568\nfinish 640 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19016\n641----rcs.size():1[tm0:1507941132683666,tm1:1507941132684277,tm2:1507941132704045(19768),tm3:1507941132704118(19841),tm4:1507941132704135(19858)][tm4-tm0]:20469\nfinish 641 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19081\n642----rcs.size():1[tm0:1507941132734644,tm1:1507941132735167,tm2:1507941132755111(19944),tm3:1507941132755179(20012),tm4:1507941132755197(20030)][tm4-tm0]:20553\nfinish 642 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:19768\n643----rcs.size():1[tm0:1507941132787391,tm1:1507941132788392,tm2:1507941132809152(20760),tm3:1507941132809265(20873),tm4:1507941132809282(20890)][tm4-tm0]:21891\nfinish 643 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19054\n644----rcs.size():1[tm0:1507941132842896,tm1:1507941132843438,tm2:1507941132863257(19819),tm3:1507941132863315(19877),tm4:1507941132863341(19903)][tm4-tm0]:20445\nfinish 644 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18828\n645----rcs.size():1[tm0:1507941132894400,tm1:1507941132894961,tm2:1507941132914480(19519),tm3:1507941132914538(19577),tm4:1507941132914552(19591)][tm4-tm0]:20152\nfinish 645 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19308\n646----rcs.size():1[tm0:1507941132947461,tm1:1507941132948024,tm2:1507941132968241(20217),tm3:1507941132968314(20290),tm4:1507941132968324(20300)][tm4-tm0]:20863\nfinish 646 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:19603\n647----rcs.size():1[tm0:1507941133001692,tm1:1507941133002619,tm2:1507941133023292(20673),tm3:1507941133023352(20733),tm4:1507941133023366(20747)][tm4-tm0]:21674\nfinish 647 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18696\n648----rcs.size():1[tm0:1507941133057953,tm1:1507941133058655,tm2:1507941133078101(19446),tm3:1507941133078169(19514),tm4:1507941133078183(19528)][tm4-tm0]:20230\nfinish 648 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:16\n(incpp)call encode cost time:tmd-tmc:18692\n649----rcs.size():1[tm0:1507941133109549,tm1:1507941133110096,tm2:1507941133129369(19273),tm3:1507941133129441(19345),tm4:1507941133129451(19355)][tm4-tm0]:19902\nfinish 649 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:17\n(incpp)call encode cost time:tmd-tmc:18403\n650----rcs.size():1[tm0:1507941133162424,tm1:1507941133162947,tm2:1507941133181840(18893),tm3:1507941133181929(18982),tm4:1507941133181941(18994)][tm4-tm0]:19517\nfinish 650 frame\n651----rcs.size():0[tm0:1507941133211587,tm1:1507941133212187,tm2:1507941133212187(0),tm3:1507941133212195(8),tm4:1507941133212195(8)][tm4-tm0]:608\nfinish 651 frame\n652----rcs.size():0[tm0:1507941133243826,tm1:1507941133244380,tm2:1507941133244380(0),tm3:1507941133244388(8),tm4:1507941133244389(9)][tm4-tm0]:563\nfinish 652 frame\n653----rcs.size():0[tm0:1507941133279882,tm1:1507941133280442,tm2:1507941133280442(0),tm3:1507941133280450(8),tm4:1507941133280451(9)][tm4-tm0]:569\nfinish 653 frame\n654----rcs.size():0[tm0:1507941133314802,tm1:1507941133315343,tm2:1507941133315343(0),tm3:1507941133315351(8),tm4:1507941133315351(8)][tm4-tm0]:549\nfinish 654 frame\n655----rcs.size():0[tm0:1507941133349132,tm1:1507941133349712,tm2:1507941133349712(0),tm3:1507941133349720(8),tm4:1507941133349721(9)][tm4-tm0]:589\nfinish 655 frame\n656----rcs.size():0[tm0:1507941133383930,tm1:1507941133384565,tm2:1507941133384565(0),tm3:1507941133384573(8),tm4:1507941133384573(8)][tm4-tm0]:643\nfinish 656 frame\n657----rcs.size():0[tm0:1507941133419839,tm1:1507941133420400,tm2:1507941133420400(0),tm3:1507941133420408(8),tm4:1507941133420408(8)][tm4-tm0]:569\nfinish 657 frame\n658----rcs.size():0[tm0:1507941133454681,tm1:1507941133455259,tm2:1507941133455259(0),tm3:1507941133455267(8),tm4:1507941133455267(8)][tm4-tm0]:586\nfinish 658 frame\n659----rcs.size():0[tm0:1507941133489083,tm1:1507941133489604,tm2:1507941133489604(0),tm3:1507941133489610(6),tm4:1507941133489611(7)][tm4-tm0]:528\nfinish 659 frame\n660----rcs.size():0[tm0:1507941133523902,tm1:1507941133524626,tm2:1507941133524626(0),tm3:1507941133524650(24),tm4:1507941133524651(25)][tm4-tm0]:749\nfinish 660 frame\n661----rcs.size():0[tm0:1507941133560082,tm1:1507941133560672,tm2:1507941133560672(0),tm3:1507941133560678(6),tm4:1507941133560679(7)][tm4-tm0]:597\nfinish 661 frame\n662----rcs.size():0[tm0:1507941133595006,tm1:1507941133595595,tm2:1507941133595595(0),tm3:1507941133595601(6),tm4:1507941133595602(7)][tm4-tm0]:596\nfinish 662 frame\n663----rcs.size():0[tm0:1507941133630547,tm1:1507941133631083,tm2:1507941133631083(0),tm3:1507941133631090(7),tm4:1507941133631090(7)][tm4-tm0]:543\nfinish 663 frame\n664----rcs.size():0[tm0:1507941133665658,tm1:1507941133666379,tm2:1507941133666379(0),tm3:1507941133666403(24),tm4:1507941133666403(24)][tm4-tm0]:745\nfinish 664 frame\n665----rcs.size():0[tm0:1507941133700810,tm1:1507941133701366,tm2:1507941133701366(0),tm3:1507941133701372(6),tm4:1507941133701373(7)][tm4-tm0]:563\nfinish 665 frame\n666----rcs.size():0[tm0:1507941133735760,tm1:1507941133736400,tm2:1507941133736400(0),tm3:1507941133736406(6),tm4:1507941133736406(6)][tm4-tm0]:646\nfinish 666 frame\n667----rcs.size():0[tm0:1507941133771436,tm1:1507941133771989,tm2:1507941133771989(0),tm3:1507941133771996(7),tm4:1507941133771996(7)][tm4-tm0]:560\nfinish 667 frame\n668----rcs.size():0[tm0:1507941133806764,tm1:1507941133807383,tm2:1507941133807383(0),tm3:1507941133807390(7),tm4:1507941133807390(7)][tm4-tm0]:626\nfinish 668 frame\n669----rcs.size():0[tm0:1507941133842229,tm1:1507941133842765,tm2:1507941133842765(0),tm3:1507941133842771(6),tm4:1507941133842771(6)][tm4-tm0]:542\nfinish 669 frame\n670----rcs.size():0[tm0:1507941133879067,tm1:1507941133879606,tm2:1507941133879606(0),tm3:1507941133879612(6),tm4:1507941133879613(7)][tm4-tm0]:546\nfinish 670 frame\n671----rcs.size():0[tm0:1507941133915056,tm1:1507941133915576,tm2:1507941133915576(0),tm3:1507941133915582(6),tm4:1507941133915583(7)][tm4-tm0]:527\nfinish 671 frame\n672----rcs.size():0[tm0:1507941133950978,tm1:1507941133951584,tm2:1507941133951584(0),tm3:1507941133951590(6),tm4:1507941133951591(7)][tm4-tm0]:613\nfinish 672 frame\n673----rcs.size():0[tm0:1507941133986143,tm1:1507941133986766,tm2:1507941133986766(0),tm3:1507941133986772(6),tm4:1507941133986772(6)][tm4-tm0]:629\nfinish 673 frame\n674----rcs.size():0[tm0:1507941134021756,tm1:1507941134022333,tm2:1507941134022333(0),tm3:1507941134022339(6),tm4:1507941134022340(7)][tm4-tm0]:584\nfinish 674 frame\n675----rcs.size():0[tm0:1507941134059774,tm1:1507941134060373,tm2:1507941134060373(0),tm3:1507941134060379(6),tm4:1507941134060379(6)][tm4-tm0]:605\nfinish 675 frame\n676----rcs.size():0[tm0:1507941134095910,tm1:1507941134096449,tm2:1507941134096449(0),tm3:1507941134096456(7),tm4:1507941134096456(7)][tm4-tm0]:546\nfinish 676 frame\n677----rcs.size():0[tm0:1507941134131549,tm1:1507941134132140,tm2:1507941134132140(0),tm3:1507941134132147(7),tm4:1507941134132147(7)][tm4-tm0]:598\nfinish 677 frame\n678----rcs.size():0[tm0:1507941134166920,tm1:1507941134167572,tm2:1507941134167572(0),tm3:1507941134167594(22),tm4:1507941134167595(23)][tm4-tm0]:675\nfinish 678 frame\n679----rcs.size():0[tm0:1507941134198688,tm1:1507941134199304,tm2:1507941134199304(0),tm3:1507941134199311(7),tm4:1507941134199311(7)][tm4-tm0]:623\nfinish 679 frame\n"
  },
  {
    "path": "logn15.txt",
    "content": "hahahah0\nhahahah1\nhahahah2\nprocess image cost time:2\n_create_network\nbatch_norm_fn\nbatch_norm_fn\n('feature dimensionality: ', 128)\nbatch_norm_fn\nhahahah\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:850\n(incpp)call encode cost time:tmd-tmc:936020\n1----rcs.size():0[tm0:1507941029485647,tm1:1507941029491064,tm2:1507941029491064(0),tm3:1507941029491073(9),tm4:1507941029491073(9)][tm4-tm0]:5426\nfinish 1 frame\n2----rcs.size():0[tm0:1507941029543009,tm1:1507941029544532,tm2:1507941029544532(0),tm3:1507941029544535(3),tm4:1507941029544535(3)][tm4-tm0]:1526\nfinish 2 frame\n3----rcs.size():0[tm0:1507941029584842,tm1:1507941029586154,tm2:1507941029586154(0),tm3:1507941029586157(3),tm4:1507941029586157(3)][tm4-tm0]:1315\nfinish 3 frame\n4----rcs.size():0[tm0:1507941029612643,tm1:1507941029613333,tm2:1507941029613333(0),tm3:1507941029613336(3),tm4:1507941029613336(3)][tm4-tm0]:693\nfinish 4 frame\n5----rcs.size():0[tm0:1507941029643478,tm1:1507941029644041,tm2:1507941029644041(0),tm3:1507941029644043(2),tm4:1507941029644043(2)][tm4-tm0]:565\nfinish 5 frame\n6----rcs.size():0[tm0:1507941029680456,tm1:1507941029681036,tm2:1507941029681036(0),tm3:1507941029681039(3),tm4:1507941029681039(3)][tm4-tm0]:583\nfinish 6 frame\n7----rcs.size():0[tm0:1507941029724278,tm1:1507941029724822,tm2:1507941029724823(1),tm3:1507941029724825(3),tm4:1507941029724825(3)][tm4-tm0]:547\nfinish 7 frame\n8----rcs.size():0[tm0:1507941029761336,tm1:1507941029762043,tm2:1507941029762043(0),tm3:1507941029762045(2),tm4:1507941029762045(2)][tm4-tm0]:709\nfinish 8 frame\n9----rcs.size():0[tm0:1507941029805503,tm1:1507941029806031,tm2:1507941029806031(0),tm3:1507941029806033(2),tm4:1507941029806034(3)][tm4-tm0]:531\nfinish 9 frame\n10----rcs.size():0[tm0:1507941029841013,tm1:1507941029841615,tm2:1507941029841615(0),tm3:1507941029841618(3),tm4:1507941029841618(3)][tm4-tm0]:605\nfinish 10 frame\n11----rcs.size():0[tm0:1507941029876088,tm1:1507941029876644,tm2:1507941029876644(0),tm3:1507941029876646(2),tm4:1507941029876646(2)][tm4-tm0]:558\nfinish 11 frame\n12----rcs.size():0[tm0:1507941029911218,tm1:1507941029912140,tm2:1507941029912140(0),tm3:1507941029912142(2),tm4:1507941029912143(3)][tm4-tm0]:925\nfinish 12 frame\n13----rcs.size():0[tm0:1507941029946533,tm1:1507941029947237,tm2:1507941029947237(0),tm3:1507941029947239(2),tm4:1507941029947239(2)][tm4-tm0]:706\nfinish 13 frame\n14----rcs.size():0[tm0:1507941029982380,tm1:1507941029983087,tm2:1507941029983087(0),tm3:1507941029983089(2),tm4:1507941029983090(3)][tm4-tm0]:710\nfinish 14 frame\n15----rcs.size():0[tm0:1507941030019302,tm1:1507941030019995,tm2:1507941030019995(0),tm3:1507941030019997(2),tm4:1507941030019997(2)][tm4-tm0]:695\nfinish 15 frame\n16----rcs.size():0[tm0:1507941030055563,tm1:1507941030056241,tm2:1507941030056241(0),tm3:1507941030056243(2),tm4:1507941030056243(2)][tm4-tm0]:680\nfinish 16 frame\n17----rcs.size():0[tm0:1507941030091494,tm1:1507941030092048,tm2:1507941030092048(0),tm3:1507941030092050(2),tm4:1507941030092050(2)][tm4-tm0]:556\nfinish 17 frame\n18----rcs.size():0[tm0:1507941030126967,tm1:1507941030127611,tm2:1507941030127611(0),tm3:1507941030127613(2),tm4:1507941030127613(2)][tm4-tm0]:646\nfinish 18 frame\n19----rcs.size():0[tm0:1507941030163429,tm1:1507941030164123,tm2:1507941030164123(0),tm3:1507941030164125(2),tm4:1507941030164125(2)][tm4-tm0]:696\nfinish 19 frame\n20----rcs.size():0[tm0:1507941030200473,tm1:1507941030201128,tm2:1507941030201128(0),tm3:1507941030201131(3),tm4:1507941030201131(3)][tm4-tm0]:658\nfinish 20 frame\n21----rcs.size():0[tm0:1507941030236173,tm1:1507941030236913,tm2:1507941030236913(0),tm3:1507941030236915(2),tm4:1507941030236915(2)][tm4-tm0]:742\nfinish 21 frame\n22----rcs.size():0[tm0:1507941030272944,tm1:1507941030273477,tm2:1507941030273477(0),tm3:1507941030273479(2),tm4:1507941030273479(2)][tm4-tm0]:535\nfinish 22 frame\n23----rcs.size():0[tm0:1507941030310328,tm1:1507941030311047,tm2:1507941030311047(0),tm3:1507941030311049(2),tm4:1507941030311049(2)][tm4-tm0]:721\nfinish 23 frame\n24----rcs.size():0[tm0:1507941030346221,tm1:1507941030346934,tm2:1507941030346934(0),tm3:1507941030346936(2),tm4:1507941030346936(2)][tm4-tm0]:715\nfinish 24 frame\n25----rcs.size():0[tm0:1507941030382834,tm1:1507941030383479,tm2:1507941030383479(0),tm3:1507941030383481(2),tm4:1507941030383481(2)][tm4-tm0]:647\nfinish 25 frame\n26----rcs.size():0[tm0:1507941030419860,tm1:1507941030420625,tm2:1507941030420625(0),tm3:1507941030420627(2),tm4:1507941030420627(2)][tm4-tm0]:767\nfinish 26 frame\n27----rcs.size():0[tm0:1507941030456312,tm1:1507941030456952,tm2:1507941030456952(0),tm3:1507941030456954(2),tm4:1507941030456954(2)][tm4-tm0]:642\nfinish 27 frame\n28----rcs.size():0[tm0:1507941030491615,tm1:1507941030492224,tm2:1507941030492224(0),tm3:1507941030492226(2),tm4:1507941030492226(2)][tm4-tm0]:611\nfinish 28 frame\n29----rcs.size():0[tm0:1507941030526464,tm1:1507941030527080,tm2:1507941030527080(0),tm3:1507941030527082(2),tm4:1507941030527083(3)][tm4-tm0]:619\nfinish 29 frame\n30----rcs.size():0[tm0:1507941030559863,tm1:1507941030560460,tm2:1507941030560460(0),tm3:1507941030560462(2),tm4:1507941030560462(2)][tm4-tm0]:599\nfinish 30 frame\n31----rcs.size():0[tm0:1507941030595488,tm1:1507941030596244,tm2:1507941030596244(0),tm3:1507941030596246(2),tm4:1507941030596246(2)][tm4-tm0]:758\nfinish 31 frame\n32----rcs.size():0[tm0:1507941030631604,tm1:1507941030632225,tm2:1507941030632225(0),tm3:1507941030632227(2),tm4:1507941030632227(2)][tm4-tm0]:623\nfinish 32 frame\n33----rcs.size():0[tm0:1507941030667062,tm1:1507941030667662,tm2:1507941030667662(0),tm3:1507941030667664(2),tm4:1507941030667664(2)][tm4-tm0]:602\nfinish 33 frame\n34----rcs.size():0[tm0:1507941030702604,tm1:1507941030703188,tm2:1507941030703188(0),tm3:1507941030703190(2),tm4:1507941030703191(3)][tm4-tm0]:587\nfinish 34 frame\n35----rcs.size():0[tm0:1507941030739781,tm1:1507941030740302,tm2:1507941030740302(0),tm3:1507941030740304(2),tm4:1507941030740304(2)][tm4-tm0]:523\nfinish 35 frame\n36----rcs.size():0[tm0:1507941030775424,tm1:1507941030775964,tm2:1507941030775964(0),tm3:1507941030775967(3),tm4:1507941030775967(3)][tm4-tm0]:543\nfinish 36 frame\n37----rcs.size():0[tm0:1507941030811268,tm1:1507941030812008,tm2:1507941030812008(0),tm3:1507941030812011(3),tm4:1507941030812011(3)][tm4-tm0]:743\nfinish 37 frame\n38----rcs.size():0[tm0:1507941030846844,tm1:1507941030847406,tm2:1507941030847406(0),tm3:1507941030847408(2),tm4:1507941030847408(2)][tm4-tm0]:564\nfinish 38 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23377\n39----rcs.size():1[tm0:1507941030882870,tm1:1507941030883432,tm2:1507941030906924(23492),tm3:1507941030906938(23506),tm4:1507941030906938(23506)][tm4-tm0]:24068\nfinish 39 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23312\n40----rcs.size():1[tm0:1507941030938647,tm1:1507941030939318,tm2:1507941030962799(23481),tm3:1507941030962832(23514),tm4:1507941030962832(23514)][tm4-tm0]:24185\nfinish 40 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23478\n41----rcs.size():1[tm0:1507941030994180,tm1:1507941030995189,tm2:1507941031018813(23624),tm3:1507941031018831(23642),tm4:1507941031018858(23669)][tm4-tm0]:24678\nfinish 41 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23327\n42----rcs.size():1[tm0:1507941031053375,tm1:1507941031054041,tm2:1507941031077480(23439),tm3:1507941031077505(23464),tm4:1507941031077522(23481)][tm4-tm0]:24147\nfinish 42 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23128\n43----rcs.size():1[tm0:1507941031113740,tm1:1507941031114285,tm2:1507941031137607(23322),tm3:1507941031137637(23352),tm4:1507941031137656(23371)][tm4-tm0]:23916\nfinish 43 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23263\n44----rcs.size():1[tm0:1507941031172598,tm1:1507941031173140,tm2:1507941031196501(23361),tm3:1507941031196523(23383),tm4:1507941031196529(23389)][tm4-tm0]:23931\nfinish 44 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23212\n45----rcs.size():1[tm0:1507941031230472,tm1:1507941031231054,tm2:1507941031254392(23338),tm3:1507941031254412(23358),tm4:1507941031254418(23364)][tm4-tm0]:23946\nfinish 45 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23228\n46----rcs.size():1[tm0:1507941031285516,tm1:1507941031286099,tm2:1507941031309434(23335),tm3:1507941031309470(23371),tm4:1507941031309477(23378)][tm4-tm0]:23961\nfinish 46 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23258\n47----rcs.size():1[tm0:1507941031340656,tm1:1507941031341218,tm2:1507941031364585(23367),tm3:1507941031364605(23387),tm4:1507941031364612(23394)][tm4-tm0]:23956\nfinish 47 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23221\n48----rcs.size():1[tm0:1507941031399807,tm1:1507941031400366,tm2:1507941031423707(23341),tm3:1507941031423746(23380),tm4:1507941031423753(23387)][tm4-tm0]:23946\nfinish 48 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23324\n49----rcs.size():1[tm0:1507941031459699,tm1:1507941031460242,tm2:1507941031483770(23528),tm3:1507941031483811(23569),tm4:1507941031483835(23593)][tm4-tm0]:24136\nfinish 49 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23186\n50----rcs.size():1[tm0:1507941031519942,tm1:1507941031520582,tm2:1507941031543877(23295),tm3:1507941031543918(23336),tm4:1507941031543941(23359)][tm4-tm0]:23999\nfinish 50 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23209\n51----rcs.size():1[tm0:1507941031579904,tm1:1507941031580543,tm2:1507941031603910(23367),tm3:1507941031603966(23423),tm4:1507941031603974(23431)][tm4-tm0]:24070\nfinish 51 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23465\n52----rcs.size():1[tm0:1507941031634346,tm1:1507941031634868,tm2:1507941031658483(23615),tm3:1507941031658504(23636),tm4:1507941031658511(23643)][tm4-tm0]:24165\nfinish 52 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23325\n53----rcs.size():1[tm0:1507941031688950,tm1:1507941031689511,tm2:1507941031712965(23454),tm3:1507941031712987(23476),tm4:1507941031712994(23483)][tm4-tm0]:24044\nfinish 53 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23316\n54----rcs.size():1[tm0:1507941031743882,tm1:1507941031744631,tm2:1507941031768056(23425),tm3:1507941031768078(23447),tm4:1507941031768101(23470)][tm4-tm0]:24219\nfinish 54 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23169\n55----rcs.size():1[tm0:1507941031800038,tm1:1507941031800613,tm2:1507941031823923(23310),tm3:1507941031823963(23350),tm4:1507941031823989(23376)][tm4-tm0]:23951\nfinish 55 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23348\n56----rcs.size():1[tm0:1507941031854721,tm1:1507941031855341,tm2:1507941031878818(23477),tm3:1507941031878858(23517),tm4:1507941031878865(23524)][tm4-tm0]:24144\nfinish 56 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23563\n57----rcs.size():1[tm0:1507941031908819,tm1:1507941031909416,tm2:1507941031933123(23707),tm3:1507941031933157(23741),tm4:1507941031933174(23758)][tm4-tm0]:24355\nfinish 57 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23519\n58----rcs.size():1[tm0:1507941031964050,tm1:1507941031964635,tm2:1507941031988281(23646),tm3:1507941031988304(23669),tm4:1507941031988320(23685)][tm4-tm0]:24270\nfinish 58 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23349\n59----rcs.size():1[tm0:1507941032022366,tm1:1507941032022948,tm2:1507941032046419(23471),tm3:1507941032046458(23510),tm4:1507941032046466(23518)][tm4-tm0]:24100\nfinish 59 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:23422\n60----rcs.size():1[tm0:1507941032077368,tm1:1507941032078123,tm2:1507941032101676(23553),tm3:1507941032101699(23576),tm4:1507941032101706(23583)][tm4-tm0]:24338\nfinish 60 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:22\n(incpp)call encode cost time:tmd-tmc:23350\n61----rcs.size():1[tm0:1507941032132410,tm1:1507941032132971,tm2:1507941032156442(23471),tm3:1507941032156483(23512),tm4:1507941032156490(23519)][tm4-tm0]:24080\nfinish 61 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24067\n62----rcs.size():1[tm0:1507941032188098,tm1:1507941032188648,tm2:1507941032212880(24232),tm3:1507941032212904(24256),tm4:1507941032212912(24264)][tm4-tm0]:24814\nfinish 62 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24886\n63----rcs.size():1[tm0:1507941032243975,tm1:1507941032244703,tm2:1507941032269707(25004),tm3:1507941032269748(25045),tm4:1507941032269756(25053)][tm4-tm0]:25781\nfinish 63 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24845\n64----rcs.size():1[tm0:1507941032300574,tm1:1507941032301154,tm2:1507941032326129(24975),tm3:1507941032326179(25025),tm4:1507941032326187(25033)][tm4-tm0]:25613\nfinish 64 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25061\n65----rcs.size():1[tm0:1507941032359106,tm1:1507941032359710,tm2:1507941032384911(25201),tm3:1507941032384935(25225),tm4:1507941032384942(25232)][tm4-tm0]:25836\nfinish 65 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24947\n66----rcs.size():1[tm0:1507941032416418,tm1:1507941032416945,tm2:1507941032442040(25095),tm3:1507941032442063(25118),tm4:1507941032442070(25125)][tm4-tm0]:25652\nfinish 66 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24957\n67----rcs.size():1[tm0:1507941032473384,tm1:1507941032473928,tm2:1507941032499038(25110),tm3:1507941032499062(25134),tm4:1507941032499070(25142)][tm4-tm0]:25686\nfinish 67 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24663\n68----rcs.size():1[tm0:1507941032530591,tm1:1507941032531109,tm2:1507941032555971(24862),tm3:1507941032556013(24904),tm4:1507941032556020(24911)][tm4-tm0]:25429\nfinish 68 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24801\n69----rcs.size():1[tm0:1507941032586681,tm1:1507941032587229,tm2:1507941032612225(24996),tm3:1507941032612266(25037),tm4:1507941032612274(25045)][tm4-tm0]:25593\nfinish 69 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24848\n70----rcs.size():1[tm0:1507941032647046,tm1:1507941032647587,tm2:1507941032672548(24961),tm3:1507941032672574(24987),tm4:1507941032672582(24995)][tm4-tm0]:25536\nfinish 70 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24743\n71----rcs.size():1[tm0:1507941032703815,tm1:1507941032704378,tm2:1507941032729241(24863),tm3:1507941032729284(24906),tm4:1507941032729292(24914)][tm4-tm0]:25477\nfinish 71 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24793\n72----rcs.size():1[tm0:1507941032760256,tm1:1507941032761015,tm2:1507941032785973(24958),tm3:1507941032786014(24999),tm4:1507941032786022(25007)][tm4-tm0]:25766\nfinish 72 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24953\n73----rcs.size():1[tm0:1507941032822016,tm1:1507941032822559,tm2:1507941032847721(25162),tm3:1507941032847745(25186),tm4:1507941032847784(25225)][tm4-tm0]:25768\nfinish 73 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24792\n74----rcs.size():2[tm0:1507941032881133,tm1:1507941032881701,tm2:1507941032906631(24930),tm3:1507941032906661(24960),tm4:1507941032906669(24968)][tm4-tm0]:25536\nfinish 74 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24645\n75----rcs.size():2[tm0:1507941032937602,tm1:1507941032938188,tm2:1507941032962947(24759),tm3:1507941032962997(24809),tm4:1507941032963005(24817)][tm4-tm0]:25403\nfinish 75 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24859\n76----rcs.size():2[tm0:1507941032993868,tm1:1507941032994666,tm2:1507941033019664(24998),tm3:1507941033019700(25034),tm4:1507941033019736(25070)][tm4-tm0]:25868\nfinish 76 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24697\n77----rcs.size():2[tm0:1507941033051386,tm1:1507941033051965,tm2:1507941033076805(24840),tm3:1507941033076858(24893),tm4:1507941033076870(24905)][tm4-tm0]:25484\nfinish 77 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24649\n78----rcs.size():2[tm0:1507941033113719,tm1:1507941033114266,tm2:1507941033139070(24804),tm3:1507941033139107(24841),tm4:1507941033139117(24851)][tm4-tm0]:25398\nfinish 78 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24894\n79----rcs.size():2[tm0:1507941033174487,tm1:1507941033175091,tm2:1507941033200112(25021),tm3:1507941033200194(25103),tm4:1507941033200207(25116)][tm4-tm0]:25720\nfinish 79 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24700\n80----rcs.size():2[tm0:1507941033231594,tm1:1507941033232158,tm2:1507941033256982(24824),tm3:1507941033257055(24897),tm4:1507941033257066(24908)][tm4-tm0]:25472\nfinish 80 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24658\n81----rcs.size():2[tm0:1507941033288382,tm1:1507941033288907,tm2:1507941033313732(24825),tm3:1507941033313787(24880),tm4:1507941033313799(24892)][tm4-tm0]:25417\nfinish 81 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24759\n82----rcs.size():2[tm0:1507941033344661,tm1:1507941033345315,tm2:1507941033370242(24927),tm3:1507941033370317(25002),tm4:1507941033370326(25011)][tm4-tm0]:25665\nfinish 82 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24749\n83----rcs.size():2[tm0:1507941033401047,tm1:1507941033401668,tm2:1507941033426530(24862),tm3:1507941033426587(24919),tm4:1507941033426598(24930)][tm4-tm0]:25551\nfinish 83 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25151\n84----rcs.size():2[tm0:1507941033457419,tm1:1507941033458002,tm2:1507941033483309(25307),tm3:1507941033483365(25363),tm4:1507941033483393(25391)][tm4-tm0]:25974\nfinish 84 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24805\n85----rcs.size():2[tm0:1507941033514587,tm1:1507941033515126,tm2:1507941033540086(24960),tm3:1507941033540169(25043),tm4:1507941033540180(25054)][tm4-tm0]:25593\nfinish 85 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24765\n86----rcs.size():2[tm0:1507941033571577,tm1:1507941033572121,tm2:1507941033597028(24907),tm3:1507941033597086(24965),tm4:1507941033597100(24979)][tm4-tm0]:25523\nfinish 86 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24756\n87----rcs.size():2[tm0:1507941033628665,tm1:1507941033629232,tm2:1507941033654167(24935),tm3:1507941033654208(24976),tm4:1507941033654219(24987)][tm4-tm0]:25554\nfinish 87 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24726\n88----rcs.size():2[tm0:1507941033685668,tm1:1507941033686230,tm2:1507941033711132(24902),tm3:1507941033711217(24987),tm4:1507941033711229(24999)][tm4-tm0]:25561\nfinish 88 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25096\n89----rcs.size():2[tm0:1507941033742176,tm1:1507941033742795,tm2:1507941033768036(25241),tm3:1507941033768096(25301),tm4:1507941033768108(25313)][tm4-tm0]:25932\nfinish 89 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24715\n90----rcs.size():2[tm0:1507941033799628,tm1:1507941033800152,tm2:1507941033825063(24911),tm3:1507941033825105(24953),tm4:1507941033825114(24962)][tm4-tm0]:25486\nfinish 90 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25090\n91----rcs.size():2[tm0:1507941033856355,tm1:1507941033856936,tm2:1507941033882208(25272),tm3:1507941033882251(25315),tm4:1507941033882264(25328)][tm4-tm0]:25909\nfinish 91 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24886\n92----rcs.size():2[tm0:1507941033913880,tm1:1507941033914442,tm2:1507941033939535(25093),tm3:1507941033939595(25153),tm4:1507941033939607(25165)][tm4-tm0]:25727\nfinish 92 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24863\n93----rcs.size():2[tm0:1507941033971461,tm1:1507941033972026,tm2:1507941033997051(25025),tm3:1507941033997096(25070),tm4:1507941033997107(25081)][tm4-tm0]:25646\nfinish 93 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24810\n94----rcs.size():2[tm0:1507941034028847,tm1:1507941034029436,tm2:1507941034054381(24945),tm3:1507941034054426(24990),tm4:1507941034054456(25020)][tm4-tm0]:25609\nfinish 94 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24899\n95----rcs.size():2[tm0:1507941034085974,tm1:1507941034086501,tm2:1507941034111581(25080),tm3:1507941034111626(25125),tm4:1507941034111638(25137)][tm4-tm0]:25664\nfinish 95 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25119\n96----rcs.size():2[tm0:1507941034142193,tm1:1507941034142738,tm2:1507941034168001(25263),tm3:1507941034168060(25322),tm4:1507941034168070(25332)][tm4-tm0]:25877\nfinish 96 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24834\n97----rcs.size():2[tm0:1507941034199859,tm1:1507941034200580,tm2:1507941034225556(24976),tm3:1507941034225601(25021),tm4:1507941034225614(25034)][tm4-tm0]:25755\nfinish 97 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24733\n98----rcs.size():2[tm0:1507941034256746,tm1:1507941034257361,tm2:1507941034282251(24890),tm3:1507941034282298(24937),tm4:1507941034282311(24950)][tm4-tm0]:25565\nfinish 98 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24917\n99----rcs.size():2[tm0:1507941034313735,tm1:1507941034314306,tm2:1507941034339382(25076),tm3:1507941034339428(25122),tm4:1507941034339440(25134)][tm4-tm0]:25705\nfinish 99 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24891\n100----rcs.size():3[tm0:1507941034371333,tm1:1507941034371882,tm2:1507941034396934(25052),tm3:1507941034396985(25103),tm4:1507941034396998(25116)][tm4-tm0]:25665\nfinish 100 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24794\n101----rcs.size():3[tm0:1507941034428067,tm1:1507941034428712,tm2:1507941034453676(24964),tm3:1507941034453732(25020),tm4:1507941034453744(25032)][tm4-tm0]:25677\nfinish 101 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24873\n102----rcs.size():3[tm0:1507941034485457,tm1:1507941034486024,tm2:1507941034511104(25080),tm3:1507941034511171(25147),tm4:1507941034511188(25164)][tm4-tm0]:25731\nfinish 102 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25198\n103----rcs.size():3[tm0:1507941034542402,tm1:1507941034542946,tm2:1507941034568293(25347),tm3:1507941034568364(25418),tm4:1507941034568378(25432)][tm4-tm0]:25976\nfinish 103 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24833\n104----rcs.size():3[tm0:1507941034599575,tm1:1507941034600161,tm2:1507941034625132(24971),tm3:1507941034625216(25055),tm4:1507941034625233(25072)][tm4-tm0]:25658\nfinish 104 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24908\n105----rcs.size():3[tm0:1507941034657429,tm1:1507941034658172,tm2:1507941034683243(25071),tm3:1507941034683319(25147),tm4:1507941034683336(25164)][tm4-tm0]:25907\nfinish 105 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24851\n106----rcs.size():3[tm0:1507941034715099,tm1:1507941034715663,tm2:1507941034740640(24977),tm3:1507941034740702(25039),tm4:1507941034740717(25054)][tm4-tm0]:25618\nfinish 106 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24878\n107----rcs.size():3[tm0:1507941034772152,tm1:1507941034772700,tm2:1507941034797706(25006),tm3:1507941034797766(25066),tm4:1507941034797784(25084)][tm4-tm0]:25632\nfinish 107 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24699\n108----rcs.size():3[tm0:1507941034828569,tm1:1507941034829114,tm2:1507941034853976(24862),tm3:1507941034854056(24942),tm4:1507941034854096(24982)][tm4-tm0]:25527\nfinish 108 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24611\n109----rcs.size():3[tm0:1507941034885114,tm1:1507941034885649,tm2:1507941034910388(24739),tm3:1507941034910446(24797),tm4:1507941034910459(24810)][tm4-tm0]:25345\nfinish 109 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25104\n110----rcs.size():3[tm0:1507941034941502,tm1:1507941034942190,tm2:1507941034967451(25261),tm3:1507941034967512(25322),tm4:1507941034967543(25353)][tm4-tm0]:26041\nfinish 110 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24788\n111----rcs.size():3[tm0:1507941034999266,tm1:1507941034999914,tm2:1507941035024901(24987),tm3:1507941035025003(25089),tm4:1507941035025043(25129)][tm4-tm0]:25777\nfinish 111 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24973\n112----rcs.size():3[tm0:1507941035055438,tm1:1507941035055948,tm2:1507941035081108(25160),tm3:1507941035081183(25235),tm4:1507941035081226(25278)][tm4-tm0]:25788\nfinish 112 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25016\n113----rcs.size():3[tm0:1507941035113041,tm1:1507941035113744,tm2:1507941035138910(25166),tm3:1507941035138988(25244),tm4:1507941035139001(25257)][tm4-tm0]:25960\nfinish 113 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24882\n114----rcs.size():3[tm0:1507941035170405,tm1:1507941035170951,tm2:1507941035196023(25072),tm3:1507941035196090(25139),tm4:1507941035196133(25182)][tm4-tm0]:25728\nfinish 114 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24932\n115----rcs.size():3[tm0:1507941035227779,tm1:1507941035228507,tm2:1507941035253634(25127),tm3:1507941035253714(25207),tm4:1507941035253731(25224)][tm4-tm0]:25952\nfinish 115 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24737\n116----rcs.size():2[tm0:1507941035284890,tm1:1507941035285574,tm2:1507941035310476(24902),tm3:1507941035310555(24981),tm4:1507941035310566(24992)][tm4-tm0]:25676\nfinish 116 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25075\n117\n117----rcs.size():2[tm0:1507941035341086,tm1:1507941035341673,tm2:1507941035366913(25240),tm3:1507941035366980(25307),tm4:1507941035366995(25322)][tm4-tm0]:25909\nfinish 117 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25173\n118----rcs.size():2[tm0:1507941035398707,tm1:1507941035399436,tm2:1507941035424811(25375),tm3:1507941035424877(25441),tm4:1507941035424891(25455)][tm4-tm0]:26184\nfinish 118 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24956\n119----rcs.size():2[tm0:1507941035455088,tm1:1507941035455673,tm2:1507941035480828(25155),tm3:1507941035480896(25223),tm4:1507941035480936(25263)][tm4-tm0]:25848\nfinish 119 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24895\n120----rcs.size():2[tm0:1507941035512436,tm1:1507941035512981,tm2:1507941035538077(25096),tm3:1507941035538148(25167),tm4:1507941035538159(25178)][tm4-tm0]:25723\nfinish 120 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25126\n121----rcs.size():2[tm0:1507941035569061,tm1:1507941035569647,tm2:1507941035594975(25328),tm3:1507941035595028(25381),tm4:1507941035595066(25419)][tm4-tm0]:26005\nfinish 121 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25182\n122----rcs.size():2[tm0:1507941035626304,tm1:1507941035627229,tm2:1507941035652682(25453),tm3:1507941035652742(25513),tm4:1507941035652780(25551)][tm4-tm0]:26476\nfinish 122 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25024\n123----rcs.size():2[tm0:1507941035688022,tm1:1507941035688600,tm2:1507941035713803(25203),tm3:1507941035713856(25256),tm4:1507941035713890(25290)][tm4-tm0]:25868\nfinish 123 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24838\n124----rcs.size():3[tm0:1507941035745218,tm1:1507941035745785,tm2:1507941035770777(24992),tm3:1507941035770867(25082),tm4:1507941035770881(25096)][tm4-tm0]:25663\nfinish 124 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24911\n125----rcs.size():3[tm0:1507941035802401,tm1:1507941035803050,tm2:1507941035828112(25062),tm3:1507941035828200(25150),tm4:1507941035828232(25182)][tm4-tm0]:25831\nfinish 125 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25117\n126----rcs.size():3[tm0:1507941035859084,tm1:1507941035859694,tm2:1507941035884983(25289),tm3:1507941035885072(25378),tm4:1507941035885085(25391)][tm4-tm0]:26001\nfinish 126 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24939\n127----rcs.size():3[tm0:1507941035915206,tm1:1507941035915751,tm2:1507941035940865(25114),tm3:1507941035940943(25192),tm4:1507941035940956(25205)][tm4-tm0]:25750\nfinish 127 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24996\n128----rcs.size():3[tm0:1507941035972537,tm1:1507941035973223,tm2:1507941035998444(25221),tm3:1507941035998511(25288),tm4:1507941035998531(25308)][tm4-tm0]:25994\nfinish 128 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24967\n129----rcs.size():3[tm0:1507941036029206,tm1:1507941036029751,tm2:1507941036054882(25131),tm3:1507941036054968(25217),tm4:1507941036054985(25234)][tm4-tm0]:25779\nfinish 129 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24851\n130----rcs.size():3[tm0:1507941036086424,tm1:1507941036086985,tm2:1507941036112001(25016),tm3:1507941036112091(25106),tm4:1507941036112109(25124)][tm4-tm0]:25685\nfinish 130 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24818\n131----rcs.size():3[tm0:1507941036144530,tm1:1507941036145269,tm2:1507941036170282(25013),tm3:1507941036170368(25099),tm4:1507941036170414(25145)][tm4-tm0]:25884\nfinish 131 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25111\n132----rcs.size():3[tm0:1507941036201062,tm1:1507941036201667,tm2:1507941036226937(25270),tm3:1507941036227006(25339),tm4:1507941036227023(25356)][tm4-tm0]:25961\nfinish 132 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25286\n133----rcs.size():3[tm0:1507941036257973,tm1:1507941036258578,tm2:1507941036284079(25501),tm3:1507941036284157(25579),tm4:1507941036284176(25598)][tm4-tm0]:26203\nfinish 133 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24870\n134----rcs.size():2[tm0:1507941036315277,tm1:1507941036315988,tm2:1507941036341068(25080),tm3:1507941036341152(25164),tm4:1507941036341163(25175)][tm4-tm0]:25886\nfinish 134 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24961\n135----rcs.size():2[tm0:1507941036372465,tm1:1507941036373030,tm2:1507941036398185(25155),tm3:1507941036398244(25214),tm4:1507941036398284(25254)][tm4-tm0]:25819\nfinish 135 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25110\n136----rcs.size():2[tm0:1507941036433300,tm1:1507941036434010,tm2:1507941036459360(25350),tm3:1507941036459422(25412),tm4:1507941036459461(25451)][tm4-tm0]:26161\nfinish 136 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25139\n137----rcs.size():2[tm0:1507941036490322,tm1:1507941036490905,tm2:1507941036516285(25380),tm3:1507941036516390(25485),tm4:1507941036516402(25497)][tm4-tm0]:26080\nfinish 137 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25208\n138----rcs.size():2[tm0:1507941036547425,tm1:1507941036548130,tm2:1507941036573571(25441),tm3:1507941036573651(25521),tm4:1507941036573666(25536)][tm4-tm0]:26241\nfinish 138 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24989\n139----rcs.size():2[tm0:1507941036603685,tm1:1507941036604254,tm2:1507941036629461(25207),tm3:1507941036629537(25283),tm4:1507941036629549(25295)][tm4-tm0]:25864\nfinish 139 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25200\n140----rcs.size():2[tm0:1507941036659477,tm1:1507941036660268,tm2:1507941036685751(25483),tm3:1507941036685813(25545),tm4:1507941036685828(25560)][tm4-tm0]:26351\nfinish 140 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25293\n141----rcs.size():2[tm0:1507941036717124,tm1:1507941036717687,tm2:1507941036743239(25552),tm3:1507941036743302(25615),tm4:1507941036743345(25658)][tm4-tm0]:26221\nfinish 141 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25151\n142----rcs.size():2[tm0:1507941036780038,tm1:1507941036780680,tm2:1507941036806083(25403),tm3:1507941036806166(25486),tm4:1507941036806208(25528)][tm4-tm0]:26170\nfinish 142 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25082\n143----rcs.size():2[tm0:1507941036837201,tm1:1507941036837766,tm2:1507941036863075(25309),tm3:1507941036863163(25397),tm4:1507941036863208(25442)][tm4-tm0]:26007\nfinish 143 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24988\n144----rcs.size():3[tm0:1507941036894315,tm1:1507941036894936,tm2:1507941036920161(25225),tm3:1507941036920303(25367),tm4:1507941036920345(25409)][tm4-tm0]:26030\nfinish 144 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24820\n145----rcs.size():3[tm0:1507941036951480,tm1:1507941036952083,tm2:1507941036977146(25063),tm3:1507941036977255(25172),tm4:1507941036977266(25183)][tm4-tm0]:25786\nfinish 145 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24980\n146----rcs.size():3[tm0:1507941037006893,tm1:1507941037007421,tm2:1507941037032624(25203),tm3:1507941037032719(25298),tm4:1507941037032732(25311)][tm4-tm0]:25839\nfinish 146 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24919\n147----rcs.size():4[tm0:1507941037062802,tm1:1507941037063352,tm2:1507941037088470(25118),tm3:1507941037088558(25206),tm4:1507941037088576(25224)][tm4-tm0]:25774\nfinish 147 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24906\n148----rcs.size():4[tm0:1507941037119761,tm1:1507941037120386,tm2:1507941037145524(25138),tm3:1507941037145603(25217),tm4:1507941037145622(25236)][tm4-tm0]:25861\nfinish 148 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25141\n149----rcs.size():4[tm0:1507941037177024,tm1:1507941037177653,tm2:1507941037203133(25480),tm3:1507941037203240(25587),tm4:1507941037203263(25610)][tm4-tm0]:26239\nfinish 149 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24900\n150----rcs.size():4[tm0:1507941037234238,tm1:1507941037234887,tm2:1507941037260001(25114),tm3:1507941037260116(25229),tm4:1507941037260146(25259)][tm4-tm0]:25908\nfinish 150 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25210\n151----rcs.size():4[tm0:1507941037291018,tm1:1507941037291586,tm2:1507941037317062(25476),tm3:1507941037317178(25592),tm4:1507941037317201(25615)][tm4-tm0]:26183\nfinish 151 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24895\n152----rcs.size():3[tm0:1507941037347494,tm1:1507941037348080,tm2:1507941037373162(25082),tm3:1507941037373280(25200),tm4:1507941037373316(25236)][tm4-tm0]:25822\nfinish 152 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24924\n153----rcs.size():3[tm0:1507941037403322,tm1:1507941037403886,tm2:1507941037429045(25159),tm3:1507941037429172(25286),tm4:1507941037429192(25306)][tm4-tm0]:25870\nfinish 153 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25516\n154----rcs.size():3[tm0:1507941037458463,tm1:1507941037458990,tm2:1507941037484735(25745),tm3:1507941037484815(25825),tm4:1507941037484835(25845)][tm4-tm0]:26372\nfinish 154 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25311\n155----rcs.size():4[tm0:1507941037514811,tm1:1507941037515399,tm2:1507941037540955(25556),tm3:1507941037541058(25659),tm4:1507941037541080(25681)][tm4-tm0]:26269\nfinish 155 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25168\n156----rcs.size():5[tm0:1507941037570864,tm1:1507941037571451,tm2:1507941037596878(25427),tm3:1507941037596988(25537),tm4:1507941037597010(25559)][tm4-tm0]:26146\nfinish 156 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25037\n157----rcs.size():5[tm0:1507941037627455,tm1:1507941037628096,tm2:1507941037653429(25333),tm3:1507941037653561(25465),tm4:1507941037653585(25489)][tm4-tm0]:26130\nfinish 157 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:24873\n158----rcs.size():5[tm0:1507941037684329,tm1:1507941037684957,tm2:1507941037710071(25114),tm3:1507941037710196(25239),tm4:1507941037710222(25265)][tm4-tm0]:25893\nfinish 158 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25240\n159----rcs.size():5[tm0:1507941037740007,tm1:1507941037740558,tm2:1507941037766059(25501),tm3:1507941037766176(25618),tm4:1507941037766196(25638)][tm4-tm0]:26189\nfinish 159 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25143\n160----rcs.size():5[tm0:1507941037796700,tm1:1507941037797282,tm2:1507941037822718(25436),tm3:1507941037822821(25539),tm4:1507941037822840(25558)][tm4-tm0]:26140\nfinish 160 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25358\n161----rcs.size():5[tm0:1507941037856620,tm1:1507941037857132,tm2:1507941037882707(25575),tm3:1507941037882817(25685),tm4:1507941037882843(25711)][tm4-tm0]:26223\nfinish 161 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25279\n162----rcs.size():5[tm0:1507941037913483,tm1:1507941037914122,tm2:1507941037939707(25585),tm3:1507941037939803(25681),tm4:1507941037939822(25700)][tm4-tm0]:26339\nfinish 162 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25107\n163----rcs.size():5[tm0:1507941037970693,tm1:1507941037971266,tm2:1507941037996632(25366),tm3:1507941037996739(25473),tm4:1507941037996782(25516)][tm4-tm0]:26089\nfinish 163 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25195\n164----rcs.size():5[tm0:1507941038026628,tm1:1507941038027274,tm2:1507941038052781(25507),tm3:1507941038052886(25612),tm4:1507941038052914(25640)][tm4-tm0]:26286\nfinish 164 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25246\n165----rcs.size():5[tm0:1507941038083112,tm1:1507941038083689,tm2:1507941038109195(25506),tm3:1507941038109321(25632),tm4:1507941038109347(25658)][tm4-tm0]:26235\nfinish 165 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25503\n166----rcs.size():5[tm0:1507941038139485,tm1:1507941038140073,tm2:1507941038165864(25791),tm3:1507941038165974(25901),tm4:1507941038166002(25929)][tm4-tm0]:26517\nfinish 166 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25155\n167----rcs.size():5[tm0:1507941038196347,tm1:1507941038196933,tm2:1507941038222401(25468),tm3:1507941038222517(25584),tm4:1507941038222545(25612)][tm4-tm0]:26198\nfinish 167 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25253\n168----rcs.size():5[tm0:1507941038253343,tm1:1507941038253939,tm2:1507941038279461(25522),tm3:1507941038279573(25634),tm4:1507941038279600(25661)][tm4-tm0]:26257\nfinish 168 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25469\n169----rcs.size():5[tm0:1507941038309890,tm1:1507941038310503,tm2:1507941038336358(25855),tm3:1507941038336469(25966),tm4:1507941038336498(25995)][tm4-tm0]:26608\nfinish 169 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25450\n170----rcs.size():5[tm0:1507941038366961,tm1:1507941038367533,tm2:1507941038393325(25792),tm3:1507941038393453(25920),tm4:1507941038393480(25947)][tm4-tm0]:26519\nfinish 170 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25420\n171----rcs.size():5[tm0:1507941038423488,tm1:1507941038424097,tm2:1507941038449796(25699),tm3:1507941038449909(25812),tm4:1507941038449940(25843)][tm4-tm0]:26452\nfinish 171 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25379\n172----rcs.size():5[tm0:1507941038480122,tm1:1507941038480697,tm2:1507941038506402(25705),tm3:1507941038506532(25835),tm4:1507941038506553(25856)][tm4-tm0]:26431\nfinish 172 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25349\n173----rcs.size():5[tm0:1507941038536661,tm1:1507941038537236,tm2:1507941038562882(25646),tm3:1507941038562997(25761),tm4:1507941038563028(25792)][tm4-tm0]:26367\nfinish 173 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25553\n174----rcs.size():5[tm0:1507941038592954,tm1:1507941038593673,tm2:1507941038619594(25921),tm3:1507941038619713(26040),tm4:1507941038619744(26071)][tm4-tm0]:26790\nfinish 174 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25306\n175----rcs.size():5[tm0:1507941038649859,tm1:1507941038650413,tm2:1507941038676000(25587),tm3:1507941038676123(25710),tm4:1507941038676167(25754)][tm4-tm0]:26308\nfinish 175 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25396\n176----rcs.size():5[tm0:1507941038706162,tm1:1507941038706753,tm2:1507941038732448(25695),tm3:1507941038732568(25815),tm4:1507941038732598(25845)][tm4-tm0]:26436\nfinish 176 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25115\n177----rcs.size():5[tm0:1507941038763259,tm1:1507941038763817,tm2:1507941038789232(25415),tm3:1507941038789368(25551),tm4:1507941038789398(25581)][tm4-tm0]:26139\nfinish 177 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25729\n178----rcs.size():5[tm0:1507941038819368,tm1:1507941038820008,tm2:1507941038846253(26245),tm3:1507941038846380(26372),tm4:1507941038846412(26404)][tm4-tm0]:27044\nfinish 178 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25500\n179----rcs.size():5[tm0:1507941038877048,tm1:1507941038877918,tm2:1507941038903778(25860),tm3:1507941038903902(25984),tm4:1507941038903933(26015)][tm4-tm0]:26885\nfinish 179 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25483\n180----rcs.size():5[tm0:1507941038934251,tm1:1507941038934818,tm2:1507941038960680(25862),tm3:1507941038960806(25988),tm4:1507941038960837(26019)][tm4-tm0]:26586\nfinish 180 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25775\n181----rcs.size():5[tm0:1507941038990513,tm1:1507941038991088,tm2:1507941039017260(26172),tm3:1507941039017386(26298),tm4:1507941039017416(26328)][tm4-tm0]:26903\nfinish 181 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25555\n182----rcs.size():5[tm0:1507941039051061,tm1:1507941039051596,tm2:1507941039077515(25919),tm3:1507941039077661(26065),tm4:1507941039077690(26094)][tm4-tm0]:26629\nfinish 182 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25480\n183----rcs.size():5[tm0:1507941039111926,tm1:1507941039112537,tm2:1507941039138381(25844),tm3:1507941039138505(25968),tm4:1507941039138526(25989)][tm4-tm0]:26600\nfinish 183 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25379\n184----rcs.size():6[tm0:1507941039169977,tm1:1507941039170611,tm2:1507941039196376(25765),tm3:1507941039196517(25906),tm4:1507941039196567(25956)][tm4-tm0]:26590\nfinish 184 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25641\n185----rcs.size():6[tm0:1507941039226628,tm1:1507941039227325,tm2:1507941039253351(26026),tm3:1507941039253499(26174),tm4:1507941039253530(26205)][tm4-tm0]:26902\nfinish 185 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25547\n186----rcs.size():6[tm0:1507941039283621,tm1:1507941039284194,tm2:1507941039310152(25958),tm3:1507941039310301(26107),tm4:1507941039310336(26142)][tm4-tm0]:26715\nfinish 186 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25974\n187----rcs.size():6[tm0:1507941039340326,tm1:1507941039340935,tm2:1507941039367327(26392),tm3:1507941039367478(26543),tm4:1507941039367517(26582)][tm4-tm0]:27191\nfinish 187 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25527\n188----rcs.size():6[tm0:1507941039401366,tm1:1507941039401920,tm2:1507941039427886(25966),tm3:1507941039428045(26125),tm4:1507941039428092(26172)][tm4-tm0]:26726\nfinish 188 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25485\n189----rcs.size():6[tm0:1507941039460387,tm1:1507941039461027,tm2:1507941039486914(25887),tm3:1507941039487070(26043),tm4:1507941039487109(26082)][tm4-tm0]:26722\nfinish 189 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25645\n190----rcs.size():6[tm0:1507941039517336,tm1:1507941039517893,tm2:1507941039543957(26064),tm3:1507941039544115(26222),tm4:1507941039544161(26268)][tm4-tm0]:26825\nfinish 190 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26160\n191----rcs.size():6[tm0:1507941039574407,tm1:1507941039575008,tm2:1507941039601574(26566),tm3:1507941039601751(26743),tm4:1507941039601835(26827)][tm4-tm0]:27428\nfinish 191 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25459\n192----rcs.size():6[tm0:1507941039632114,tm1:1507941039632667,tm2:1507941039658536(25869),tm3:1507941039658712(26045),tm4:1507941039658748(26081)][tm4-tm0]:26634\nfinish 192 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26186\n193----rcs.size():6[tm0:1507941039689753,tm1:1507941039690327,tm2:1507941039716964(26637),tm3:1507941039717122(26795),tm4:1507941039717167(26840)][tm4-tm0]:27414\nfinish 193 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25537\n194----rcs.size():6[tm0:1507941039751133,tm1:1507941039751662,tm2:1507941039777623(25961),tm3:1507941039777779(26117),tm4:1507941039777805(26143)][tm4-tm0]:26672\nfinish 194 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25870\n195----rcs.size():6[tm0:1507941039807543,tm1:1507941039808129,tm2:1507941039834416(26287),tm3:1507941039834569(26440),tm4:1507941039834594(26465)][tm4-tm0]:27051\nfinish 195 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25955\n196----rcs.size():6[tm0:1507941039864693,tm1:1507941039865293,tm2:1507941039891731(26438),tm3:1507941039891895(26602),tm4:1507941039891935(26642)][tm4-tm0]:27242\nfinish 196 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26024\n197----rcs.size():6[tm0:1507941039921981,tm1:1507941039922537,tm2:1507941039949007(26470),tm3:1507941039949192(26655),tm4:1507941039949231(26694)][tm4-tm0]:27250\nfinish 197 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25656\n198----rcs.size():6[tm0:1507941039979324,tm1:1507941039979880,tm2:1507941040006059(26179),tm3:1507941040006274(26394),tm4:1507941040006316(26436)][tm4-tm0]:26992\nfinish 198 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25817\n199----rcs.size():6[tm0:1507941040037623,tm1:1507941040038183,tm2:1507941040064454(26271),tm3:1507941040064620(26437),tm4:1507941040064662(26479)][tm4-tm0]:27039\nfinish 199 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25910\n200----rcs.size():6[tm0:1507941040094966,tm1:1507941040095523,tm2:1507941040121974(26451),tm3:1507941040122151(26628),tm4:1507941040122190(26667)][tm4-tm0]:27224\nfinish 200 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25682\n201----rcs.size():6[tm0:1507941040152001,tm1:1507941040152609,tm2:1507941040178785(26176),tm3:1507941040179024(26415),tm4:1507941040179069(26460)][tm4-tm0]:27068\nfinish 201 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25887\n202----rcs.size():6[tm0:1507941040210003,tm1:1507941040210800,tm2:1507941040237294(26494),tm3:1507941040237482(26682),tm4:1507941040237524(26724)][tm4-tm0]:27521\nfinish 202 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26505\n203----rcs.size():6[tm0:1507941040273192,tm1:1507941040274530,tm2:1507941040302234(27704),tm3:1507941040302409(27879),tm4:1507941040302448(27918)][tm4-tm0]:29256\nfinish 203 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26504\n204----rcs.size():6[tm0:1507941040332210,tm1:1507941040332921,tm2:1507941040359992(27071),tm3:1507941040360183(27262),tm4:1507941040360340(27419)][tm4-tm0]:28130\nfinish 204 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26234\n205----rcs.size():6[tm0:1507941040391569,tm1:1507941040393097,tm2:1507941040420769(27672),tm3:1507941040420980(27883),tm4:1507941040421119(28022)][tm4-tm0]:29550\nfinish 205 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26415\n206----rcs.size():6[tm0:1507941040452564,tm1:1507941040453987,tm2:1507941040481846(27859),tm3:1507941040482054(28067),tm4:1507941040482205(28218)][tm4-tm0]:29641\nfinish 206 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26557\n207----rcs.size():6[tm0:1507941040514191,tm1:1507941040515551,tm2:1507941040543543(27992),tm3:1507941040543748(28197),tm4:1507941040543777(28226)][tm4-tm0]:29586\nfinish 207 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26302\n208----rcs.size():6[tm0:1507941040579591,tm1:1507941040580906,tm2:1507941040608651(27745),tm3:1507941040608834(27928),tm4:1507941040608863(27957)][tm4-tm0]:29272\nfinish 208 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26504\n209----rcs.size():6[tm0:1507941040638957,tm1:1507941040640268,tm2:1507941040668176(27908),tm3:1507941040668399(28131),tm4:1507941040668444(28176)][tm4-tm0]:29487\nfinish 209 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26192\n210----rcs.size():7[tm0:1507941040703083,tm1:1507941040704396,tm2:1507941040732075(27679),tm3:1507941040732308(27912),tm4:1507941040732349(27953)][tm4-tm0]:29266\nfinish 210 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26541\n211----rcs.size():7[tm0:1507941040764507,tm1:1507941040765889,tm2:1507941040794081(28192),tm3:1507941040794292(28403),tm4:1507941040794335(28446)][tm4-tm0]:29828\nfinish 211 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26870\n212----rcs.size():7[tm0:1507941040825714,tm1:1507941040827395,tm2:1507941040855602(28207),tm3:1507941040855809(28414),tm4:1507941040855855(28460)][tm4-tm0]:30141\nfinish 212 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26808\n213----rcs.size():7[tm0:1507941040887371,tm1:1507941040888728,tm2:1507941040916648(27920),tm3:1507941040916900(28172),tm4:1507941040916946(28218)][tm4-tm0]:29575\nfinish 213 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26516\n214----rcs.size():7[tm0:1507941040948479,tm1:1507941040949800,tm2:1507941040977500(27700),tm3:1507941040977756(27956),tm4:1507941040977801(28001)][tm4-tm0]:29322\nfinish 214 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27130\n215----rcs.size():7[tm0:1507941041012315,tm1:1507941041013676,tm2:1507941041041983(28307),tm3:1507941041042228(28552),tm4:1507941041042272(28596)][tm4-tm0]:29957\nfinish 215 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27095\n216----rcs.size():7[tm0:1507941041077709,tm1:1507941041079063,tm2:1507941041107498(28435),tm3:1507941041107738(28675),tm4:1507941041107782(28719)][tm4-tm0]:30073\nfinish 216 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26954\n217----rcs.size():7[tm0:1507941041142227,tm1:1507941041143901,tm2:1507941041172370(28469),tm3:1507941041172636(28735),tm4:1507941041172683(28782)][tm4-tm0]:30456\nfinish 217 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27124\n218----rcs.size():7[tm0:1507941041204103,tm1:1507941041205521,tm2:1507941041234119(28598),tm3:1507941041234381(28860),tm4:1507941041234428(28907)][tm4-tm0]:30325\nfinish 218 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27120\n219----rcs.size():6[tm0:1507941041265932,tm1:1507941041267326,tm2:1507941041296324(28998),tm3:1507941041296566(29240),tm4:1507941041296616(29290)][tm4-tm0]:30684\nfinish 219 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27508\n220----rcs.size():6[tm0:1507941041327055,tm1:1507941041328533,tm2:1507941041357979(29446),tm3:1507941041358208(29675),tm4:1507941041358254(29721)][tm4-tm0]:31199\nfinish 220 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27346\n221----rcs.size():6[tm0:1507941041388733,tm1:1507941041390046,tm2:1507941041418902(28856),tm3:1507941041419111(29065),tm4:1507941041419163(29117)][tm4-tm0]:30430\nfinish 221 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27143\n222----rcs.size():6[tm0:1507941041450837,tm1:1507941041452320,tm2:1507941041480811(28491),tm3:1507941041481234(28914),tm4:1507941041481303(28983)][tm4-tm0]:30466\nfinish 222 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27058\n223----rcs.size():6[tm0:1507941041511934,tm1:1507941041513211,tm2:1507941041542120(28909),tm3:1507941041542347(29136),tm4:1507941041542390(29179)][tm4-tm0]:30456\nfinish 223 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27014\n224----rcs.size():6[tm0:1507941041572462,tm1:1507941041573838,tm2:1507941041602488(28650),tm3:1507941041602707(28869),tm4:1507941041602750(28912)][tm4-tm0]:30288\nfinish 224 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27194\n225----rcs.size():6[tm0:1507941041635750,tm1:1507941041637056,tm2:1507941041666264(29208),tm3:1507941041666475(29419),tm4:1507941041666518(29462)][tm4-tm0]:30768\nfinish 225 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27134\n226----rcs.size():7[tm0:1507941041698203,tm1:1507941041699610,tm2:1507941041728611(29001),tm3:1507941041728850(29240),tm4:1507941041728884(29274)][tm4-tm0]:30681\nfinish 226 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27185\n227----rcs.size():7[tm0:1507941041761424,tm1:1507941041762716,tm2:1507941041791775(29059),tm3:1507941041792017(29301),tm4:1507941041792052(29336)][tm4-tm0]:30628\nfinish 227 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27456\n228----rcs.size():7[tm0:1507941041822183,tm1:1507941041823535,tm2:1507941041853061(29526),tm3:1507941041853346(29811),tm4:1507941041853395(29860)][tm4-tm0]:31212\nfinish 228 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27019\n229----rcs.size():7[tm0:1507941041884592,tm1:1507941041885896,tm2:1507941041914691(28795),tm3:1507941041914953(29057),tm4:1507941041915002(29106)][tm4-tm0]:30410\nfinish 229 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27139\n230----rcs.size():8[tm0:1507941041945824,tm1:1507941041947233,tm2:1507941041975697(28464),tm3:1507941041975933(28700),tm4:1507941041975984(28751)][tm4-tm0]:30160\nfinish 230 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27477\n231----rcs.size():8[tm0:1507941042007791,tm1:1507941042009302,tm2:1507941042038905(29603),tm3:1507941042039180(29878),tm4:1507941042039227(29925)][tm4-tm0]:31436\nfinish 231 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27236\n232----rcs.size():8[tm0:1507941042069794,tm1:1507941042071253,tm2:1507941042100306(29053),tm3:1507941042100602(29349),tm4:1507941042100658(29405)][tm4-tm0]:30864\nfinish 232 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27098\n233----rcs.size():8[tm0:1507941042131302,tm1:1507941042132984,tm2:1507941042162116(29132),tm3:1507941042162410(29426),tm4:1507941042162465(29481)][tm4-tm0]:31163\nfinish 233 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27765\n234----rcs.size():8[tm0:1507941042192067,tm1:1507941042193688,tm2:1507941042223338(29650),tm3:1507941042223586(29898),tm4:1507941042223642(29954)][tm4-tm0]:31575\nfinish 234 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27675\n235----rcs.size():8[tm0:1507941042253878,tm1:1507941042255302,tm2:1507941042285025(29723),tm3:1507941042285296(29994),tm4:1507941042285351(30049)]****[tm4-tm0]:31473\nfinish 235 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27345\n236----rcs.size():8[tm0:1507941042316260,tm1:1507941042317762,tm2:1507941042347339(29577),tm3:1507941042347604(29842),tm4:1507941042347814(30052)]****[tm4-tm0]:31554\nfinish 236 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26992\n237----rcs.size():8[tm0:1507941042378867,tm1:1507941042380282,tm2:1507941042409352(29070),tm3:1507941042409608(29326),tm4:1507941042409645(29363)][tm4-tm0]:30778\nfinish 237 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27422\n238----rcs.size():8[tm0:1507941042440436,tm1:1507941042441892,tm2:1507941042471928(30036),tm3:1507941042472209(30317),tm4:1507941042472417(30525)]****[tm4-tm0]:31981\nfinish 238 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25774\n239----rcs.size():7[tm0:1507941042502195,tm1:1507941042503494,tm2:1507941042529590(26096),tm3:1507941042529871(26377),tm4:1507941042529903(26409)][tm4-tm0]:27708\nfinish 239 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25681\n240----rcs.size():7[tm0:1507941042559524,tm1:1507941042560092,tm2:1507941042586185(26093),tm3:1507941042586383(26291),tm4:1507941042586415(26323)][tm4-tm0]:26891\nfinish 240 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25603\n241----rcs.size():7[tm0:1507941042615863,tm1:1507941042616447,tm2:1507941042642419(25972),tm3:1507941042642632(26185),tm4:1507941042642663(26216)][tm4-tm0]:26800\nfinish 241 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26190\n242----rcs.size():7[tm0:1507941042672556,tm1:1507941042673123,tm2:1507941042699787(26664),tm3:1507941042699999(26876),tm4:1507941042700032(26909)][tm4-tm0]:27476\nfinish 242 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25382\n243----rcs.size():7[tm0:1507941042730075,tm1:1507941042730684,tm2:1507941042756443(25759),tm3:1507941042756677(25993),tm4:1507941042756709(26025)][tm4-tm0]:26634\nfinish 243 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25764\n244----rcs.size():7[tm0:1507941042787658,tm1:1507941042788414,tm2:1507941042814586(26172),tm3:1507941042814812(26398),tm4:1507941042814847(26433)][tm4-tm0]:27189\nfinish 244 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25396\n245----rcs.size():7[tm0:1507941042845490,tm1:1507941042846228,tm2:1507941042871981(25753),tm3:1507941042872231(26003),tm4:1507941042872283(26055)][tm4-tm0]:26793\nfinish 245 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25533\n246----rcs.size():7[tm0:1507941042902416,tm1:1507941042903116,tm2:1507941042929089(25973),tm3:1507941042929338(26222),tm4:1507941042929487(26371)][tm4-tm0]:27071\nfinish 246 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25527\n247----rcs.size():7[tm0:1507941042959749,tm1:1507941042960512,tm2:1507941042986427(25915),tm3:1507941042986672(26160),tm4:1507941042986814(26302)][tm4-tm0]:27065\nfinish 247 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25831\n248----rcs.size():7[tm0:1507941043017551,tm1:1507941043018297,tm2:1507941043044611(26314),tm3:1507941043044850(26553),tm4:1507941043044885(26588)][tm4-tm0]:27334\nfinish 248 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26795\n249----rcs.size():7[tm0:1507941043075537,tm1:1507941043076287,tm2:1507941043103890(27603),tm3:1507941043104114(27827),tm4:1507941043104168(27881)][tm4-tm0]:28631\nfinish 249 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26320\n250----rcs.size():7[tm0:1507941043135781,tm1:1507941043137249,tm2:1507941043163984(26735),tm3:1507941043164232(26983),tm4:1507941043164265(27016)][tm4-tm0]:28484\nfinish 250 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25531\n251----rcs.size():7[tm0:1507941043193038,tm1:1507941043193699,tm2:1507941043219612(25913),tm3:1507941043219839(26140),tm4:1507941043219872(26173)][tm4-tm0]:26834\nfinish 251 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26047\n252----rcs.size():7[tm0:1507941043249847,tm1:1507941043250471,tm2:1507941043276936(26465),tm3:1507941043277219(26748),tm4:1507941043277252(26781)][tm4-tm0]:27405\nfinish 252 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25568\n253----rcs.size():7[tm0:1507941043311187,tm1:1507941043311785,tm2:1507941043337749(25964),tm3:1507941043338000(26215),tm4:1507941043338031(26246)][tm4-tm0]:26844\nfinish 253 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25657\n254----rcs.size():7[tm0:1507941043371695,tm1:1507941043372276,tm2:1507941043398330(26054),tm3:1507941043398562(26286),tm4:1507941043398596(26320)][tm4-tm0]:26901\nfinish 254 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25713\n255----rcs.size():7[tm0:1507941043428279,tm1:1507941043428858,tm2:1507941043454997(26139),tm3:1507941043455240(26382),tm4:1507941043455273(26415)][tm4-tm0]:26994\nfinish 255 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25577\n256----rcs.size():7[tm0:1507941043484323,tm1:1507941043484869,tm2:1507941043510876(26007),tm3:1507941043511132(26263),tm4:1507941043511174(26305)][tm4-tm0]:26851\nfinish 256 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26133\n257----rcs.size():7[tm0:1507941043540725,tm1:1507941043541290,tm2:1507941043567890(26600),tm3:1507941043568129(26839),tm4:1507941043568172(26882)][tm4-tm0]:27447\nfinish 257 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25864\n258----rcs.size():7[tm0:1507941043601580,tm1:1507941043602164,tm2:1507941043628575(26411),tm3:1507941043628814(26650),tm4:1507941043628860(26696)][tm4-tm0]:27280\nfinish 258 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25643\n259----rcs.size():7[tm0:1507941043659153,tm1:1507941043659914,tm2:1507941043686135(26221),tm3:1507941043686403(26489),tm4:1507941043686452(26538)][tm4-tm0]:27299\nfinish 259 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26219\n260----rcs.size():7[tm0:1507941043717180,tm1:1507941043717894,tm2:1507941043744681(26787),tm3:1507941043744948(27054),tm4:1507941043745110(27216)][tm4-tm0]:27930\nfinish 260 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26010\n261----rcs.size():7[tm0:1507941043777702,tm1:1507941043779141,tm2:1507941043806437(27296),tm3:1507941043806682(27541),tm4:1507941043806728(27587)][tm4-tm0]:29026\nfinish 261 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25825\n262----rcs.size():7[tm0:1507941043837195,tm1:1507941043837927,tm2:1507941043864215(26288),tm3:1507941043864464(26537),tm4:1507941043864498(26571)][tm4-tm0]:27303\nfinish 262 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26541\n263----rcs.size():7[tm0:1507941043894919,tm1:1507941043895530,tm2:1507941043922659(27129),tm3:1507941043922933(27403),tm4:1507941043922981(27451)][tm4-tm0]:28062\nfinish 263 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26934\n264----rcs.size():7[tm0:1507941043954697,tm1:1507941043956179,tm2:1507941043984489(28310),tm3:1507941043984754(28575),tm4:1507941043984801(28622)][tm4-tm0]:30104\nfinish 264 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26412\n265----rcs.size():7[tm0:1507941044016411,tm1:1507941044017914,tm2:1507941044045770(27856),tm3:1507941044046022(28108),tm4:1507941044046072(28158)][tm4-tm0]:29661\nfinish 265 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26824\n266----rcs.size():7[tm0:1507941044078121,tm1:1507941044079441,tm2:1507941044108253(28812),tm3:1507941044108549(29108),tm4:1507941044108604(29163)][tm4-tm0]:30483\nfinish 266 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26538\n267----rcs.size():7[tm0:1507941044142242,tm1:1507941044143803,tm2:1507941044171998(28195),tm3:1507941044172282(28479),tm4:1507941044172327(28524)][tm4-tm0]:30085\nfinish 267 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26733\n268----rcs.size():7[tm0:1507941044203385,tm1:1507941044204786,tm2:1507941044232763(27977),tm3:1507941044233052(28266),tm4:1507941044233099(28313)][tm4-tm0]:29714\nfinish 268 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26626\n269----rcs.size():7[tm0:1507941044264768,tm1:1507941044266184,tm2:1507941044294745(28561),tm3:1507941044295043(28859),tm4:1507941044295090(28906)][tm4-tm0]:30322\nfinish 269 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25698\n270----rcs.size():6[tm0:1507941044326796,tm1:1507941044328255,tm2:1507941044354248(25993),tm3:1507941044354513(26258),tm4:1507941044354551(26296)][tm4-tm0]:27755\nfinish 270 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25559\n271----rcs.size():6[tm0:1507941044385272,tm1:1507941044385979,tm2:1507941044411864(25885),tm3:1507941044412061(26082),tm4:1507941044412100(26121)][tm4-tm0]:26828\nfinish 271 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:24949\n272----rcs.size():6[tm0:1507941044441738,tm1:1507941044442487,tm2:1507941044467750(25263),tm3:1507941044467953(25466),tm4:1507941044467993(25506)][tm4-tm0]:26255\nfinish 272 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25316\n273----rcs.size():6[tm0:1507941044499753,tm1:1507941044500382,tm2:1507941044525988(25606),tm3:1507941044526212(25830),tm4:1507941044526251(25869)][tm4-tm0]:26498\nfinish 273 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25564\n274----rcs.size():6[tm0:1507941044556399,tm1:1507941044557080,tm2:1507941044583011(25931),tm3:1507941044583211(26131),tm4:1507941044583256(26176)][tm4-tm0]:26857\nfinish 274 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25272\n275----rcs.size():6[tm0:1507941044613431,tm1:1507941044614009,tm2:1507941044639610(25601),tm3:1507941044639819(25810),tm4:1507941044639861(25852)][tm4-tm0]:26430\nfinish 275 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25445\n276----rcs.size():6[tm0:1507941044669969,tm1:1507941044670659,tm2:1507941044696432(25773),tm3:1507941044696638(25979),tm4:1507941044696678(26019)][tm4-tm0]:26709\nfinish 276 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25669\n277----rcs.size():6[tm0:1507941044726457,tm1:1507941044726986,tm2:1507941044753100(26114),tm3:1507941044753349(26363),tm4:1507941044753381(26395)][tm4-tm0]:26924\nfinish 277 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25564\n278----rcs.size():6[tm0:1507941044785373,tm1:1507941044786025,tm2:1507941044812042(26017),tm3:1507941044812303(26278),tm4:1507941044812440(26415)][tm4-tm0]:27067\nfinish 278 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25168\n279----rcs.size():6[tm0:1507941044841743,tm1:1507941044842499,tm2:1507941044867997(25498),tm3:1507941044868233(25734),tm4:1507941044868272(25773)][tm4-tm0]:26529\nfinish 279 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25337\n280----rcs.size():6[tm0:1507941044901738,tm1:1507941044902302,tm2:1507941044928027(25725),tm3:1507941044928267(25965),tm4:1507941044928306(26004)][tm4-tm0]:26568\nfinish 280 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26026\n281----rcs.size():6[tm0:1507941044958018,tm1:1507941044959017,tm2:1507941044985546(26529),tm3:1507941044985796(26779),tm4:1507941044985857(26840)][tm4-tm0]:27839\nfinish 281 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25525\n282----rcs.size():6[tm0:1507941045016111,tm1:1507941045016885,tm2:1507941045042840(25955),tm3:1507941045043086(26201),tm4:1507941045043127(26242)][tm4-tm0]:27016\nfinish 282 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25674\n283----rcs.size():7[tm0:1507941045073019,tm1:1507941045073647,tm2:1507941045099691(26044),tm3:1507941045099992(26345),tm4:1507941045100035(26388)][tm4-tm0]:27016\nfinish 283 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25056\n284----rcs.size():7[tm0:1507941045129851,tm1:1507941045130637,tm2:1507941045156027(25390),tm3:1507941045156327(25690),tm4:1507941045156368(25731)][tm4-tm0]:26517\nfinish 284 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25501\n285----rcs.size():7[tm0:1507941045185744,tm1:1507941045186378,tm2:1507941045212340(25962),tm3:1507941045212649(26271),tm4:1507941045212696(26318)][tm4-tm0]:26952\nfinish 285 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25671\n286----rcs.size():7[tm0:1507941045242726,tm1:1507941045243439,tm2:1507941045269599(26160),tm3:1507941045269914(26475),tm4:1507941045270097(26658)][tm4-tm0]:27371\nfinish 286 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25534\n287----rcs.size():7[tm0:1507941045299654,tm1:1507941045300429,tm2:1507941045326353(25924),tm3:1507941045326611(26182),tm4:1507941045326660(26231)][tm4-tm0]:27006\nfinish 287 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25791\n288----rcs.size():7[tm0:1507941045356250,tm1:1507941045356981,tm2:1507941045383165(26184),tm3:1507941045383442(26461),tm4:1507941045383488(26507)][tm4-tm0]:27238\nfinish 288 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25423\n289----rcs.size():7[tm0:1507941045413894,tm1:1507941045414567,tm2:1507941045440440(25873),tm3:1507941045440703(26136),tm4:1507941045440747(26180)][tm4-tm0]:26853\nfinish 289 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25494\n290----rcs.size():7[tm0:1507941045470764,tm1:1507941045471471,tm2:1507941045497387(25916),tm3:1507941045497652(26181),tm4:1507941045497699(26228)][tm4-tm0]:26935\nfinish 290 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25479\n291----rcs.size():7[tm0:1507941045529393,tm1:1507941045530100,tm2:1507941045556109(26009),tm3:1507941045556401(26301),tm4:1507941045556449(26349)][tm4-tm0]:27056\nfinish 291 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25576\n292----rcs.size():7[tm0:1507941045586233,tm1:1507941045586945,tm2:1507941045612948(26003),tm3:1507941045613226(26281),tm4:1507941045613271(26326)][tm4-tm0]:27038\nfinish 292 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25512\n293----rcs.size():6[tm0:1507941045642920,tm1:1507941045643669,tm2:1507941045669632(25963),tm3:1507941045669907(26238),tm4:1507941045669967(26298)][tm4-tm0]:27047\nfinish 293 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25491\n294----rcs.size():6[tm0:1507941045699835,tm1:1507941045700585,tm2:1507941045726516(25931),tm3:1507941045726810(26225),tm4:1507941045726869(26284)][tm4-tm0]:27034\nfinish 294 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26029\n295----rcs.size():6[tm0:1507941045756338,tm1:1507941045757081,tm2:1507941045783556(26475),tm3:1507941045783790(26709),tm4:1507941045783833(26752)][tm4-tm0]:27495\nfinish 295 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25728\n296----rcs.size():6[tm0:1507941045813842,tm1:1507941045814587,tm2:1507941045840800(26213),tm3:1507941045841098(26511),tm4:1507941045841150(26563)][tm4-tm0]:27308\nfinish 296 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26062\n297----rcs.size():6[tm0:1507941045871206,tm1:1507941045871796,tm2:1507941045898334(26538),tm3:1507941045898588(26792),tm4:1507941045898633(26837)][tm4-tm0]:27427\nfinish 297 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26006\n298----rcs.size():6[tm0:1507941045928725,tm1:1507941045929405,tm2:1507941045955991(26586),tm3:1507941045956272(26867),tm4:1507941045956319(26914)][tm4-tm0]:27594\nfinish 298 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25567\n299----rcs.size():6[tm0:1507941045986097,tm1:1507941045986834,tm2:1507941046012843(26009),tm3:1507941046013097(26263),tm4:1507941046013158(26324)][tm4-tm0]:27061\nfinish 299 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25651\n300----rcs.size():6[tm0:1507941046043571,tm1:1507941046044234,tm2:1507941046070419(26185),tm3:1507941046070692(26458),tm4:1507941046070761(26527)][tm4-tm0]:27190\nfinish 300 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25733\n301----rcs.size():6[tm0:1507941046097417,tm1:1507941046098000,tm2:1507941046124233(26233),tm3:1507941046124493(26493),tm4:1507941046124540(26540)][tm4-tm0]:27123\nfinish 301 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25909\n302----rcs.size():6[tm0:1507941046153352,tm1:1507941046154082,tm2:1507941046180466(26384),tm3:1507941046180722(26640),tm4:1507941046180768(26686)][tm4-tm0]:27416\nfinish 302 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25946\n303----rcs.size():6[tm0:1507941046210434,tm1:1507941046211135,tm2:1507941046237655(26520),tm3:1507941046237934(26799),tm4:1507941046237982(26847)][tm4-tm0]:27548\nfinish 303 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25810\n304----rcs.size():6[tm0:1507941046269332,tm1:1507941046269967,tm2:1507941046296404(26437),tm3:1507941046296666(26699),tm4:1507941046296715(26748)][tm4-tm0]:27383\nfinish 304 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25929\n305----rcs.size():6[tm0:1507941046326367,tm1:1507941046327064,tm2:1507941046353573(26509),tm3:1507941046353838(26774),tm4:1507941046353892(26828)][tm4-tm0]:27525\nfinish 305 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26107\n306----rcs.size():6[tm0:1507941046383697,tm1:1507941046384385,tm2:1507941046411085(26700),tm3:1507941046411357(26972),tm4:1507941046411543(27158)][tm4-tm0]:27846\nfinish 306 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26228\n307----rcs.size():6[tm0:1507941046441134,tm1:1507941046442068,tm2:1507941046469077(27009),tm3:1507941046469350(27282),tm4:1507941046469533(27465)][tm4-tm0]:28399\nfinish 307 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26014\n308----rcs.size():6[tm0:1507941046499374,tm1:1507941046500145,tm2:1507941046526743(26598),tm3:1507941046527006(26861),tm4:1507941046527198(27053)][tm4-tm0]:27824\nfinish 308 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25954\n309----rcs.size():7[tm0:1507941046556831,tm1:1507941046557555,tm2:1507941046584179(26624),tm3:1507941046584462(26907),tm4:1507941046584499(26944)][tm4-tm0]:27668\nfinish 309 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25865\n310----rcs.size():7[tm0:1507941046613474,tm1:1507941046614040,tm2:1507941046640470(26430),tm3:1507941046640760(26720),tm4:1507941046640963(26923)][tm4-tm0]:27489\nfinish 310 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25947\n311----rcs.size():7[tm0:1507941046671425,tm1:1507941046672047,tm2:1507941046698510(26463),tm3:1507941046698819(26772),tm4:1507941046698860(26813)][tm4-tm0]:27435\nfinish 311 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26223\n312----rcs.size():7[tm0:1507941046730661,tm1:1507941046731256,tm2:1507941046758028(26772),tm3:1507941046758369(27113),tm4:1507941046758567(27311)][tm4-tm0]:27906\nfinish 312 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26233\n313----rcs.size():8[tm0:1507941046791127,tm1:1507941046792642,tm2:1507941046820109(27467),tm3:1507941046820420(27778),tm4:1507941046820476(27834)][tm4-tm0]:29349\nfinish 313 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26153\n314----rcs.size():8[tm0:1507941046850172,tm1:1507941046850895,tm2:1507941046877658(26763),tm3:1507941046877941(27046),tm4:1507941046877998(27103)][tm4-tm0]:27826\nfinish 314 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26364\n315----rcs.size():8[tm0:1507941046908943,tm1:1507941046910417,tm2:1507941046938132(27715),tm3:1507941046938426(28009),tm4:1507941046938468(28051)][tm4-tm0]:29525\nfinish 315 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26473\n316----rcs.size():8[tm0:1507941046970270,tm1:1507941046970884,tm2:1507941046998005(27121),tm3:1507941046998300(27416),tm4:1507941046998361(27477)][tm4-tm0]:28091\nfinish 316 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26593\n317----rcs.size():8[tm0:1507941047031653,tm1:1507941047033050,tm2:1507941047061177(28127),tm3:1507941047061498(28448),tm4:1507941047061746(28696)][tm4-tm0]:30093\nfinish 317 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26152\n318----rcs.size():8[tm0:1507941047092343,tm1:1507941047093696,tm2:1507941047121243(27547),tm3:1507941047121541(27845),tm4:1507941047121583(27887)][tm4-tm0]:29240\nfinish 318 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26705\n319----rcs.size():8[tm0:1507941047151510,tm1:1507941047152818,tm2:1507941047180953(28135),tm3:1507941047181271(28453),tm4:1507941047181313(28495)][tm4-tm0]:29803\nfinish 319 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26592\n320----rcs.size():8[tm0:1507941047211956,tm1:1507941047213246,tm2:1507941047241873(28627),tm3:1507941047242181(28935),tm4:1507941047242225(28979)][tm4-tm0]:30269\nfinish 320 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26439\n321----rcs.size():8[tm0:1507941047273105,tm1:1507941047274411,tm2:1507941047302781(28370),tm3:1507941047303080(28669),tm4:1507941047303124(28713)][tm4-tm0]:30019\nfinish 321 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26500\n322----rcs.size():8[tm0:1507941047333481,tm1:1507941047334778,tm2:1507941047362892(28114),tm3:1507941047363204(28426),tm4:1507941047363248(28470)][tm4-tm0]:29767\nfinish 322 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26354\n323----rcs.size():8[tm0:1507941047393719,tm1:1507941047395009,tm2:1507941047422972(27963),tm3:1507941047423296(28287),tm4:1507941047423341(28332)][tm4-tm0]:29622\nfinish 323 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27110\n324----rcs.size():8[tm0:1507941047453876,tm1:1507941047455238,tm2:1507941047484476(29238),tm3:1507941047484794(29556),tm4:1507941047485035(29797)][tm4-tm0]:31159\nfinish 324 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26535\n325----rcs.size():8[tm0:1507941047516376,tm1:1507941047517727,tm2:1507941047546355(28628),tm3:1507941047546689(28962),tm4:1507941047546758(29031)][tm4-tm0]:30382\nfinish 325 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26745\n326----rcs.size():8[tm0:1507941047578081,tm1:1507941047579430,tm2:1507941047607760(28330),tm3:1507941047608095(28665),tm4:1507941047608351(28921)][tm4-tm0]:30270\nfinish 326 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27338\n327----rcs.size():8[tm0:1507941047640758,tm1:1507941047642500,tm2:1507941047671797(29297),tm3:1507941047672125(29625),tm4:1507941047672381(29881)][tm4-tm0]:31623\nfinish 327 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27575\n328----rcs.size():7[tm0:1507941047704736,tm1:1507941047706081,tm2:1507941047735631(29550),tm3:1507941047735982(29901),tm4:1507941047736228(30147)]****[tm4-tm0]:31492\nfinish 328 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27658\n329----rcs.size():8[tm0:1507941047767285,tm1:1507941047768651,tm2:1507941047798169(29518),tm3:1507941047798531(29880),tm4:1507941047798759(30108)]****[tm4-tm0]:31474\nfinish 329 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27666\n330----rcs.size():7[tm0:1507941047831267,tm1:1507941047832590,tm2:1507941047862453(29863),tm3:1507941047862812(30222),tm4:1507941047863033(30443)]****[tm4-tm0]:31766\nfinish 330 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27345\n331----rcs.size():7[tm0:1507941047893309,tm1:1507941047894613,tm2:1507941047923944(29331),tm3:1507941047924311(29698),tm4:1507941047924537(29924)][tm4-tm0]:31228\nfinish 331 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27396\n332----rcs.size():6[tm0:1507941047954475,tm1:1507941047955801,tm2:1507941047985348(29547),tm3:1507941047985646(29845),tm4:1507941047985684(29883)][tm4-tm0]:31209\nfinish 332 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27397\n333----rcs.size():6[tm0:1507941048016486,tm1:1507941048017850,tm2:1507941048047203(29353),tm3:1507941048047499(29649),tm4:1507941048047697(29847)][tm4-tm0]:31211\nfinish 333 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27671\n334----rcs.size():7[tm0:1507941048079408,tm1:1507941048080823,tm2:1507941048110755(29932),tm3:1507941048111098(30275),tm4:1507941048111165(30342)]****[tm4-tm0]:31757\nfinish 334 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27363\n335----rcs.size():7[tm0:1507941048141562,tm1:1507941048142953,tm2:1507941048172358(29405),tm3:1507941048172667(29714),tm4:1507941048172725(29772)][tm4-tm0]:31163\nfinish 335 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27308\n336----rcs.size():6[tm0:1507941048202835,tm1:1507941048204179,tm2:1507941048233328(29149),tm3:1507941048233629(29450),tm4:1507941048233824(29645)][tm4-tm0]:30989\nfinish 336 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27883\n337----rcs.size():7[tm0:1507941048264030,tm1:1507941048265380,tm2:1507941048295305(29925),tm3:1507941048295640(30260),tm4:1507941048295688(30308)]****[tm4-tm0]:31658\nfinish 337 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28100\n338----rcs.size():6[tm0:1507941048329287,tm1:1507941048330654,tm2:1507941048361267(30613),tm3:1507941048361617(30963),tm4:1507941048361675(31021)]****[tm4-tm0]:32388\nfinish 338 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27606\n339----rcs.size():6[tm0:1507941048392210,tm1:1507941048393582,tm2:1507941048423275(29693),tm3:1507941048423622(30040),tm4:1507941048423674(30092)]****[tm4-tm0]:31464\nfinish 339 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28175\n340----rcs.size():7[tm0:1507941048456215,tm1:1507941048457611,tm2:1507941048488458(30847),tm3:1507941048488830(31219),tm4:1507941048488890(31279)]****[tm4-tm0]:32675\nfinish 340 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27737\n341----rcs.size():6[tm0:1507941048518550,tm1:1507941048519892,tm2:1507941048549813(29921),tm3:1507941048550116(30224),tm4:1507941048550177(30285)]****[tm4-tm0]:31627\nfinish 341 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27645\n342----rcs.size():6[tm0:1507941048580402,tm1:1507941048581740,tm2:1507941048612051(30311),tm3:1507941048612308(30568),tm4:1507941048612359(30619)]****[tm4-tm0]:31957\nfinish 342 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27757\n343----rcs.size():6[tm0:1507941048643240,tm1:1507941048644581,tm2:1507941048674277(29696),tm3:1507941048674524(29943),tm4:1507941048674575(29994)][tm4-tm0]:31335\nfinish 343 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27832\n344----rcs.size():6[tm0:1507941048707290,tm1:1507941048708969,tm2:1507941048738971(30002),tm3:1507941048739223(30254),tm4:1507941048739404(30435)]****[tm4-tm0]:32114\nfinish 344 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27782\n345----rcs.size():6[tm0:1507941048770998,tm1:1507941048772330,tm2:1507941048802493(30163),tm3:1507941048802734(30404),tm4:1507941048802785(30455)]****[tm4-tm0]:31787\nfinish 345 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28424\n346----rcs.size():6[tm0:1507941048833314,tm1:1507941048834614,tm2:1507941048865674(31060),tm3:1507941048865913(31299),tm4:1507941048865963(31349)]****[tm4-tm0]:32649\nfinish 346 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27805\n347----rcs.size():6[tm0:1507941048899643,tm1:1507941048900290,tm2:1507941048930771(30481),tm3:1507941048931020(30730),tm4:1507941048931059(30769)]****[tm4-tm0]:31416\nfinish 347 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27861\n348----rcs.size():6[tm0:1507941048961671,tm1:1507941048963025,tm2:1507941048993576(30551),tm3:1507941048993832(30807),tm4:1507941048993882(30857)]****[tm4-tm0]:32211\nfinish 348 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28614\n349----rcs.size():6[tm0:1507941049024280,tm1:1507941049025767,tm2:1507941049057153(31386),tm3:1507941049057390(31623),tm4:1507941049057442(31675)]****[tm4-tm0]:33162\nfinish 349 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28408\n350----rcs.size():6[tm0:1507941049090280,tm1:1507941049091022,tm2:1507941049122301(31279),tm3:1507941049122541(31519),tm4:1507941049122595(31573)]****[tm4-tm0]:32315\nfinish 350 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28460\n351----rcs.size():6[tm0:1507941049150177,tm1:1507941049150804,tm2:1507941049181888(31084),tm3:1507941049182133(31329),tm4:1507941049182191(31387)]****[tm4-tm0]:32014\nfinish 351 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28311\n352----rcs.size():6[tm0:1507941049211549,tm1:1507941049212845,tm2:1507941049243914(31069),tm3:1507941049244242(31397),tm4:1507941049244292(31447)]****[tm4-tm0]:32743\nfinish 352 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28149\n353----rcs.size():6[tm0:1507941049273408,tm1:1507941049273972,tm2:1507941049305473(31501),tm3:1507941049305790(31818),tm4:1507941049305843(31871)]****[tm4-tm0]:32435\nfinish 353 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26800\n354----rcs.size():5[tm0:1507941049335375,tm1:1507941049336688,tm2:1507941049364797(28109),tm3:1507941049365021(28333),tm4:1507941049365063(28375)][tm4-tm0]:29688\nfinish 354 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26421\n355----rcs.size():6[tm0:1507941049395785,tm1:1507941049397139,tm2:1507941049424931(27792),tm3:1507941049425269(28130),tm4:1507941049425309(28170)][tm4-tm0]:29524\nfinish 355 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26611\n356----rcs.size():6[tm0:1507941049456185,tm1:1507941049457658,tm2:1507941049485956(28298),tm3:1507941049486276(28618),tm4:1507941049486316(28658)][tm4-tm0]:30131\nfinish 356 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26358\n357----rcs.size():6[tm0:1507941049517497,tm1:1507941049518839,tm2:1507941049546594(27755),tm3:1507941049546905(28066),tm4:1507941049546952(28113)][tm4-tm0]:29455\nfinish 357 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26353\n358----rcs.size():6[tm0:1507941049578729,tm1:1507941049580167,tm2:1507941049608029(27862),tm3:1507941049608279(28112),tm4:1507941049608326(28159)][tm4-tm0]:29597\nfinish 358 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26689\n359----rcs.size():6[tm0:1507941049641786,tm1:1507941049643130,tm2:1507941049671245(28115),tm3:1507941049671577(28447),tm4:1507941049671623(28493)][tm4-tm0]:29837\nfinish 359 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26684\n360----rcs.size():6[tm0:1507941049702671,tm1:1507941049703974,tm2:1507941049732129(28155),tm3:1507941049732341(28367),tm4:1507941049732373(28399)][tm4-tm0]:29702\nfinish 360 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26352\n361----rcs.size():6[tm0:1507941049763406,tm1:1507941049764711,tm2:1507941049792488(27777),tm3:1507941049792711(28000),tm4:1507941049792742(28031)][tm4-tm0]:29336\nfinish 361 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26871\n362----rcs.size():6[tm0:1507941049828656,tm1:1507941049830049,tm2:1507941049858446(28397),tm3:1507941049858678(28629),tm4:1507941049858835(28786)][tm4-tm0]:30179\nfinish 362 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26576\n363----rcs.size():6[tm0:1507941049892842,tm1:1507941049894171,tm2:1507941049922215(28044),tm3:1507941049922444(28273),tm4:1507941049922599(28428)][tm4-tm0]:29757\nfinish 363 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26708\n364----rcs.size():6[tm0:1507941049954158,tm1:1507941049955498,tm2:1507941049984501(29003),tm3:1507941049984726(29228),tm4:1507941049984776(29278)][tm4-tm0]:30618\nfinish 364 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26582\n365----rcs.size():6[tm0:1507941050016548,tm1:1507941050017899,tm2:1507941050046501(28602),tm3:1507941050046735(28836),tm4:1507941050046871(28972)][tm4-tm0]:30323\nfinish 365 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26926\n366----rcs.size():6[tm0:1507941050078896,tm1:1507941050080232,tm2:1507941050109263(29031),tm3:1507941050109492(29260),tm4:1507941050109533(29301)][tm4-tm0]:30637\nfinish 366 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26892\n367----rcs.size():6[tm0:1507941050141476,tm1:1507941050143004,tm2:1507941050171872(28868),tm3:1507941050172086(29082),tm4:1507941050172128(29124)][tm4-tm0]:30652\nfinish 367 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26857\n368----rcs.size():6[tm0:1507941050203878,tm1:1507941050205265,tm2:1507941050233676(28411),tm3:1507941050233903(28638),tm4:1507941050233965(28700)][tm4-tm0]:30087\nfinish 368 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26538\n369----rcs.size():6[tm0:1507941050266220,tm1:1507941050267560,tm2:1507941050296026(28466),tm3:1507941050296373(28813),tm4:1507941050296414(28854)][tm4-tm0]:30194\nfinish 369 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25767\n370----rcs.size():5[tm0:1507941050328366,tm1:1507941050329783,tm2:1507941050355904(26121),tm3:1507941050356105(26322),tm4:1507941050356150(26367)][tm4-tm0]:27784\nfinish 370 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25534\n371----rcs.size():5[tm0:1507941050386348,tm1:1507941050386924,tm2:1507941050412867(25943),tm3:1507941050413021(26097),tm4:1507941050413056(26132)][tm4-tm0]:26708\nfinish 371 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25919\n372----rcs.size():5[tm0:1507941050443489,tm1:1507941050444010,tm2:1507941050470343(26333),tm3:1507941050470579(26569),tm4:1507941050470697(26687)][tm4-tm0]:27208\nfinish 372 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25510\n373----rcs.size():5[tm0:1507941050502895,tm1:1507941050503558,tm2:1507941050529446(25888),tm3:1507941050529623(26065),tm4:1507941050529743(26185)][tm4-tm0]:26848\nfinish 373 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25495\n374----rcs.size():5[tm0:1507941050562506,tm1:1507941050563065,tm2:1507941050588982(25917),tm3:1507941050589156(26091),tm4:1507941050589208(26143)][tm4-tm0]:26702\nfinish 374 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25669\n375----rcs.size():5[tm0:1507941050623192,tm1:1507941050623768,tm2:1507941050650092(26324),tm3:1507941050650284(26516),tm4:1507941050650404(26636)][tm4-tm0]:27212\nfinish 375 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25613\n376----rcs.size():5[tm0:1507941050683434,tm1:1507941050684050,tm2:1507941050710048(25998),tm3:1507941050710247(26197),tm4:1507941050710364(26314)][tm4-tm0]:26930\nfinish 376 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25427\n377----rcs.size():5[tm0:1507941050741226,tm1:1507941050742028,tm2:1507941050767840(25812),tm3:1507941050767992(25964),tm4:1507941050768019(25991)][tm4-tm0]:26793\nfinish 377 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25628\n378----rcs.size():5[tm0:1507941050800250,tm1:1507941050800831,tm2:1507941050826824(25993),tm3:1507941050826997(26166),tm4:1507941050827115(26284)][tm4-tm0]:26865\nfinish 378 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25552\n379----rcs.size():5[tm0:1507941050860610,tm1:1507941050861278,tm2:1507941050887248(25970),tm3:1507941050887421(26143),tm4:1507941050887447(26169)][tm4-tm0]:26837\nfinish 379 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25339\n380----rcs.size():5[tm0:1507941050919527,tm1:1507941050920149,tm2:1507941050945808(25659),tm3:1507941050946021(25872),tm4:1507941050946057(25908)][tm4-tm0]:26530\nfinish 380 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25568\n381----rcs.size():5[tm0:1507941050980732,tm1:1507941050981294,tm2:1507941051007271(25977),tm3:1507941051007443(26149),tm4:1507941051007559(26265)][tm4-tm0]:26827\nfinish 381 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25828\n382----rcs.size():5[tm0:1507941051039471,tm1:1507941051040060,tm2:1507941051066329(26269),tm3:1507941051066504(26444),tm4:1507941051066532(26472)][tm4-tm0]:27061\nfinish 382 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25394\n383----rcs.size():5[tm0:1507941051096651,tm1:1507941051097234,tm2:1507941051123008(25774),tm3:1507941051123209(25975),tm4:1507941051123337(26103)][tm4-tm0]:26686\nfinish 383 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25724\n384----rcs.size():5[tm0:1507941051153545,tm1:1507941051154106,tm2:1507941051180331(26225),tm3:1507941051180520(26414),tm4:1507941051180562(26456)][tm4-tm0]:27017\nfinish 384 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26101\n385----rcs.size():5[tm0:1507941051211127,tm1:1507941051211673,tm2:1507941051238317(26644),tm3:1507941051238487(26814),tm4:1507941051238527(26854)][tm4-tm0]:27400\nfinish 385 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25667\n386----rcs.size():5[tm0:1507941051269299,tm1:1507941051269900,tm2:1507941051295962(26062),tm3:1507941051296153(26253),tm4:1507941051296284(26384)][tm4-tm0]:26985\nfinish 386 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25906\n387----rcs.size():5[tm0:1507941051325962,tm1:1507941051326509,tm2:1507941051352923(26414),tm3:1507941051353120(26611),tm4:1507941051353304(26795)][tm4-tm0]:27342\nfinish 387 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26554\n388----rcs.size():5[tm0:1507941051384401,tm1:1507941051385788,tm2:1507941051413373(27585),tm3:1507941051413559(27771),tm4:1507941051413599(27811)][tm4-tm0]:29198\nfinish 388 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25547\n389----rcs.size():5[tm0:1507941051444048,tm1:1507941051444759,tm2:1507941051470714(25955),tm3:1507941051470923(26164),tm4:1507941051470963(26204)][tm4-tm0]:26915\nfinish 389 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26546\n390----rcs.size():5[tm0:1507941051505723,tm1:1507941051506428,tm2:1507941051533465(27037),tm3:1507941051533677(27249),tm4:1507941051533811(27383)][tm4-tm0]:28088\nfinish 390 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26381\n391----rcs.size():5[tm0:1507941051564916,tm1:1507941051566267,tm2:1507941051593931(27664),tm3:1507941051594124(27857),tm4:1507941051594174(27907)][tm4-tm0]:29258\nfinish 391 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25893\n392----rcs.size():5[tm0:1507941051629118,tm1:1507941051629701,tm2:1507941051656120(26419),tm3:1507941051656334(26633),tm4:1507941051656471(26770)][tm4-tm0]:27353\nfinish 392 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25912\n393----rcs.size():6[tm0:1507941051686242,tm1:1507941051686830,tm2:1507941051713191(26361),tm3:1507941051713455(26625),tm4:1507941051713589(26759)][tm4-tm0]:27347\nfinish 393 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26130\n394----rcs.size():6[tm0:1507941051742968,tm1:1507941051743593,tm2:1507941051770263(26670),tm3:1507941051770546(26953),tm4:1507941051770685(27092)][tm4-tm0]:27717\nfinish 394 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26523\n395----rcs.size():6[tm0:1507941051802317,tm1:1507941051803728,tm2:1507941051831477(27749),tm3:1507941051831731(28003),tm4:1507941051831775(28047)][tm4-tm0]:29458\nfinish 395 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26386\n396----rcs.size():6[tm0:1507941051863941,tm1:1507941051865451,tm2:1507941051893230(27779),tm3:1507941051893433(27982),tm4:1507941051893480(28029)][tm4-tm0]:29539\nfinish 396 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26025\n397----rcs.size():6[tm0:1507941051925617,tm1:1507941051926939,tm2:1507941051954357(27418),tm3:1507941051954561(27622),tm4:1507941051954606(27667)][tm4-tm0]:28989\nfinish 397 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26681\n398----rcs.size():6[tm0:1507941051986147,tm1:1507941051987556,tm2:1507941052015739(28183),tm3:1507941052015960(28404),tm4:1507941052016014(28458)][tm4-tm0]:29867\nfinish 398 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26511\n399----rcs.size():6[tm0:1507941052048081,tm1:1507941052049574,tm2:1507941052077456(27882),tm3:1507941052077677(28103),tm4:1507941052077832(28258)][tm4-tm0]:29751\nfinish 399 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26340\n400----rcs.size():6[tm0:1507941052111811,tm1:1507941052113132,tm2:1507941052140703(27571),tm3:1507941052140955(27823),tm4:1507941052141110(27978)][tm4-tm0]:29299\nfinish 400 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26936\n401----rcs.size():6[tm0:1507941052169651,tm1:1507941052170251,tm2:1507941052198309(28058),tm3:1507941052198540(28289),tm4:1507941052198591(28340)][tm4-tm0]:28940\nfinish 401 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26733\n402----rcs.size():6[tm0:1507941052230180,tm1:1507941052231557,tm2:1507941052259779(28222),tm3:1507941052259994(28437),tm4:1507941052260039(28482)][tm4-tm0]:29859\nfinish 402 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26636\n403----rcs.size():6[tm0:1507941052291073,tm1:1507941052292601,tm2:1507941052320588(27987),tm3:1507941052320803(28202),tm4:1507941052320849(28248)][tm4-tm0]:29776\nfinish 403 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26717\n404----rcs.size():6[tm0:1507941052352291,tm1:1507941052353792,tm2:1507941052382118(28326),tm3:1507941052382355(28563),tm4:1507941052382403(28611)][tm4-tm0]:30112\nfinish 404 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26464\n405----rcs.size():6[tm0:1507941052414042,tm1:1507941052415400,tm2:1507941052443574(28174),tm3:1507941052443822(28422),tm4:1507941052443868(28468)][tm4-tm0]:29826\nfinish 405 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26855\n406----rcs.size():6[tm0:1507941052475226,tm1:1507941052476568,tm2:1507941052504795(28227),tm3:1507941052505010(28442),tm4:1507941052505044(28476)][tm4-tm0]:29818\nfinish 406 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27441\n407----rcs.size():6[tm0:1507941052536902,tm1:1507941052538367,tm2:1507941052567624(29257),tm3:1507941052567857(29490),tm4:1507941052567891(29524)][tm4-tm0]:30989\nfinish 407 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26918\n408----rcs.size():6[tm0:1507941052599559,tm1:1507941052601029,tm2:1507941052630048(29019),tm3:1507941052630289(29260),tm4:1507941052630462(29433)][tm4-tm0]:30903\nfinish 408 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26832\n409----rcs.size():6[tm0:1507941052661586,tm1:1507941052662893,tm2:1507941052691681(28788),tm3:1507941052691907(29014),tm4:1507941052691941(29048)][tm4-tm0]:30355\nfinish 409 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26571\n410----rcs.size():6[tm0:1507941052723088,tm1:1507941052724586,tm2:1507941052753287(28701),tm3:1507941052753510(28924),tm4:1507941052753562(28976)][tm4-tm0]:30474\nfinish 410 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28293\n411----rcs.size():6[tm0:1507941052785609,tm1:1507941052787094,tm2:1507941052818068(30974),tm3:1507941052818318(31224),tm4:1507941052818364(31270)]****[tm4-tm0]:32755\nfinish 411 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27300\n412----rcs.size():6[tm0:1507941052849194,tm1:1507941052850521,tm2:1507941052880027(29506),tm3:1507941052880261(29740),tm4:1507941052880308(29787)][tm4-tm0]:31114\nfinish 412 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27464\n413----rcs.size():6[tm0:1507941052912629,tm1:1507941052914028,tm2:1507941052943639(29611),tm3:1507941052943895(29867),tm4:1507941052943941(29913)][tm4-tm0]:31312\nfinish 413 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27334\n414----rcs.size():6[tm0:1507941052975125,tm1:1507941052976534,tm2:1507941053005689(29155),tm3:1507941053005939(29405),tm4:1507941053005989(29455)][tm4-tm0]:30864\nfinish 414 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27317\n415----rcs.size():6[tm0:1507941053036806,tm1:1507941053038255,tm2:1507941053067388(29133),tm3:1507941053067639(29384),tm4:1507941053067798(29543)][tm4-tm0]:30992\nfinish 415 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28020\n416----rcs.size():6[tm0:1507941053098528,tm1:1507941053099964,tm2:1507941053130345(30381),tm3:1507941053130593(30629),tm4:1507941053130642(30678)]****[tm4-tm0]:32114\nfinish 416 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27607\n417----rcs.size():6[tm0:1507941053162273,tm1:1507941053163728,tm2:1507941053193450(29722),tm3:1507941053193694(29966),tm4:1507941053193874(30146)]****[tm4-tm0]:31601\nfinish 417 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27483\n418----rcs.size():5[tm0:1507941053225520,tm1:1507941053226925,tm2:1507941053256471(29546),tm3:1507941053256732(29807),tm4:1507941053256875(29950)][tm4-tm0]:31355\nfinish 418 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27097\n419----rcs.size():5[tm0:1507941053290808,tm1:1507941053292248,tm2:1507941053321465(29217),tm3:1507941053321657(29409),tm4:1507941053321797(29549)][tm4-tm0]:30989\nfinish 419 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27421\n420----rcs.size():5[tm0:1507941053354661,tm1:1507941053356032,tm2:1507941053385401(29369),tm3:1507941053385603(29571),tm4:1507941053385717(29685)][tm4-tm0]:31056\nfinish 420 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26836\n421----rcs.size():5[tm0:1507941053419833,tm1:1507941053421091,tm2:1507941053449294(28203),tm3:1507941053449481(28390),tm4:1507941053449505(28414)][tm4-tm0]:29672\nfinish 421 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25722\n422----rcs.size():4[tm0:1507941053482222,tm1:1507941053483510,tm2:1507941053509541(26031),tm3:1507941053509708(26198),tm4:1507941053509736(26226)][tm4-tm0]:27514\nfinish 422 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25251\n423----rcs.size():4[tm0:1507941053540738,tm1:1507941053541538,tm2:1507941053567114(25576),tm3:1507941053567254(25716),tm4:1507941053567282(25744)][tm4-tm0]:26544\nfinish 423 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25514\n424----rcs.size():4[tm0:1507941053601576,tm1:1507941053602276,tm2:1507941053628157(25881),tm3:1507941053628273(25997),tm4:1507941053628300(26024)][tm4-tm0]:26724\nfinish 424 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25165\n425----rcs.size():5[tm0:1507941053660862,tm1:1507941053661525,tm2:1507941053687014(25489),tm3:1507941053687261(25736),tm4:1507941053687349(25824)][tm4-tm0]:26487\nfinish 425 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26002\n426----rcs.size():5[tm0:1507941053721660,tm1:1507941053722374,tm2:1507941053748707(26333),tm3:1507941053748923(26549),tm4:1507941053748950(26576)][tm4-tm0]:27290\nfinish 426 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25219\n427----rcs.size():5[tm0:1507941053782061,tm1:1507941053782725,tm2:1507941053808264(25539),tm3:1507941053808516(25791),tm4:1507941053808547(25822)][tm4-tm0]:26486\nfinish 427 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25408\n428----rcs.size():5[tm0:1507941053844270,tm1:1507941053844990,tm2:1507941053870765(25775),tm3:1507941053870902(25912),tm4:1507941053870934(25944)][tm4-tm0]:26664\nfinish 428 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25195\n429----rcs.size():5[tm0:1507941053901472,tm1:1507941053902131,tm2:1507941053927784(25653),tm3:1507941053927932(25801),tm4:1507941053927968(25837)][tm4-tm0]:26496\nfinish 429 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25292\n430----rcs.size():5[tm0:1507941053958626,tm1:1507941053959295,tm2:1507941053984934(25639),tm3:1507941053985110(25815),tm4:1507941053985223(25928)][tm4-tm0]:26597\nfinish 430 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25262\n431----rcs.size():5[tm0:1507941054015928,tm1:1507941054016660,tm2:1507941054042290(25630),tm3:1507941054042529(25869),tm4:1507941054042634(25974)][tm4-tm0]:26706\nfinish 431 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25323\n432----rcs.size():5[tm0:1507941054072889,tm1:1507941054073798,tm2:1507941054099461(25663),tm3:1507941054099610(25812),tm4:1507941054099718(25920)][tm4-tm0]:26829\nfinish 432 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25671\n433----rcs.size():5[tm0:1507941054130205,tm1:1507941054130886,tm2:1507941054156993(26107),tm3:1507941054157155(26269),tm4:1507941054157180(26294)][tm4-tm0]:26975\nfinish 433 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25543\n434----rcs.size():5[tm0:1507941054186421,tm1:1507941054187003,tm2:1507941054212935(25932),tm3:1507941054213070(26067),tm4:1507941054213095(26092)][tm4-tm0]:26674\nfinish 434 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25406\n435----rcs.size():5[tm0:1507941054242537,tm1:1507941054243118,tm2:1507941054268863(25745),tm3:1507941054269018(25900),tm4:1507941054269160(26042)][tm4-tm0]:26623\nfinish 435 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25620\n436----rcs.size():5[tm0:1507941054300038,tm1:1507941054300788,tm2:1507941054326771(25983),tm3:1507941054326934(26146),tm4:1507941054327042(26254)][tm4-tm0]:27004\nfinish 436 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25637\n437----rcs.size():5[tm0:1507941054357456,tm1:1507941054358089,tm2:1507941054384209(26120),tm3:1507941054384369(26280),tm4:1507941054384394(26305)][tm4-tm0]:26938\nfinish 437 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25551\n438----rcs.size():5[tm0:1507941054414234,tm1:1507941054414839,tm2:1507941054440756(25917),tm3:1507941054440950(26111),tm4:1507941054440984(26145)][tm4-tm0]:26750\nfinish 438 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25765\n439----rcs.size():5[tm0:1507941054470695,tm1:1507941054471300,tm2:1507941054497450(26150),tm3:1507941054497611(26311),tm4:1507941054497637(26337)][tm4-tm0]:26942\nfinish 439 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25568\n440----rcs.size():5[tm0:1507941054529392,tm1:1507941054530007,tm2:1507941054555929(25922),tm3:1507941054556092(26085),tm4:1507941054556127(26120)][tm4-tm0]:26735\nfinish 440 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25834\n441----rcs.size():5[tm0:1507941054586050,tm1:1507941054586774,tm2:1507941054613003(26229),tm3:1507941054613169(26395),tm4:1507941054613203(26429)][tm4-tm0]:27153\nfinish 441 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25425\n442----rcs.size():5[tm0:1507941054642971,tm1:1507941054643553,tm2:1507941054669379(25826),tm3:1507941054669539(25986),tm4:1507941054669564(26011)][tm4-tm0]:26593\nfinish 442 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25400\n443----rcs.size():5[tm0:1507941054698940,tm1:1507941054699505,tm2:1507941054725325(25820),tm3:1507941054725481(25976),tm4:1507941054725516(26011)][tm4-tm0]:26576\nfinish 443 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26195\n444----rcs.size():5[tm0:1507941054755544,tm1:1507941054756151,tm2:1507941054783060(26909),tm3:1507941054783226(27075),tm4:1507941054783262(27111)][tm4-tm0]:27718\nfinish 444 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25677\n445----rcs.size():5[tm0:1507941054813580,tm1:1507941054814144,tm2:1507941054840370(26226),tm3:1507941054840607(26463),tm4:1507941054840648(26504)][tm4-tm0]:27068\nfinish 445 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26011\n446----rcs.size():6[tm0:1507941054871470,tm1:1507941054872145,tm2:1507941054898581(26436),tm3:1507941054898862(26717),tm4:1507941054898989(26844)][tm4-tm0]:27519\nfinish 446 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25498\n447----rcs.size():6[tm0:1507941054928865,tm1:1507941054929412,tm2:1507941054955315(25903),tm3:1507941054955571(26159),tm4:1507941054955599(26187)][tm4-tm0]:26734\nfinish 447 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26512\n448----rcs.size():6[tm0:1507941054985219,tm1:1507941054985783,tm2:1507941055013034(27251),tm3:1507941055013291(27508),tm4:1507941055013433(27650)][tm4-tm0]:28214\nfinish 448 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26493\n449----rcs.size():6[tm0:1507941055045321,tm1:1507941055046638,tm2:1507941055074382(27744),tm3:1507941055074566(27928),tm4:1507941055074597(27959)][tm4-tm0]:29276\nfinish 449 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26213\n450----rcs.size():6[tm0:1507941055105211,tm1:1507941055106708,tm2:1507941055134163(27455),tm3:1507941055134350(27642),tm4:1507941055134379(27671)][tm4-tm0]:29168\nfinish 450 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26182\n451----rcs.size():6[tm0:1507941055163451,tm1:1507941055164789,tm2:1507941055192215(27426),tm3:1507941055192418(27629),tm4:1507941055192446(27657)][tm4-tm0]:28995\nfinish 451 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26659\n452----rcs.size():6[tm0:1507941055223321,tm1:1507941055224797,tm2:1507941055252786(27989),tm3:1507941055252984(28187),tm4:1507941055253028(28231)][tm4-tm0]:29707\nfinish 452 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26285\n453----rcs.size():6[tm0:1507941055289066,tm1:1507941055290718,tm2:1507941055318701(27983),tm3:1507941055318898(28180),tm4:1507941055318960(28242)][tm4-tm0]:29894\nfinish 453 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26775\n454----rcs.size():6[tm0:1507941055349864,tm1:1507941055351209,tm2:1507941055379270(28061),tm3:1507941055379464(28255),tm4:1507941055379510(28301)][tm4-tm0]:29646\nfinish 454 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26309\n455----rcs.size():6[tm0:1507941055409941,tm1:1507941055411254,tm2:1507941055438783(27529),tm3:1507941055438986(27732),tm4:1507941055439034(27780)][tm4-tm0]:29093\nfinish 455 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26167\n456----rcs.size():6[tm0:1507941055469076,tm1:1507941055469613,tm2:1507941055496356(26743),tm3:1507941055496541(26928),tm4:1507941055496584(26971)][tm4-tm0]:27508\nfinish 456 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26200\n457----rcs.size():6[tm0:1507941055531239,tm1:1507941055532573,tm2:1507941055560100(27527),tm3:1507941055560315(27742),tm4:1507941055560357(27784)][tm4-tm0]:29118\nfinish 457 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26456\n458----rcs.size():6[tm0:1507941055590641,tm1:1507941055592147,tm2:1507941055619760(27613),tm3:1507941055619948(27801),tm4:1507941055619993(27846)][tm4-tm0]:29352\nfinish 458 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26813\n459----rcs.size():6[tm0:1507941055650912,tm1:1507941055652270,tm2:1507941055680472(28202),tm3:1507941055680666(28396),tm4:1507941055680711(28441)][tm4-tm0]:29799\nfinish 459 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26843\n460----rcs.size():6[tm0:1507941055716467,tm1:1507941055717781,tm2:1507941055745972(28191),tm3:1507941055746181(28400),tm4:1507941055746328(28547)][tm4-tm0]:29861\nfinish 460 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26615\n461----rcs.size():6[tm0:1507941055777070,tm1:1507941055778364,tm2:1507941055806269(27905),tm3:1507941055806452(28088),tm4:1507941055806483(28119)][tm4-tm0]:29413\nfinish 461 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26882\n462----rcs.size():6[tm0:1507941055836832,tm1:1507941055838195,tm2:1507941055866603(28408),tm3:1507941055866813(28618),tm4:1507941055866860(28665)][tm4-tm0]:30028\nfinish 462 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26601\n463----rcs.size():6[tm0:1507941055898725,tm1:1507941055900111,tm2:1507941055928075(27964),tm3:1507941055928305(28194),tm4:1507941055928472(28361)][tm4-tm0]:29747\nfinish 463 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26711\n464----rcs.size():6[tm0:1507941055960276,tm1:1507941055961630,tm2:1507941055989637(28007),tm3:1507941055989860(28230),tm4:1507941055989905(28275)][tm4-tm0]:29629\nfinish 464 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26781\n465----rcs.size():6[tm0:1507941056022495,tm1:1507941056024089,tm2:1507941056052322(28233),tm3:1507941056052544(28455),tm4:1507941056052698(28609)][tm4-tm0]:30203\nfinish 465 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27129\n466----rcs.size():6[tm0:1507941056084440,tm1:1507941056085847,tm2:1507941056114446(28599),tm3:1507941056114678(28831),tm4:1507941056114724(28877)][tm4-tm0]:30284\nfinish 466 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26381\n467----rcs.size():6[tm0:1507941056150084,tm1:1507941056151422,tm2:1507941056179176(27754),tm3:1507941056179397(27975),tm4:1507941056179445(28023)][tm4-tm0]:29361\nfinish 467 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26659\n468----rcs.size():6[tm0:1507941056211170,tm1:1507941056212580,tm2:1507941056240599(28019),tm3:1507941056240828(28248),tm4:1507941056240983(28403)][tm4-tm0]:29813\nfinish 468 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26529\n469----rcs.size():6[tm0:1507941056272794,tm1:1507941056274363,tm2:1507941056302312(27949),tm3:1507941056302548(28185),tm4:1507941056302708(28345)][tm4-tm0]:29914\nfinish 469 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27083\n470----rcs.size():6[tm0:1507941056334393,tm1:1507941056335859,tm2:1507941056364892(29033),tm3:1507941056365108(29249),tm4:1507941056365275(29416)][tm4-tm0]:30882\nfinish 470 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26682\n471----rcs.size():6[tm0:1507941056402249,tm1:1507941056403632,tm2:1507941056432355(28723),tm3:1507941056432591(28959),tm4:1507941056432754(29122)][tm4-tm0]:30505\nfinish 471 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26814\n472----rcs.size():6[tm0:1507941056466400,tm1:1507941056467747,tm2:1507941056496065(28318),tm3:1507941056496321(28574),tm4:1507941056496366(28619)][tm4-tm0]:29966\nfinish 472 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26653\n473----rcs.size():5[tm0:1507941056528081,tm1:1507941056529465,tm2:1507941056557691(28226),tm3:1507941056557923(28458),tm4:1507941056557950(28485)][tm4-tm0]:29869\nfinish 473 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26146\n474----rcs.size():4[tm0:1507941056589146,tm1:1507941056590763,tm2:1507941056618020(27257),tm3:1507941056618226(27463),tm4:1507941056618261(27498)][tm4-tm0]:29115\nfinish 474 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26816\n475----rcs.size():5[tm0:1507941056650130,tm1:1507941056651544,tm2:1507941056679660(28116),tm3:1507941056679872(28328),tm4:1507941056679908(28364)][tm4-tm0]:29778\nfinish 475 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26541\n476----rcs.size():5[tm0:1507941056711977,tm1:1507941056713400,tm2:1507941056741321(27921),tm3:1507941056741569(28169),tm4:1507941056741602(28202)][tm4-tm0]:29625\nfinish 476 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26560\n477----rcs.size():6[tm0:1507941056773568,tm1:1507941056775074,tm2:1507941056802985(27911),tm3:1507941056803341(28267),tm4:1507941056803379(28305)][tm4-tm0]:29811\nfinish 477 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27023\n478----rcs.size():6[tm0:1507941056834622,tm1:1507941056836004,tm2:1507941056864401(28397),tm3:1507941056864641(28637),tm4:1507941056864678(28674)][tm4-tm0]:30056\nfinish 478 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26538\n479----rcs.size():6[tm0:1507941056899041,tm1:1507941056900413,tm2:1507941056928346(27933),tm3:1507941056928590(28177),tm4:1507941056928632(28219)][tm4-tm0]:29591\nfinish 479 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26475\n480----rcs.size():6[tm0:1507941056960704,tm1:1507941056962101,tm2:1507941056990020(27919),tm3:1507941056990247(28146),tm4:1507941056990292(28191)][tm4-tm0]:29588\nfinish 480 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26615\n481----rcs.size():6[tm0:1507941057022195,tm1:1507941057023896,tm2:1507941057051940(28044),tm3:1507941057052165(28269),tm4:1507941057052206(28310)][tm4-tm0]:30011\nfinish 481 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26721\n482----rcs.size():6[tm0:1507941057084079,tm1:1507941057085445,tm2:1507941057113710(28265),tm3:1507941057113909(28464),tm4:1507941057113953(28508)][tm4-tm0]:29874\nfinish 482 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26715\n483----rcs.size():6[tm0:1507941057145657,tm1:1507941057146986,tm2:1507941057175167(28181),tm3:1507941057175384(28398),tm4:1507941057175426(28440)][tm4-tm0]:29769\nfinish 483 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26564\n484----rcs.size():6[tm0:1507941057207456,tm1:1507941057208973,tm2:1507941057237533(28560),tm3:1507941057237742(28769),tm4:1507941057237899(28926)][tm4-tm0]:30443\nfinish 484 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26714\n485----rcs.size():6[tm0:1507941057270820,tm1:1507941057272158,tm2:1507941057300718(28560),tm3:1507941057300947(28789),tm4:1507941057301006(28848)][tm4-tm0]:30186\nfinish 485 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26519\n486----rcs.size():6[tm0:1507941057331887,tm1:1507941057333290,tm2:1507941057361323(28033),tm3:1507941057361552(28262),tm4:1507941057361693(28403)][tm4-tm0]:29806\nfinish 486 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26620\n487----rcs.size():6[tm0:1507941057393556,tm1:1507941057394987,tm2:1507941057423171(28184),tm3:1507941057423375(28388),tm4:1507941057423421(28434)][tm4-tm0]:29865\nfinish 487 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26538\n488----rcs.size():6[tm0:1507941057454995,tm1:1507941057456561,tm2:1507941057484647(28086),tm3:1507941057484835(28274),tm4:1507941057484881(28320)][tm4-tm0]:29886\nfinish 488 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27022\n489----rcs.size():6[tm0:1507941057517318,tm1:1507941057518759,tm2:1507941057547634(28875),tm3:1507941057547830(29071),tm4:1507941057547976(29217)][tm4-tm0]:30658\nfinish 489 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26616\n490----rcs.size():6[tm0:1507941057583074,tm1:1507941057584336,tm2:1507941057612903(28567),tm3:1507941057613114(28778),tm4:1507941057613185(28849)][tm4-tm0]:30111\nfinish 490 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26794\n491----rcs.size():6[tm0:1507941057648578,tm1:1507941057649917,tm2:1507941057678409(28492),tm3:1507941057678626(28709),tm4:1507941057678672(28755)][tm4-tm0]:30094\nfinish 491 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26680\n492----rcs.size():6[tm0:1507941057710746,tm1:1507941057712182,tm2:1507941057741003(28821),tm3:1507941057741231(29049),tm4:1507941057741262(29080)][tm4-tm0]:30516\nfinish 492 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27134\n493----rcs.size():6[tm0:1507941057773902,tm1:1507941057775268,tm2:1507941057804202(28934),tm3:1507941057804411(29143),tm4:1507941057804581(29313)][tm4-tm0]:30679\nfinish 493 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27625\n494----rcs.size():6[tm0:1507941057835816,tm1:1507941057837228,tm2:1507941057866787(29559),tm3:1507941057867037(29809),tm4:1507941057867199(29971)][tm4-tm0]:31383\nfinish 494 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27388\n495----rcs.size():6[tm0:1507941057900357,tm1:1507941057901754,tm2:1507941057931023(29269),tm3:1507941057931277(29523),tm4:1507941057931308(29554)][tm4-tm0]:30951\nfinish 495 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27053\n496----rcs.size():6[tm0:1507941057962397,tm1:1507941057963703,tm2:1507941057992623(28920),tm3:1507941057992831(29128),tm4:1507941057992878(29175)][tm4-tm0]:30481\nfinish 496 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27310\n497----rcs.size():6[tm0:1507941058023921,tm1:1507941058025307,tm2:1507941058054523(29216),tm3:1507941058054734(29427),tm4:1507941058054765(29458)][tm4-tm0]:30844\nfinish 497 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27800\n498----rcs.size():6[tm0:1507941058085282,tm1:1507941058086605,tm2:1507941058116252(29647),tm3:1507941058116460(29855),tm4:1507941058116491(29886)][tm4-tm0]:31209\nfinish 498 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26638\n499----rcs.size():6[tm0:1507941058147535,tm1:1507941058148896,tm2:1507941058176938(28042),tm3:1507941058177159(28263),tm4:1507941058177189(28293)][tm4-tm0]:29654\nfinish 499 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27220\n500----rcs.size():6[tm0:1507941058212641,tm1:1507941058213953,tm2:1507941058242881(28928),tm3:1507941058243096(29143),tm4:1507941058243125(29172)][tm4-tm0]:30484\nfinish 500 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26602\n501----rcs.size():6[tm0:1507941058271898,tm1:1507941058273521,tm2:1507941058301600(28079),tm3:1507941058301834(28313),tm4:1507941058301865(28344)][tm4-tm0]:29967\nfinish 501 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27103\n502----rcs.size():6[tm0:1507941058332308,tm1:1507941058333626,tm2:1507941058362442(28816),tm3:1507941058362731(29105),tm4:1507941058362778(29152)][tm4-tm0]:30470\nfinish 502 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25866\n503----rcs.size():5[tm0:1507941058397775,tm1:1507941058399133,tm2:1507941058425689(26556),tm3:1507941058425887(26754),tm4:1507941058425920(26787)][tm4-tm0]:28145\nfinish 503 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25685\n504----rcs.size():5[tm0:1507941058456506,tm1:1507941058457212,tm2:1507941058483263(26051),tm3:1507941058483421(26209),tm4:1507941058483447(26235)][tm4-tm0]:26941\nfinish 504 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25293\n505----rcs.size():5[tm0:1507941058518018,tm1:1507941058518569,tm2:1507941058544210(25641),tm3:1507941058544393(25824),tm4:1507941058544429(25860)][tm4-tm0]:26411\nfinish 505 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25822\n506----rcs.size():5[tm0:1507941058574900,tm1:1507941058575459,tm2:1507941058601718(26259),tm3:1507941058601870(26411),tm4:1507941058601908(26449)][tm4-tm0]:27008\nfinish 506 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25609\n507----rcs.size():5[tm0:1507941058633042,tm1:1507941058633597,tm2:1507941058659566(25969),tm3:1507941058659728(26131),tm4:1507941058659753(26156)][tm4-tm0]:26711\nfinish 507 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25286\n508----rcs.size():5[tm0:1507941058689814,tm1:1507941058690416,tm2:1507941058716025(25609),tm3:1507941058716207(25791),tm4:1507941058716244(25828)][tm4-tm0]:26430\nfinish 508 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25544\n509----rcs.size():5[tm0:1507941058746888,tm1:1507941058747624,tm2:1507941058773514(25890),tm3:1507941058773690(26066),tm4:1507941058773726(26102)][tm4-tm0]:26838\nfinish 509 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25481\n510----rcs.size():5[tm0:1507941058807801,tm1:1507941058808425,tm2:1507941058834287(25862),tm3:1507941058834454(26029),tm4:1507941058834478(26053)][tm4-tm0]:26677\nfinish 510 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25543\n511----rcs.size():5[tm0:1507941058869447,tm1:1507941058869956,tm2:1507941058895839(25883),tm3:1507941058896015(26059),tm4:1507941058896054(26098)][tm4-tm0]:26607\nfinish 511 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25669\n512----rcs.size():5[tm0:1507941058926599,tm1:1507941058927233,tm2:1507941058953270(26037),tm3:1507941058953464(26231),tm4:1507941058953490(26257)][tm4-tm0]:26891\nfinish 512 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25741\n513----rcs.size():5[tm0:1507941058983462,tm1:1507941058984190,tm2:1507941059010318(26128),tm3:1507941059010533(26343),tm4:1507941059010571(26381)][tm4-tm0]:27109\nfinish 513 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:25564\n514----rcs.size():5[tm0:1507941059040659,tm1:1507941059041386,tm2:1507941059067406(26020),tm3:1507941059067585(26199),tm4:1507941059067620(26234)][tm4-tm0]:26961\nfinish 514 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26443\n515----rcs.size():4[tm0:1507941059099276,tm1:1507941059099895,tm2:1507941059126966(27071),tm3:1507941059127118(27223),tm4:1507941059127161(27266)][tm4-tm0]:27885\nfinish 515 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26371\n516----rcs.size():5[tm0:1507941059162572,tm1:1507941059164056,tm2:1507941059191503(27447),tm3:1507941059191740(27684),tm4:1507941059191782(27726)][tm4-tm0]:29210\nfinish 516 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25554\n517----rcs.size():5[tm0:1507941059226154,tm1:1507941059226690,tm2:1507941059252665(25975),tm3:1507941059252885(26195),tm4:1507941059252907(26217)][tm4-tm0]:26753\nfinish 517 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:25677\n518----rcs.size():5[tm0:1507941059288754,tm1:1507941059289570,tm2:1507941059315759(26189),tm3:1507941059315993(26423),tm4:1507941059316022(26452)][tm4-tm0]:27268\nfinish 518 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26084\n519----rcs.size():5[tm0:1507941059350763,tm1:1507941059351321,tm2:1507941059377965(26644),tm3:1507941059378114(26793),tm4:1507941059378172(26851)][tm4-tm0]:27409\nfinish 519 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26135\n520----rcs.size():5[tm0:1507941059414440,tm1:1507941059415715,tm2:1507941059442836(27121),tm3:1507941059442988(27273),tm4:1507941059443016(27301)][tm4-tm0]:28576\nfinish 520 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26671\n521----rcs.size():5[tm0:1507941059472767,tm1:1507941059473507,tm2:1507941059501119(27612),tm3:1507941059501385(27878),tm4:1507941059501536(28029)][tm4-tm0]:28769\nfinish 521 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26640\n522----rcs.size():5[tm0:1507941059534003,tm1:1507941059535459,tm2:1507941059563623(28164),tm3:1507941059563867(28408),tm4:1507941059563905(28446)][tm4-tm0]:29902\nfinish 522 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26066\n523----rcs.size():5[tm0:1507941059593990,tm1:1507941059595272,tm2:1507941059622447(27175),tm3:1507941059622618(27346),tm4:1507941059622644(27372)][tm4-tm0]:28654\nfinish 523 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26172\n524----rcs.size():5[tm0:1507941059652512,tm1:1507941059653089,tm2:1507941059679831(26742),tm3:1507941059679999(26910),tm4:1507941059680122(27033)][tm4-tm0]:27610\nfinish 524 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26257\n525----rcs.size():5[tm0:1507941059710771,tm1:1507941059711353,tm2:1507941059738181(26828),tm3:1507941059738357(27004),tm4:1507941059738383(27030)][tm4-tm0]:27612\nfinish 525 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26384\n526----rcs.size():5[tm0:1507941059769387,tm1:1507941059770831,tm2:1507941059799021(28190),tm3:1507941059799209(28378),tm4:1507941059799248(28417)][tm4-tm0]:29861\nfinish 526 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26516\n527----rcs.size():5[tm0:1507941059830643,tm1:1507941059831984,tm2:1507941059860088(28104),tm3:1507941059860261(28277),tm4:1507941059860304(28320)][tm4-tm0]:29661\nfinish 527 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26771\n528----rcs.size():5[tm0:1507941059892308,tm1:1507941059893663,tm2:1507941059922269(28606),tm3:1507941059922440(28777),tm4:1507941059922573(28910)][tm4-tm0]:30265\nfinish 528 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26397\n529----rcs.size():5[tm0:1507941059954231,tm1:1507941059955899,tm2:1507941059983763(27864),tm3:1507941059983956(28057),tm4:1507941059984091(28192)][tm4-tm0]:29860\nfinish 529 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26348\n530----rcs.size():5[tm0:1507941060015928,tm1:1507941060017355,tm2:1507941060044969(27614),tm3:1507941060045186(27831),tm4:1507941060045228(27873)][tm4-tm0]:29300\nfinish 530 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26253\n531----rcs.size():5[tm0:1507941060077018,tm1:1507941060078355,tm2:1507941060105974(27619),tm3:1507941060106133(27778),tm4:1507941060106170(27815)][tm4-tm0]:29152\nfinish 531 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27037\n532----rcs.size():5[tm0:1507941060137478,tm1:1507941060139163,tm2:1507941060167868(28705),tm3:1507941060168057(28894),tm4:1507941060168207(29044)][tm4-tm0]:30729\nfinish 532 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27149\n533----rcs.size():5[tm0:1507941060201748,tm1:1507941060203176,tm2:1507941060231757(28581),tm3:1507941060231938(28762),tm4:1507941060232093(28917)][tm4-tm0]:30345\nfinish 533 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26689\n534----rcs.size():5[tm0:1507941060265570,tm1:1507941060266878,tm2:1507941060294829(27951),tm3:1507941060295010(28132),tm4:1507941060295039(28161)][tm4-tm0]:29469\nfinish 534 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26775\n535----rcs.size():5[tm0:1507941060325570,tm1:1507941060326848,tm2:1507941060354906(28058),tm3:1507941060355087(28239),tm4:1507941060355114(28266)][tm4-tm0]:29544\nfinish 535 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27233\n536----rcs.size():4[tm0:1507941060385553,tm1:1507941060386843,tm2:1507941060415674(28831),tm3:1507941060415841(28998),tm4:1507941060415866(29023)][tm4-tm0]:30313\nfinish 536 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26820\n537----rcs.size():4[tm0:1507941060451107,tm1:1507941060452419,tm2:1507941060480719(28300),tm3:1507941060480864(28445),tm4:1507941060480889(28470)][tm4-tm0]:29782\nfinish 537 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26510\n538----rcs.size():4[tm0:1507941060515110,tm1:1507941060516494,tm2:1507941060544623(28129),tm3:1507941060544760(28266),tm4:1507941060544800(28306)][tm4-tm0]:29690\nfinish 538 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27333\n539----rcs.size():4[tm0:1507941060576147,tm1:1507941060577549,tm2:1507941060606689(29140),tm3:1507941060606837(29288),tm4:1507941060606864(29315)][tm4-tm0]:30717\nfinish 539 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26755\n540----rcs.size():4[tm0:1507941060637396,tm1:1507941060638800,tm2:1507941060667171(28371),tm3:1507941060667318(28518),tm4:1507941060667342(28542)][tm4-tm0]:29946\nfinish 540 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26514\n541----rcs.size():5[tm0:1507941060703437,tm1:1507941060704727,tm2:1507941060733168(28441),tm3:1507941060733363(28636),tm4:1507941060733387(28660)][tm4-tm0]:29950\nfinish 541 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26626\n542----rcs.size():5[tm0:1507941060764014,tm1:1507941060765307,tm2:1507941060793413(28106),tm3:1507941060793627(28320),tm4:1507941060793672(28365)][tm4-tm0]:29658\nfinish 542 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27098\n543----rcs.size():5[tm0:1507941060825371,tm1:1507941060826777,tm2:1507941060855941(29164),tm3:1507941060856124(29347),tm4:1507941060856178(29401)][tm4-tm0]:30807\nfinish 543 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26560\n544----rcs.size():5[tm0:1507941060887093,tm1:1507941060888350,tm2:1507941060916687(28337),tm3:1507941060916885(28535),tm4:1507941060916915(28565)][tm4-tm0]:29822\nfinish 544 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27261\n545----rcs.size():5[tm0:1507941060952762,tm1:1507941060954157,tm2:1507941060983804(29647),tm3:1507941060984007(29850),tm4:1507941060984057(29900)][tm4-tm0]:31295\nfinish 545 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27368\n546----rcs.size():5[tm0:1507941061016383,tm1:1507941061017748,tm2:1507941061046947(29199),tm3:1507941061047134(29386),tm4:1507941061047191(29443)][tm4-tm0]:30808\nfinish 546 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27557\n547----rcs.size():5[tm0:1507941061078121,tm1:1507941061079530,tm2:1507941061108935(29405),tm3:1507941061109123(29593),tm4:1507941061109181(29651)][tm4-tm0]:31060\nfinish 547 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27292\n548----rcs.size():5[tm0:1507941061142476,tm1:1507941061143926,tm2:1507941061173195(29269),tm3:1507941061173409(29483),tm4:1507941061173439(29513)][tm4-tm0]:30963\nfinish 548 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27326\n549----rcs.size():5[tm0:1507941061207938,tm1:1507941061209339,tm2:1507941061238648(29309),tm3:1507941061238844(29505),tm4:1507941061238874(29535)][tm4-tm0]:30936\nfinish 549 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27341\n550----rcs.size():5[tm0:1507941061270073,tm1:1507941061271452,tm2:1507941061301094(29642),tm3:1507941061301336(29884),tm4:1507941061301367(29915)][tm4-tm0]:31294\nfinish 550 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27416\n551----rcs.size():5[tm0:1507941061329373,tm1:1507941061330744,tm2:1507941061360251(29507),tm3:1507941061360449(29705),tm4:1507941061360480(29736)][tm4-tm0]:31107\nfinish 551 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27347\n552----rcs.size():5[tm0:1507941061390793,tm1:1507941061392107,tm2:1507941061421663(29556),tm3:1507941061421882(29775),tm4:1507941061421913(29806)][tm4-tm0]:31120\nfinish 552 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27289\n553----rcs.size():5[tm0:1507941061453551,tm1:1507941061454916,tm2:1507941061484852(29936),tm3:1507941061485062(30146),tm4:1507941061485113(30197)]****[tm4-tm0]:31562\nfinish 553 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27490\n554----rcs.size():5[tm0:1507941061515705,tm1:1507941061517134,tm2:1507941061546819(29685),tm3:1507941061547014(29880),tm4:1507941061547067(29933)][tm4-tm0]:31362\nfinish 554 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28114\n555----rcs.size():5[tm0:1507941061577532,tm1:1507941061578939,tm2:1507941061609255(30316),tm3:1507941061609467(30528),tm4:1507941061609514(30575)]****[tm4-tm0]:31982\nfinish 555 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27416\n556----rcs.size():5[tm0:1507941061640017,tm1:1507941061641421,tm2:1507941061671017(29596),tm3:1507941061671234(29813),tm4:1507941061671280(29859)][tm4-tm0]:31263\nfinish 556 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27594\n557----rcs.size():5[tm0:1507941061701824,tm1:1507941061703381,tm2:1507941061733216(29835),tm3:1507941061733414(30033),tm4:1507941061733475(30094)]****[tm4-tm0]:31651\nfinish 557 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27808\n558----rcs.size():5[tm0:1507941061766358,tm1:1507941061767792,tm2:1507941061797329(29537),tm3:1507941061797540(29748),tm4:1507941061797585(29793)][tm4-tm0]:31227\nfinish 558 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27689\n559----rcs.size():5[tm0:1507941061827415,tm1:1507941061828740,tm2:1507941061858789(30049),tm3:1507941061859008(30268),tm4:1507941061859052(30312)]****[tm4-tm0]:31637\nfinish 559 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26760\n560----rcs.size():4[tm0:1507941061889830,tm1:1507941061891304,tm2:1507941061919457(28153),tm3:1507941061919650(28346),tm4:1507941061919674(28370)][tm4-tm0]:29844\nfinish 560 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27076\n561----rcs.size():4[tm0:1507941061950560,tm1:1507941061951899,tm2:1507941061980536(28637),tm3:1507941061980674(28775),tm4:1507941061980712(28813)][tm4-tm0]:30152\nfinish 561 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26873\n562----rcs.size():4[tm0:1507941062012261,tm1:1507941062013660,tm2:1507941062042159(28499),tm3:1507941062042313(28653),tm4:1507941062042353(28693)][tm4-tm0]:30092\nfinish 562 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27058\n563----rcs.size():4[tm0:1507941062074188,tm1:1507941062075569,tm2:1507941062104103(28534),tm3:1507941062104273(28704),tm4:1507941062104403(28834)][tm4-tm0]:30215\nfinish 563 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27326\n564----rcs.size():4[tm0:1507941062135648,tm1:1507941062137099,tm2:1507941062166265(29166),tm3:1507941062166404(29305),tm4:1507941062166443(29344)][tm4-tm0]:30795\nfinish 564 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26941\n565----rcs.size():4[tm0:1507941062198215,tm1:1507941062199543,tm2:1507941062228126(28583),tm3:1507941062228266(28723),tm4:1507941062228292(28749)][tm4-tm0]:30077\nfinish 565 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26870\n566----rcs.size():4[tm0:1507941062259570,tm1:1507941062260973,tm2:1507941062289595(28622),tm3:1507941062289752(28779),tm4:1507941062289790(28817)][tm4-tm0]:30220\nfinish 566 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27045\n567----rcs.size():4[tm0:1507941062321255,tm1:1507941062322868,tm2:1507941062352068(29200),tm3:1507941062352221(29353),tm4:1507941062352260(29392)][tm4-tm0]:31005\nfinish 567 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27388\n568----rcs.size():4[tm0:1507941062383507,tm1:1507941062384829,tm2:1507941062414268(29439),tm3:1507941062414409(29580),tm4:1507941062414449(29620)][tm4-tm0]:30942\nfinish 568 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26628\n569----rcs.size():4[tm0:1507941062445766,tm1:1507941062447051,tm2:1507941062475171(28120),tm3:1507941062475341(28290),tm4:1507941062475382(28331)][tm4-tm0]:29616\nfinish 569 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26385\n570----rcs.size():4[tm0:1507941062506769,tm1:1507941062508060,tm2:1507941062536107(28047),tm3:1507941062536277(28217),tm4:1507941062536311(28251)][tm4-tm0]:29542\nfinish 570 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27168\n571----rcs.size():4[tm0:1507941062567392,tm1:1507941062568736,tm2:1507941062597991(29255),tm3:1507941062598165(29429),tm4:1507941062598213(29477)][tm4-tm0]:30821\nfinish 571 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27405\n572----rcs.size():4[tm0:1507941062630601,tm1:1507941062632010,tm2:1507941062661491(29481),tm3:1507941062661653(29643),tm4:1507941062661687(29677)][tm4-tm0]:31086\nfinish 572 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26846\n573----rcs.size():4[tm0:1507941062692598,tm1:1507941062693949,tm2:1507941062722887(28938),tm3:1507941062723033(29084),tm4:1507941062723072(29123)][tm4-tm0]:30474\nfinish 573 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26344\n574----rcs.size():3[tm0:1507941062753629,tm1:1507941062755122,tm2:1507941062782890(27768),tm3:1507941062783042(27920),tm4:1507941062783069(27947)][tm4-tm0]:29440\nfinish 574 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26070\n575----rcs.size():3[tm0:1507941062813164,tm1:1507941062813716,tm2:1507941062840277(26561),tm3:1507941062840387(26671),tm4:1507941062840417(26701)][tm4-tm0]:27253\nfinish 575 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26280\n576----rcs.size():3[tm0:1507941062873796,tm1:1507941062875183,tm2:1507941062902798(27615),tm3:1507941062902909(27726),tm4:1507941062902938(27755)][tm4-tm0]:29142\nfinish 576 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26225\n577----rcs.size():3[tm0:1507941062935956,tm1:1507941062936507,tm2:1507941062963312(26805),tm3:1507941062963434(26927),tm4:1507941062963455(26948)][tm4-tm0]:27499\nfinish 577 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26418\n578----rcs.size():3[tm0:1507941062998814,tm1:1507941063000225,tm2:1507941063028167(27942),tm3:1507941063028315(28090),tm4:1507941063028344(28119)][tm4-tm0]:29530\nfinish 578 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26450\n579----rcs.size():3[tm0:1507941063059374,tm1:1507941063060776,tm2:1507941063088606(27830),tm3:1507941063088735(27959),tm4:1507941063088764(27988)][tm4-tm0]:29390\nfinish 579 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26383\n580----rcs.size():3[tm0:1507941063119636,tm1:1507941063121015,tm2:1507941063149073(28058),tm3:1507941063149198(28183),tm4:1507941063149231(28216)][tm4-tm0]:29595\nfinish 580 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26712\n581----rcs.size():3[tm0:1507941063180413,tm1:1507941063181809,tm2:1507941063210179(28370),tm3:1507941063210305(28496),tm4:1507941063210337(28528)][tm4-tm0]:29924\nfinish 581 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26589\n582----rcs.size():3[tm0:1507941063241842,tm1:1507941063243234,tm2:1507941063271300(28066),tm3:1507941063271428(28194),tm4:1507941063271527(28293)][tm4-tm0]:29685\nfinish 582 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26406\n583----rcs.size():3[tm0:1507941063306849,tm1:1507941063308199,tm2:1507941063336183(27984),tm3:1507941063336327(28128),tm4:1507941063336349(28150)][tm4-tm0]:29500\nfinish 583 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26722\n584----rcs.size():3[tm0:1507941063366274,tm1:1507941063367589,tm2:1507941063395823(28234),tm3:1507941063395956(28367),tm4:1507941063395979(28390)][tm4-tm0]:29705\nfinish 584 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26515\n585----rcs.size():3[tm0:1507941063426740,tm1:1507941063428212,tm2:1507941063456292(28080),tm3:1507941063456427(28215),tm4:1507941063456463(28251)][tm4-tm0]:29723\nfinish 585 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26381\n586----rcs.size():3[tm0:1507941063487341,tm1:1507941063488957,tm2:1507941063517023(28066),tm3:1507941063517185(28228),tm4:1507941063517218(28261)][tm4-tm0]:29877\nfinish 586 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26819\n587----rcs.size():3[tm0:1507941063552067,tm1:1507941063553579,tm2:1507941063582410(28831),tm3:1507941063582534(28955),tm4:1507941063582643(29064)][tm4-tm0]:30576\nfinish 587 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26697\n588----rcs.size():3[tm0:1507941063615851,tm1:1507941063617219,tm2:1507941063645671(28452),tm3:1507941063645807(28588),tm4:1507941063645840(28621)][tm4-tm0]:29989\nfinish 588 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26668\n589----rcs.size():3[tm0:1507941063677289,tm1:1507941063678708,tm2:1507941063707175(28467),tm3:1507941063707313(28605),tm4:1507941063707346(28638)][tm4-tm0]:30057\nfinish 589 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26576\n590----rcs.size():3[tm0:1507941063741776,tm1:1507941063743233,tm2:1507941063771640(28407),tm3:1507941063771768(28535),tm4:1507941063771808(28575)][tm4-tm0]:30032\nfinish 590 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27161\n591----rcs.size():3[tm0:1507941063803486,tm1:1507941063805017,tm2:1507941063833830(28813),tm3:1507941063833971(28954),tm4:1507941063834009(28992)][tm4-tm0]:30523\nfinish 591 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26582\n592----rcs.size():3[tm0:1507941063869256,tm1:1507941063870592,tm2:1507941063899318(28726),tm3:1507941063899443(28851),tm4:1507941063899477(28885)][tm4-tm0]:30221\nfinish 592 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26433\n593----rcs.size():3[tm0:1507941063935253,tm1:1507941063936651,tm2:1507941063964880(28229),tm3:1507941063965006(28355),tm4:1507941063965039(28388)][tm4-tm0]:29786\nfinish 593 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26657\n594----rcs.size():3[tm0:1507941063996490,tm1:1507941063997933,tm2:1507941064026048(28115),tm3:1507941064026186(28253),tm4:1507941064026220(28287)][tm4-tm0]:29730\nfinish 594 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27036\n595----rcs.size():3[tm0:1507941064057604,tm1:1507941064059016,tm2:1507941064087542(28526),tm3:1507941064087685(28669),tm4:1507941064087720(28704)][tm4-tm0]:30116\nfinish 595 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27069\n596----rcs.size():3[tm0:1507941064120104,tm1:1507941064121697,tm2:1507941064150423(28726),tm3:1507941064150576(28879),tm4:1507941064150612(28915)][tm4-tm0]:30508\nfinish 596 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27575\n597----rcs.size():3[tm0:1507941064182306,tm1:1507941064183737,tm2:1507941064213036(29299),tm3:1507941064213174(29437),tm4:1507941064213211(29474)][tm4-tm0]:30905\nfinish 597 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27354\n598----rcs.size():3[tm0:1507941064244866,tm1:1507941064246311,tm2:1507941064275466(29155),tm3:1507941064275595(29284),tm4:1507941064275631(29320)][tm4-tm0]:30765\nfinish 598 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27386\n599----rcs.size():3[tm0:1507941064309728,tm1:1507941064311154,tm2:1507941064341244(30090),tm3:1507941064341389(30235),tm4:1507941064341428(30274)]****[tm4-tm0]:31700\nfinish 599 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27160\n600----rcs.size():3[tm0:1507941064375729,tm1:1507941064377125,tm2:1507941064405940(28815),tm3:1507941064406069(28944),tm4:1507941064406109(28984)][tm4-tm0]:30380\nfinish 600 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27086\n601----rcs.size():3[tm0:1507941064436005,tm1:1507941064437388,tm2:1507941064466413(29025),tm3:1507941064466544(29156),tm4:1507941064466580(29192)][tm4-tm0]:30575\nfinish 601 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27819\n602----rcs.size():3[tm0:1507941064497253,tm1:1507941064498652,tm2:1507941064528430(29778),tm3:1507941064528568(29916),tm4:1507941064528606(29954)][tm4-tm0]:31353\nfinish 602 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27149\n603----rcs.size():3[tm0:1507941064559528,tm1:1507941064561026,tm2:1507941064590465(29439),tm3:1507941064590613(29587),tm4:1507941064590648(29622)][tm4-tm0]:31120\nfinish 603 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27296\n604----rcs.size():3[tm0:1507941064622221,tm1:1507941064623695,tm2:1507941064653210(29515),tm3:1507941064653340(29645),tm4:1507941064653375(29680)][tm4-tm0]:31154\nfinish 604 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27294\n605----rcs.size():3[tm0:1507941064689078,tm1:1507941064690449,tm2:1507941064719396(28947),tm3:1507941064719525(29076),tm4:1507941064719555(29106)][tm4-tm0]:30477\nfinish 605 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27396\n606----rcs.size():2[tm0:1507941064752495,tm1:1507941064753899,tm2:1507941064784009(30110),tm3:1507941064784136(30237),tm4:1507941064784161(30262)]****[tm4-tm0]:31666\nfinish 606 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27335\n607----rcs.size():2[tm0:1507941064818524,tm1:1507941064819821,tm2:1507941064849600(29779),tm3:1507941064849681(29860),tm4:1507941064849708(29887)][tm4-tm0]:31184\nfinish 607 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28041\n608----rcs.size():2[tm0:1507941064881379,tm1:1507941064882764,tm2:1507941064913559(30795),tm3:1507941064913657(30893),tm4:1507941064913682(30918)]****[tm4-tm0]:32303\nfinish 608 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27819\n609----rcs.size():2[tm0:1507941064944420,tm1:1507941064945764,tm2:1507941064976507(30743),tm3:1507941064976620(30856),tm4:1507941064976706(30942)]****[tm4-tm0]:32286\nfinish 609 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27759\n610----rcs.size():2[tm0:1507941065011566,tm1:1507941065013114,tm2:1507941065043776(30662),tm3:1507941065043871(30757),tm4:1507941065043889(30775)]****[tm4-tm0]:32323\nfinish 610 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28000\n611----rcs.size():2[tm0:1507941065074774,tm1:1507941065076167,tm2:1507941065107090(30923),tm3:1507941065107202(31035),tm4:1507941065107310(31143)]****[tm4-tm0]:32536\nfinish 611 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27904\n612----rcs.size():2[tm0:1507941065138194,tm1:1507941065139658,tm2:1507941065170957(31299),tm3:1507941065171062(31404),tm4:1507941065171090(31432)]****[tm4-tm0]:32896\nfinish 612 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28224\n613----rcs.size():2[tm0:1507941065202568,tm1:1507941065204067,tm2:1507941065235668(31601),tm3:1507941065235766(31699),tm4:1507941065235793(31726)]****[tm4-tm0]:33225\nfinish 613 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28448\n614----rcs.size():2[tm0:1507941065266792,tm1:1507941065268186,tm2:1507941065300576(32390),tm3:1507941065300658(32472),tm4:1507941065300686(32500)]****[tm4-tm0]:33894\nfinish 614 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28406\n615----rcs.size():2[tm0:1507941065330934,tm1:1507941065331652,tm2:1507941065363169(31517),tm3:1507941065363264(31612),tm4:1507941065363282(31630)]****[tm4-tm0]:32348\nfinish 615 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28027\n616----rcs.size():2[tm0:1507941065393783,tm1:1507941065395149,tm2:1507941065426530(31381),tm3:1507941065426632(31483),tm4:1507941065426662(31513)]****[tm4-tm0]:32879\nfinish 616 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28313\n617----rcs.size():2[tm0:1507941065458714,tm1:1507941065460099,tm2:1507941065491495(31396),tm3:1507941065491597(31498),tm4:1507941065491689(31590)]****[tm4-tm0]:32975\nfinish 617 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28480\n618----rcs.size():2[tm0:1507941065525188,tm1:1507941065526599,tm2:1507941065558690(32091),tm3:1507941065558779(32180),tm4:1507941065558873(32274)]****[tm4-tm0]:33685\nfinish 618 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28765\n619----rcs.size():2[tm0:1507941065591718,tm1:1507941065592323,tm2:1507941065625204(32881),tm3:1507941065625294(32971),tm4:1507941065625390(33067)]****[tm4-tm0]:33672\nfinish 619 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27214\n620----rcs.size():1[tm0:1507941065659123,tm1:1507941065659839,tm2:1507941065688329(28490),tm3:1507941065688428(28589),tm4:1507941065688468(28629)][tm4-tm0]:29345\nfinish 620 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28870\n621----rcs.size():2[tm0:1507941065720591,tm1:1507941065722362,tm2:1507941065755886(33524),tm3:1507941065755977(33615),tm4:1507941065756075(33713)]****[tm4-tm0]:35484\nfinish 621 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28693\n622----rcs.size():2[tm0:1507941065785387,tm1:1507941065785919,tm2:1507941065818874(32955),tm3:1507941065818956(33037),tm4:1507941065818976(33057)]****[tm4-tm0]:33589\nfinish 622 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28521\n623----rcs.size():2[tm0:1507941065848364,tm1:1507941065848904,tm2:1507941065881297(32393),tm3:1507941065881378(32474),tm4:1507941065881398(32494)]****[tm4-tm0]:33034\nfinish 623 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28723\n624----rcs.size():2[tm0:1507941065910994,tm1:1507941065911569,tm2:1507941065944575(33006),tm3:1507941065944658(33089),tm4:1507941065944678(33109)]****[tm4-tm0]:33684\nfinish 624 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28521\n625----rcs.size():2[tm0:1507941065974359,tm1:1507941065974950,tm2:1507941066007218(32268),tm3:1507941066007307(32357),tm4:1507941066007337(32387)]****[tm4-tm0]:32978\nfinish 625 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28684\n626----rcs.size():2[tm0:1507941066041707,tm1:1507941066042278,tm2:1507941066074580(32302),tm3:1507941066074685(32407),tm4:1507941066074714(32436)]****[tm4-tm0]:33007\nfinish 626 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:28290\n627----rcs.size():2[tm0:1507941066104913,tm1:1507941066105605,tm2:1507941066136759(31154),tm3:1507941066136858(31253),tm4:1507941066136878(31273)]****[tm4-tm0]:31965\nfinish 627 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27149\n628----rcs.size():1[tm0:1507941066170650,tm1:1507941066172256,tm2:1507941066201155(28899),tm3:1507941066201256(29000),tm4:1507941066201302(29046)][tm4-tm0]:30652\nfinish 628 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27047\n629----rcs.size():1[tm0:1507941066236969,tm1:1507941066238746,tm2:1507941066267785(29039),tm3:1507941066267875(29129),tm4:1507941066267891(29145)][tm4-tm0]:30922\nfinish 629 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27682\n630----rcs.size():1[tm0:1507941066299552,tm1:1507941066300924,tm2:1507941066330389(29465),tm3:1507941066330461(29537),tm4:1507941066330477(29553)][tm4-tm0]:30925\nfinish 630 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26612\n631----rcs.size():1[tm0:1507941066361661,tm1:1507941066363030,tm2:1507941066391582(28552),tm3:1507941066391634(28604),tm4:1507941066391645(28615)][tm4-tm0]:29984\nfinish 631 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27238\n632----rcs.size():1[tm0:1507941066423446,tm1:1507941066424789,tm2:1507941066453896(29107),tm3:1507941066453955(29166),tm4:1507941066454000(29211)][tm4-tm0]:30554\nfinish 632 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27080\n633----rcs.size():1[tm0:1507941066485732,tm1:1507941066487092,tm2:1507941066516834(29742),tm3:1507941066516907(29815),tm4:1507941066516924(29832)][tm4-tm0]:31192\nfinish 633 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27686\n634----rcs.size():1[tm0:1507941066549045,tm1:1507941066550430,tm2:1507941066580526(30096),tm3:1507941066580598(30168),tm4:1507941066580614(30184)]****[tm4-tm0]:31569\nfinish 634 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27269\n635----rcs.size():1[tm0:1507941066612913,tm1:1507941066614267,tm2:1507941066644002(29735),tm3:1507941066644093(29826),tm4:1507941066644110(29843)][tm4-tm0]:31197\nfinish 635 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:26316\n636----rcs.size():1[tm0:1507941066678517,tm1:1507941066679902,tm2:1507941066708503(28601),tm3:1507941066708593(28691),tm4:1507941066708610(28708)][tm4-tm0]:30093\nfinish 636 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27793\n637----rcs.size():1[tm0:1507941066740930,tm1:1507941066742327,tm2:1507941066772293(29966),tm3:1507941066772383(30056),tm4:1507941066772399(30072)]****[tm4-tm0]:31469\nfinish 637 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27564\n638----rcs.size():1[tm0:1507941066803724,tm1:1507941066805472,tm2:1507941066835213(29741),tm3:1507941066835270(29798),tm4:1507941066835287(29815)][tm4-tm0]:31563\nfinish 638 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27818\n639----rcs.size():1[tm0:1507941066867663,tm1:1507941066869273,tm2:1507941066899518(30245),tm3:1507941066899572(30299),tm4:1507941066899583(30310)]****[tm4-tm0]:31920\nfinish 639 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27918\n640----rcs.size():1[tm0:1507941066930899,tm1:1507941066932255,tm2:1507941066962608(30353),tm3:1507941066962680(30425),tm4:1507941066962697(30442)]****[tm4-tm0]:31798\nfinish 640 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27353\n641----rcs.size():1[tm0:1507941066996791,tm1:1507941066998236,tm2:1507941067028022(29786),tm3:1507941067028079(29843),tm4:1507941067028096(29860)][tm4-tm0]:31305\nfinish 641 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27853\n642----rcs.size():1[tm0:1507941067061039,tm1:1507941067062463,tm2:1507941067093008(30545),tm3:1507941067093067(30604),tm4:1507941067093117(30654)]****[tm4-tm0]:32078\nfinish 642 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27785\n643----rcs.size():1[tm0:1507941067124237,tm1:1507941067125612,tm2:1507941067155499(29887),tm3:1507941067155558(29946),tm4:1507941067155591(29979)][tm4-tm0]:31354\nfinish 643 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27816\n644----rcs.size():1[tm0:1507941067186798,tm1:1507941067188542,tm2:1507941067218588(30046),tm3:1507941067218661(30119),tm4:1507941067218678(30136)]****[tm4-tm0]:31880\nfinish 644 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27342\n645----rcs.size():1[tm0:1507941067250998,tm1:1507941067252487,tm2:1507941067282429(29942),tm3:1507941067282487(30000),tm4:1507941067282500(30013)]****[tm4-tm0]:31502\nfinish 645 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:28300\n646----rcs.size():1[tm0:1507941067315781,tm1:1507941067317208,tm2:1507941067348389(31181),tm3:1507941067348479(31271),tm4:1507941067348495(31287)]****[tm4-tm0]:32714\nfinish 646 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27854\n647----rcs.size():1[tm0:1507941067381191,tm1:1507941067382574,tm2:1507941067412773(30199),tm3:1507941067412843(30269),tm4:1507941067412852(30278)]****[tm4-tm0]:31661\nfinish 647 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:27396\n648----rcs.size():1[tm0:1507941067444254,tm1:1507941067445628,tm2:1507941067474703(29075),tm3:1507941067474781(29153),tm4:1507941067474812(29184)][tm4-tm0]:30558\nfinish 648 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:23\n(incpp)call encode cost time:tmd-tmc:27200\n649----rcs.size():1[tm0:1507941067507430,tm1:1507941067508838,tm2:1507941067538218(29380),tm3:1507941067538274(29436),tm4:1507941067538286(29448)][tm4-tm0]:30856\nfinish 649 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:24\n(incpp)call encode cost time:tmd-tmc:26820\n650----rcs.size():1[tm0:1507941067570320,tm1:1507941067572109,tm2:1507941067600542(28433),tm3:1507941067600651(28542),tm4:1507941067600680(28571)][tm4-tm0]:30360\nfinish 650 frame\n651----rcs.size():0[tm0:1507941067631994,tm1:1507941067633385,tm2:1507941067633385(0),tm3:1507941067633393(8),tm4:1507941067633393(8)][tm4-tm0]:1399\nfinish 651 frame\n652----rcs.size():0[tm0:1507941067665961,tm1:1507941067666564,tm2:1507941067666564(0),tm3:1507941067666571(7),tm4:1507941067666572(8)][tm4-tm0]:611\nfinish 652 frame\n653----rcs.size():0[tm0:1507941067699198,tm1:1507941067699733,tm2:1507941067699733(0),tm3:1507941067699741(8),tm4:1507941067699741(8)][tm4-tm0]:543\nfinish 653 frame\n654----rcs.size():0[tm0:1507941067734425,tm1:1507941067735051,tm2:1507941067735051(0),tm3:1507941067735058(7),tm4:1507941067735058(7)][tm4-tm0]:633\nfinish 654 frame\n655----rcs.size():0[tm0:1507941067770390,tm1:1507941067771395,tm2:1507941067771395(0),tm3:1507941067771403(8),tm4:1507941067771403(8)][tm4-tm0]:1013\nfinish 655 frame\n656----rcs.size():0[tm0:1507941067805488,tm1:1507941067806130,tm2:1507941067806130(0),tm3:1507941067806140(10),tm4:1507941067806140(10)][tm4-tm0]:652\nfinish 656 frame\n657----rcs.size():0[tm0:1507941067840692,tm1:1507941067841219,tm2:1507941067841219(0),tm3:1507941067841227(8),tm4:1507941067841227(8)][tm4-tm0]:535\nfinish 657 frame\n658----rcs.size():0[tm0:1507941067875490,tm1:1507941067876091,tm2:1507941067876091(0),tm3:1507941067876099(8),tm4:1507941067876099(8)][tm4-tm0]:609\nfinish 658 frame\n659----rcs.size():0[tm0:1507941067910528,tm1:1507941067911263,tm2:1507941067911263(0),tm3:1507941067911269(6),tm4:1507941067911270(7)][tm4-tm0]:742\nfinish 659 frame\n660----rcs.size():0[tm0:1507941067945528,tm1:1507941067946176,tm2:1507941067946176(0),tm3:1507941067946183(7),tm4:1507941067946183(7)][tm4-tm0]:655\nfinish 660 frame\n661----rcs.size():0[tm0:1507941067981507,tm1:1507941067982167,tm2:1507941067982167(0),tm3:1507941067982174(7),tm4:1507941067982175(8)][tm4-tm0]:668\nfinish 661 frame\n662----rcs.size():0[tm0:1507941068016509,tm1:1507941068017235,tm2:1507941068017235(0),tm3:1507941068017242(7),tm4:1507941068017242(7)][tm4-tm0]:733\nfinish 662 frame\n663----rcs.size():0[tm0:1507941068051772,tm1:1507941068052457,tm2:1507941068052457(0),tm3:1507941068052464(7),tm4:1507941068052464(7)][tm4-tm0]:692\nfinish 663 frame\n664----rcs.size():0[tm0:1507941068086590,tm1:1507941068087347,tm2:1507941068087347(0),tm3:1507941068087372(25),tm4:1507941068087372(25)][tm4-tm0]:782\nfinish 664 frame\n665----rcs.size():0[tm0:1507941068124200,tm1:1507941068124882,tm2:1507941068124882(0),tm3:1507941068124889(7),tm4:1507941068124889(7)][tm4-tm0]:689\nfinish 665 frame\n666----rcs.size():0[tm0:1507941068160367,tm1:1507941068161045,tm2:1507941068161045(0),tm3:1507941068161051(6),tm4:1507941068161051(6)][tm4-tm0]:684\nfinish 666 frame\n667----rcs.size():0[tm0:1507941068195180,tm1:1507941068195933,tm2:1507941068195933(0),tm3:1507941068195940(7),tm4:1507941068195940(7)][tm4-tm0]:760\nfinish 667 frame\n668----rcs.size():0[tm0:1507941068231214,tm1:1507941068231860,tm2:1507941068231860(0),tm3:1507941068231866(6),tm4:1507941068231867(7)][tm4-tm0]:653\nfinish 668 frame\n669----rcs.size():0[tm0:1507941068266700,tm1:1507941068267297,tm2:1507941068267297(0),tm3:1507941068267303(6),tm4:1507941068267304(7)][tm4-tm0]:604\nfinish 669 frame\n670----rcs.size():0[tm0:1507941068302154,tm1:1507941068302694,tm2:1507941068302694(0),tm3:1507941068302700(6),tm4:1507941068302701(7)][tm4-tm0]:547\nfinish 670 frame\n671----rcs.size():0[tm0:1507941068339658,tm1:1507941068340320,tm2:1507941068340320(0),tm3:1507941068340327(7),tm4:1507941068340327(7)][tm4-tm0]:669\nfinish 671 frame\n672----rcs.size():0[tm0:1507941068375275,tm1:1507941068375834,tm2:1507941068375834(0),tm3:1507941068375841(7),tm4:1507941068375841(7)][tm4-tm0]:566\nfinish 672 frame\n673----rcs.size():0[tm0:1507941068410779,tm1:1507941068411501,tm2:1507941068411501(0),tm3:1507941068411508(7),tm4:1507941068411508(7)][tm4-tm0]:729\nfinish 673 frame\n674----rcs.size():0[tm0:1507941068446159,tm1:1507941068446824,tm2:1507941068446824(0),tm3:1507941068446830(6),tm4:1507941068446830(6)][tm4-tm0]:671\nfinish 674 frame\n675----rcs.size():0[tm0:1507941068481221,tm1:1507941068481741,tm2:1507941068481742(1),tm3:1507941068481748(7),tm4:1507941068481748(7)][tm4-tm0]:527\nfinish 675 frame\n676----rcs.size():0[tm0:1507941068515716,tm1:1507941068516293,tm2:1507941068516293(0),tm3:1507941068516299(6),tm4:1507941068516299(6)][tm4-tm0]:583\nfinish 676 frame\n677----rcs.size():0[tm0:1507941068550913,tm1:1507941068551474,tm2:1507941068551474(0),tm3:1507941068551480(6),tm4:1507941068551480(6)][tm4-tm0]:567\nfinish 677 frame\n678----rcs.size():0[tm0:1507941068590037,tm1:1507941068590689,tm2:1507941068590690(1),tm3:1507941068590696(7),tm4:1507941068590696(7)][tm4-tm0]:659\nfinish 678 frame\n679----rcs.size():0[tm0:1507941068625183,tm1:1507941068625679,tm2:1507941068625679(0),tm3:1507941068625686(7),tm4:1507941068625686(7)][tm4-tm0]:503\nfinish 679 frame\n"
  },
  {
    "path": "logn20.txt",
    "content": "hahahah0\nhahahah1\nhahahah2\nprocess image cost time:1\n_create_network\nbatch_norm_fn\nbatch_norm_fn\n('feature dimensionality: ', 128)\nbatch_norm_fn\nhahahah\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:963\n(incpp)call encode cost time:tmd-tmc:1053045\n1----rcs.size():0[tm0:1507940934430047,tm1:1507940934435754,tm2:1507940934435754(0),tm3:1507940934435762(8),tm4:1507940934435762(8)][tm4-tm0]:5715\nfinish 1 frame\n2----rcs.size():0[tm0:1507940934486848,tm1:1507940934488444,tm2:1507940934488444(0),tm3:1507940934488446(2),tm4:1507940934488446(2)][tm4-tm0]:1598\nfinish 2 frame\n3----rcs.size():0[tm0:1507940934529762,tm1:1507940934530410,tm2:1507940934530410(0),tm3:1507940934530413(3),tm4:1507940934530413(3)][tm4-tm0]:651\nfinish 3 frame\n4----rcs.size():0[tm0:1507940934558436,tm1:1507940934558947,tm2:1507940934558947(0),tm3:1507940934558949(2),tm4:1507940934558950(3)][tm4-tm0]:514\nfinish 4 frame\n5----rcs.size():0[tm0:1507940934594917,tm1:1507940934595498,tm2:1507940934595498(0),tm3:1507940934595500(2),tm4:1507940934595501(3)][tm4-tm0]:584\nfinish 5 frame\n6----rcs.size():0[tm0:1507940934631359,tm1:1507940934631905,tm2:1507940934631905(0),tm3:1507940934631907(2),tm4:1507940934631907(2)][tm4-tm0]:548\nfinish 6 frame\n7----rcs.size():0[tm0:1507940934674166,tm1:1507940934674894,tm2:1507940934674894(0),tm3:1507940934674896(2),tm4:1507940934674897(3)][tm4-tm0]:731\nfinish 7 frame\n8----rcs.size():0[tm0:1507940934710071,tm1:1507940934710599,tm2:1507940934710599(0),tm3:1507940934710601(2),tm4:1507940934710602(3)][tm4-tm0]:531\nfinish 8 frame\n9----rcs.size():0[tm0:1507940934745149,tm1:1507940934745694,tm2:1507940934745694(0),tm3:1507940934745696(2),tm4:1507940934745696(2)][tm4-tm0]:547\nfinish 9 frame\n10----rcs.size():0[tm0:1507940934781832,tm1:1507940934782361,tm2:1507940934782361(0),tm3:1507940934782363(2),tm4:1507940934782363(2)][tm4-tm0]:531\nfinish 10 frame\n11----rcs.size():0[tm0:1507940934815817,tm1:1507940934816354,tm2:1507940934816354(0),tm3:1507940934816356(2),tm4:1507940934816356(2)][tm4-tm0]:539\nfinish 11 frame\n12----rcs.size():0[tm0:1507940934850533,tm1:1507940934851030,tm2:1507940934851030(0),tm3:1507940934851032(2),tm4:1507940934851032(2)][tm4-tm0]:499\nfinish 12 frame\n13----rcs.size():0[tm0:1507940934885128,tm1:1507940934885675,tm2:1507940934885675(0),tm3:1507940934885677(2),tm4:1507940934885678(3)][tm4-tm0]:550\nfinish 13 frame\n14----rcs.size():0[tm0:1507940934920198,tm1:1507940934920731,tm2:1507940934920731(0),tm3:1507940934920733(2),tm4:1507940934920733(2)][tm4-tm0]:535\nfinish 14 frame\n15----rcs.size():0[tm0:1507940934954774,tm1:1507940934955351,tm2:1507940934955351(0),tm3:1507940934955353(2),tm4:1507940934955353(2)][tm4-tm0]:579\nfinish 15 frame\n16----rcs.size():0[tm0:1507940934989958,tm1:1507940934990485,tm2:1507940934990485(0),tm3:1507940934990487(2),tm4:1507940934990487(2)][tm4-tm0]:529\nfinish 16 frame\n17----rcs.size():0[tm0:1507940935024260,tm1:1507940935024775,tm2:1507940935024775(0),tm3:1507940935024778(3),tm4:1507940935024778(3)][tm4-tm0]:518\nfinish 17 frame\n18----rcs.size():0[tm0:1507940935060102,tm1:1507940935060656,tm2:1507940935060656(0),tm3:1507940935060658(2),tm4:1507940935060659(3)][tm4-tm0]:557\nfinish 18 frame\n19----rcs.size():0[tm0:1507940935095817,tm1:1507940935096335,tm2:1507940935096335(0),tm3:1507940935096337(2),tm4:1507940935096337(2)][tm4-tm0]:520\nfinish 19 frame\n20----rcs.size():0[tm0:1507940935131041,tm1:1507940935131666,tm2:1507940935131666(0),tm3:1507940935131668(2),tm4:1507940935131668(2)][tm4-tm0]:627\nfinish 20 frame\n21----rcs.size():0[tm0:1507940935165755,tm1:1507940935166307,tm2:1507940935166307(0),tm3:1507940935166309(2),tm4:1507940935166309(2)][tm4-tm0]:554\nfinish 21 frame\n22----rcs.size():0[tm0:1507940935200871,tm1:1507940935201456,tm2:1507940935201456(0),tm3:1507940935201458(2),tm4:1507940935201458(2)][tm4-tm0]:587\nfinish 22 frame\n23----rcs.size():0[tm0:1507940935235779,tm1:1507940935236320,tm2:1507940935236320(0),tm3:1507940935236322(2),tm4:1507940935236322(2)][tm4-tm0]:543\nfinish 23 frame\n24----rcs.size():0[tm0:1507940935270596,tm1:1507940935271111,tm2:1507940935271112(1),tm3:1507940935271114(3),tm4:1507940935271114(3)][tm4-tm0]:518\nfinish 24 frame\n25----rcs.size():0[tm0:1507940935305608,tm1:1507940935306146,tm2:1507940935306146(0),tm3:1507940935306148(2),tm4:1507940935306148(2)][tm4-tm0]:540\nfinish 25 frame\n26----rcs.size():0[tm0:1507940935341066,tm1:1507940935341642,tm2:1507940935341643(1),tm3:1507940935341645(3),tm4:1507940935341645(3)][tm4-tm0]:579\nfinish 26 frame\n27----rcs.size():0[tm0:1507940935375930,tm1:1507940935376511,tm2:1507940935376511(0),tm3:1507940935376514(3),tm4:1507940935376514(3)][tm4-tm0]:584\nfinish 27 frame\n28----rcs.size():0[tm0:1507940935411309,tm1:1507940935411863,tm2:1507940935411863(0),tm3:1507940935411865(2),tm4:1507940935411865(2)][tm4-tm0]:556\nfinish 28 frame\n29----rcs.size():0[tm0:1507940935446165,tm1:1507940935446932,tm2:1507940935446932(0),tm3:1507940935446934(2),tm4:1507940935446935(3)][tm4-tm0]:770\nfinish 29 frame\n30----rcs.size():0[tm0:1507940935481776,tm1:1507940935482294,tm2:1507940935482294(0),tm3:1507940935482297(3),tm4:1507940935482297(3)][tm4-tm0]:521\nfinish 30 frame\n31----rcs.size():0[tm0:1507940935516471,tm1:1507940935517026,tm2:1507940935517026(0),tm3:1507940935517028(2),tm4:1507940935517029(3)][tm4-tm0]:558\nfinish 31 frame\n32----rcs.size():0[tm0:1507940935551487,tm1:1507940935552060,tm2:1507940935552060(0),tm3:1507940935552062(2),tm4:1507940935552063(3)][tm4-tm0]:576\nfinish 32 frame\n33----rcs.size():0[tm0:1507940935586387,tm1:1507940935586887,tm2:1507940935586887(0),tm3:1507940935586890(3),tm4:1507940935586890(3)][tm4-tm0]:503\nfinish 33 frame\n34----rcs.size():0[tm0:1507940935621203,tm1:1507940935621721,tm2:1507940935621721(0),tm3:1507940935621723(2),tm4:1507940935621723(2)][tm4-tm0]:520\nfinish 34 frame\n35----rcs.size():0[tm0:1507940935655857,tm1:1507940935656395,tm2:1507940935656395(0),tm3:1507940935656397(2),tm4:1507940935656397(2)][tm4-tm0]:540\nfinish 35 frame\n36----rcs.size():0[tm0:1507940935691344,tm1:1507940935691898,tm2:1507940935691898(0),tm3:1507940935691900(2),tm4:1507940935691900(2)][tm4-tm0]:556\nfinish 36 frame\n37----rcs.size():0[tm0:1507940935726520,tm1:1507940935727036,tm2:1507940935727036(0),tm3:1507940935727038(2),tm4:1507940935727038(2)][tm4-tm0]:518\nfinish 37 frame\n38----rcs.size():0[tm0:1507940935761794,tm1:1507940935762336,tm2:1507940935762336(0),tm3:1507940935762339(3),tm4:1507940935762339(3)][tm4-tm0]:545\nfinish 38 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32571\n39----rcs.size():1[tm0:1507940935796099,tm1:1507940935796945,tm2:1507940935829663(32718),tm3:1507940935829677(32732),tm4:1507940935829677(32732)]****[tm4-tm0]:33578\nfinish 39 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:33097\n40----rcs.size():1[tm0:1507940935860797,tm1:1507940935861442,tm2:1507940935894724(33282),tm3:1507940935894791(33349),tm4:1507940935894791(33349)]****[tm4-tm0]:33994\nfinish 40 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32713\n41----rcs.size():1[tm0:1507940935930823,tm1:1507940935931540,tm2:1507940935964430(32890),tm3:1507940935964446(32906),tm4:1507940935964473(32933)]****[tm4-tm0]:33650\nfinish 41 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:30\n(incpp)call encode cost time:tmd-tmc:32340\n42----rcs.size():1[tm0:1507940935996015,tm1:1507940935996908,tm2:1507940936029378(32470),tm3:1507940936029420(32512),tm4:1507940936029427(32519)]****[tm4-tm0]:33412\nfinish 42 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:30\n(incpp)call encode cost time:tmd-tmc:32644\n43----rcs.size():1[tm0:1507940936061015,tm1:1507940936061642,tm2:1507940936094493(32851),tm3:1507940936094530(32888),tm4:1507940936094537(32895)]****[tm4-tm0]:33522\nfinish 43 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32512\n44----rcs.size():1[tm0:1507940936125332,tm1:1507940936125879,tm2:1507940936158517(32638),tm3:1507940936158537(32658),tm4:1507940936158544(32665)]****[tm4-tm0]:33212\nfinish 44 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:30\n(incpp)call encode cost time:tmd-tmc:32129\n45----rcs.size():1[tm0:1507940936191630,tm1:1507940936192175,tm2:1507940936224472(32297),tm3:1507940936224491(32316),tm4:1507940936224498(32323)]****[tm4-tm0]:32868\nfinish 45 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32493\n46----rcs.size():1[tm0:1507940936255496,tm1:1507940936256043,tm2:1507940936288682(32639),tm3:1507940936288702(32659),tm4:1507940936288709(32666)]****[tm4-tm0]:33213\nfinish 46 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32528\n47----rcs.size():1[tm0:1507940936320603,tm1:1507940936321231,tm2:1507940936353939(32708),tm3:1507940936353960(32729),tm4:1507940936353983(32752)]****[tm4-tm0]:33380\nfinish 47 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32895\n48----rcs.size():1[tm0:1507940936386651,tm1:1507940936387212,tm2:1507940936420265(33053),tm3:1507940936420302(33090),tm4:1507940936420309(33097)]****[tm4-tm0]:33658\nfinish 48 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32518\n49----rcs.size():1[tm0:1507940936455913,tm1:1507940936456471,tm2:1507940936489146(32675),tm3:1507940936489168(32697),tm4:1507940936489192(32721)]****[tm4-tm0]:33279\nfinish 49 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32532\n50----rcs.size():1[tm0:1507940936521576,tm1:1507940936522220,tm2:1507940936554927(32707),tm3:1507940936554966(32746),tm4:1507940936554973(32753)]****[tm4-tm0]:33397\nfinish 50 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32344\n51----rcs.size():1[tm0:1507940936591130,tm1:1507940936591674,tm2:1507940936624190(32516),tm3:1507940936624227(32553),tm4:1507940936624235(32561)]****[tm4-tm0]:33105\nfinish 51 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32394\n52----rcs.size():1[tm0:1507940936659463,tm1:1507940936660087,tm2:1507940936692714(32627),tm3:1507940936692752(32665),tm4:1507940936692759(32672)]****[tm4-tm0]:33296\nfinish 52 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32376\n53----rcs.size():1[tm0:1507940936722726,tm1:1507940936723286,tm2:1507940936755830(32544),tm3:1507940936755851(32565),tm4:1507940936755859(32573)]****[tm4-tm0]:33133\nfinish 53 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32773\n54----rcs.size():1[tm0:1507940936786450,tm1:1507940936787142,tm2:1507940936820248(33106),tm3:1507940936820286(33144),tm4:1507940936820294(33152)]****[tm4-tm0]:33844\nfinish 54 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32656\n55----rcs.size():1[tm0:1507940936851726,tm1:1507940936852374,tm2:1507940936885226(32852),tm3:1507940936885249(32875),tm4:1507940936885255(32881)]****[tm4-tm0]:33529\nfinish 55 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:30\n(incpp)call encode cost time:tmd-tmc:32347\n56----rcs.size():1[tm0:1507940936916309,tm1:1507940936916903,tm2:1507940936949418(32515),tm3:1507940936949440(32537),tm4:1507940936949449(32546)]****[tm4-tm0]:33140\nfinish 56 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:31\n(incpp)call encode cost time:tmd-tmc:32433\n57----rcs.size():1[tm0:1507940936983081,tm1:1507940936983640,tm2:1507940937016239(32599),tm3:1507940937016261(32621),tm4:1507940937016284(32644)]****[tm4-tm0]:33203\nfinish 57 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34662\n58----rcs.size():1[tm0:1507940937047948,tm1:1507940937048517,tm2:1507940937083344(34827),tm3:1507940937083366(34849),tm4:1507940937083373(34856)]****[tm4-tm0]:35425\nfinish 58 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34557\n59----rcs.size():1[tm0:1507940937114987,tm1:1507940937115481,tm2:1507940937150210(34729),tm3:1507940937150251(34770),tm4:1507940937150259(34778)]****[tm4-tm0]:35272\nfinish 59 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34674\n60----rcs.size():1[tm0:1507940937181855,tm1:1507940937182437,tm2:1507940937217264(34827),tm3:1507940937217287(34850),tm4:1507940937217294(34857)]****[tm4-tm0]:35439\nfinish 60 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34597\n61----rcs.size():1[tm0:1507940937253549,tm1:1507940937254125,tm2:1507940937288881(34756),tm3:1507940937288904(34779),tm4:1507940937288912(34787)]****[tm4-tm0]:35363\nfinish 61 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34749\n62----rcs.size():1[tm0:1507940937323865,tm1:1507940937324548,tm2:1507940937359467(34919),tm3:1507940937359491(34943),tm4:1507940937359508(34960)]****[tm4-tm0]:35643\nfinish 62 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:34645\n63----rcs.size():1[tm0:1507940937391214,tm1:1507940937391756,tm2:1507940937426552(34796),tm3:1507940937426574(34818),tm4:1507940937426581(34825)]****[tm4-tm0]:35367\nfinish 63 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35069\n64----rcs.size():1[tm0:1507940937461009,tm1:1507940937461562,tm2:1507940937496799(35237),tm3:1507940937496821(35259),tm4:1507940937496827(35265)]****[tm4-tm0]:35818\nfinish 64 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34637\n65----rcs.size():1[tm0:1507940937527088,tm1:1507940937527677,tm2:1507940937562490(34813),tm3:1507940937562514(34837),tm4:1507940937562522(34845)]****[tm4-tm0]:35434\nfinish 65 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:34906\n66----rcs.size():1[tm0:1507940937593981,tm1:1507940937594543,tm2:1507940937629651(35108),tm3:1507940937629675(35132),tm4:1507940937629682(35139)]****[tm4-tm0]:35701\nfinish 66 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34753\n67----rcs.size():1[tm0:1507940937659811,tm1:1507940937660303,tm2:1507940937695284(34981),tm3:1507940937695309(35006),tm4:1507940937695318(35015)]****[tm4-tm0]:35507\nfinish 67 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35121\n68----rcs.size():1[tm0:1507940937725906,tm1:1507940937726460,tm2:1507940937761804(35344),tm3:1507940937761828(35368),tm4:1507940937761835(35375)]****[tm4-tm0]:35929\nfinish 68 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34874\n69----rcs.size():1[tm0:1507940937792134,tm1:1507940937792676,tm2:1507940937827769(35093),tm3:1507940937827810(35134),tm4:1507940937827817(35141)]****[tm4-tm0]:35683\nfinish 69 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34524\n70----rcs.size():1[tm0:1507940937862301,tm1:1507940937863185,tm2:1507940937897908(34723),tm3:1507940937897931(34746),tm4:1507940937897938(34753)]****[tm4-tm0]:35637\nfinish 70 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35029\n71----rcs.size():1[tm0:1507940937929655,tm1:1507940937930277,tm2:1507940937965543(35266),tm3:1507940937965566(35289),tm4:1507940937965573(35296)]****[tm4-tm0]:35918\nfinish 71 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:34892\n72----rcs.size():1[tm0:1507940937995718,tm1:1507940937996523,tm2:1507940938031597(35074),tm3:1507940938031622(35099),tm4:1507940938031645(35122)]****[tm4-tm0]:35927\nfinish 72 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34864\n73----rcs.size():1[tm0:1507940938062732,tm1:1507940938063471,tm2:1507940938098567(35096),tm3:1507940938098592(35121),tm4:1507940938098612(35141)]****[tm4-tm0]:35880\nfinish 73 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34587\n74----rcs.size():2[tm0:1507940938130178,tm1:1507940938130801,tm2:1507940938165596(34795),tm3:1507940938165626(34825),tm4:1507940938165634(34833)]****[tm4-tm0]:35456\nfinish 74 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34642\n75----rcs.size():2[tm0:1507940938197029,tm1:1507940938197626,tm2:1507940938232435(34809),tm3:1507940938232470(34844),tm4:1507940938232478(34852)]****[tm4-tm0]:35449\nfinish 75 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34623\n76----rcs.size():2[tm0:1507940938263218,tm1:1507940938263863,tm2:1507940938298655(34792),tm3:1507940938298724(34861),tm4:1507940938298742(34879)]****[tm4-tm0]:35524\nfinish 76 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:34731\n77----rcs.size():2[tm0:1507940938330013,tm1:1507940938330638,tm2:1507940938365527(34889),tm3:1507940938365580(34942),tm4:1507940938365593(34955)]****[tm4-tm0]:35580\nfinish 77 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34801\n78----rcs.size():2[tm0:1507940938397180,tm1:1507940938397741,tm2:1507940938432722(34981),tm3:1507940938432776(35035),tm4:1507940938432787(35046)]****[tm4-tm0]:35607\nfinish 78 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34834\n79----rcs.size():2[tm0:1507940938463984,tm1:1507940938464567,tm2:1507940938499563(34996),tm3:1507940938499601(35034),tm4:1507940938499634(35067)]****[tm4-tm0]:35650\nfinish 79 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34873\n80----rcs.size():2[tm0:1507940938530932,tm1:1507940938531535,tm2:1507940938566571(35036),tm3:1507940938566625(35090),tm4:1507940938566638(35103)]****[tm4-tm0]:35706\nfinish 80 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35044\n81----rcs.size():2[tm0:1507940938598151,tm1:1507940938598682,tm2:1507940938633895(35213),tm3:1507940938633932(35250),tm4:1507940938633945(35263)]****[tm4-tm0]:35794\nfinish 81 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35187\n82----rcs.size():2[tm0:1507940938665056,tm1:1507940938665657,tm2:1507940938701065(35408),tm3:1507940938701120(35463),tm4:1507940938701132(35475)]****[tm4-tm0]:36076\nfinish 82 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34906\n83----rcs.size():2[tm0:1507940938732553,tm1:1507940938733117,tm2:1507940938768176(35059),tm3:1507940938768214(35097),tm4:1507940938768226(35109)]****[tm4-tm0]:35673\nfinish 83 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35094\n84----rcs.size():2[tm0:1507940938800058,tm1:1507940938800618,tm2:1507940938835946(35328),tm3:1507940938836003(35385),tm4:1507940938836015(35397)]****[tm4-tm0]:35957\nfinish 84 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34647\n85----rcs.size():2[tm0:1507940938867414,tm1:1507940938867959,tm2:1507940938902791(34832),tm3:1507940938902831(34872),tm4:1507940938902844(34885)]****[tm4-tm0]:35430\nfinish 85 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34645\n86----rcs.size():2[tm0:1507940938934143,tm1:1507940938934676,tm2:1507940938969483(34807),tm3:1507940938969524(34848),tm4:1507940938969534(34858)]****[tm4-tm0]:35391\nfinish 86 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34684\n87----rcs.size():2[tm0:1507940939001313,tm1:1507940939001802,tm2:1507940939036690(34888),tm3:1507940939036747(34945),tm4:1507940939036759(34957)]****[tm4-tm0]:35446\nfinish 87 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34868\n88----rcs.size():2[tm0:1507940939068194,tm1:1507940939068718,tm2:1507940939103794(35076),tm3:1507940939103836(35118),tm4:1507940939103869(35151)]****[tm4-tm0]:35675\nfinish 88 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34942\n89----rcs.size():2[tm0:1507940939135674,tm1:1507940939136205,tm2:1507940939171364(35159),tm3:1507940939171418(35213),tm4:1507940939171430(35225)]****[tm4-tm0]:35756\nfinish 89 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34744\n90----rcs.size():2[tm0:1507940939202826,tm1:1507940939203360,tm2:1507940939238274(34914),tm3:1507940939238332(34972),tm4:1507940939238344(34984)]****[tm4-tm0]:35518\nfinish 90 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35150\n91----rcs.size():2[tm0:1507940939271734,tm1:1507940939272325,tm2:1507940939307716(35391),tm3:1507940939307774(35449),tm4:1507940939307787(35462)]****[tm4-tm0]:36053\nfinish 91 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35197\n92----rcs.size():2[tm0:1507940939340621,tm1:1507940939341182,tm2:1507940939376609(35427),tm3:1507940939376681(35499),tm4:1507940939376694(35512)]****[tm4-tm0]:36073\nfinish 92 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34792\n93----rcs.size():2[tm0:1507940939407962,tm1:1507940939408568,tm2:1507940939443568(35000),tm3:1507940939443610(35042),tm4:1507940939443625(35057)]****[tm4-tm0]:35663\nfinish 93 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34658\n94----rcs.size():2[tm0:1507940939474841,tm1:1507940939475392,tm2:1507940939510249(34857),tm3:1507940939510309(34917),tm4:1507940939510323(34931)]****[tm4-tm0]:35482\nfinish 94 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35055\n95----rcs.size():2[tm0:1507940939541883,tm1:1507940939542446,tm2:1507940939577730(35284),tm3:1507940939577791(35345),tm4:1507940939577804(35358)]****[tm4-tm0]:35921\nfinish 95 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34850\n96----rcs.size():2[tm0:1507940939609250,tm1:1507940939609875,tm2:1507940939644991(35116),tm3:1507940939645078(35203),tm4:1507940939645091(35216)]****[tm4-tm0]:35841\nfinish 96 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34753\n97----rcs.size():2[tm0:1507940939676223,tm1:1507940939676853,tm2:1507940939711792(34939),tm3:1507940939711838(34985),tm4:1507940939711852(34999)]****[tm4-tm0]:35629\nfinish 97 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34841\n98----rcs.size():2[tm0:1507940939742607,tm1:1507940939743201,tm2:1507940939778269(35068),tm3:1507940939778315(35114),tm4:1507940939778328(35127)]****[tm4-tm0]:35721\nfinish 98 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35149\n99----rcs.size():2[tm0:1507940939810021,tm1:1507940939810622,tm2:1507940939846018(35396),tm3:1507940939846062(35440),tm4:1507940939846073(35451)]****[tm4-tm0]:36052\nfinish 99 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34973\n100----rcs.size():3[tm0:1507940939876837,tm1:1507940939877397,tm2:1507940939912576(35179),tm3:1507940939912627(35230),tm4:1507940939912641(35244)]****[tm4-tm0]:35804\nfinish 100 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35022\n101----rcs.size():3[tm0:1507940939943088,tm1:1507940939943641,tm2:1507940939978853(35212),tm3:1507940939978909(35268),tm4:1507940939978922(35281)]****[tm4-tm0]:35834\nfinish 101 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35406\n102----rcs.size():3[tm0:1507940940013370,tm1:1507940940013918,tm2:1507940940049508(35590),tm3:1507940940049582(35664),tm4:1507940940049602(35684)]****[tm4-tm0]:36232\nfinish 102 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34895\n103----rcs.size():3[tm0:1507940940080308,tm1:1507940940080884,tm2:1507940940115967(35083),tm3:1507940940116033(35149),tm4:1507940940116052(35168)]****[tm4-tm0]:35744\nfinish 103 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34919\n104----rcs.size():3[tm0:1507940940146742,tm1:1507940940147327,tm2:1507940940182442(35115),tm3:1507940940182499(35172),tm4:1507940940182517(35190)]****[tm4-tm0]:35775\nfinish 104 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34778\n105----rcs.size():3[tm0:1507940940213558,tm1:1507940940214145,tm2:1507940940249100(34955),tm3:1507940940249176(35031),tm4:1507940940249204(35059)]****[tm4-tm0]:35646\nfinish 105 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34755\n106----rcs.size():3[tm0:1507940940280858,tm1:1507940940281481,tm2:1507940940316459(34978),tm3:1507940940316518(35037),tm4:1507940940316534(35053)]****[tm4-tm0]:35676\nfinish 106 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34563\n107----rcs.size():3[tm0:1507940940347567,tm1:1507940940348132,tm2:1507940940382886(34754),tm3:1507940940382946(34814),tm4:1507940940382963(34831)]****[tm4-tm0]:35396\nfinish 107 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34870\n108----rcs.size():3[tm0:1507940940413738,tm1:1507940940414349,tm2:1507940940449403(35054),tm3:1507940940449463(35114),tm4:1507940940449479(35130)]****[tm4-tm0]:35741\nfinish 108 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:34495\n109----rcs.size():3[tm0:1507940940480286,tm1:1507940940480859,tm2:1507940940515518(34659),tm3:1507940940515594(34735),tm4:1507940940515611(34752)]****[tm4-tm0]:35325\nfinish 109 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34970\n110----rcs.size():3[tm0:1507940940546115,tm1:1507940940546679,tm2:1507940940581857(35178),tm3:1507940940581918(35239),tm4:1507940940581935(35256)]****[tm4-tm0]:35820\nfinish 110 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35027\n111----rcs.size():3[tm0:1507940940612610,tm1:1507940940613208,tm2:1507940940648432(35224),tm3:1507940940648511(35303),tm4:1507940940648529(35321)]****[tm4-tm0]:35919\nfinish 111 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35108\n112----rcs.size():3[tm0:1507940940678938,tm1:1507940940679590,tm2:1507940940714990(35400),tm3:1507940940715052(35462),tm4:1507940940715070(35480)]****[tm4-tm0]:36132\nfinish 112 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34974\n113----rcs.size():3[tm0:1507940940748081,tm1:1507940940748719,tm2:1507940940783887(35168),tm3:1507940940783951(35232),tm4:1507940940783969(35250)]****[tm4-tm0]:35888\nfinish 113 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34950\n114----rcs.size():3[tm0:1507940940814499,tm1:1507940940815081,tm2:1507940940850251(35170),tm3:1507940940850330(35249),tm4:1507940940850347(35266)]****[tm4-tm0]:35848\nfinish 114 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34765\n115----rcs.size():3[tm0:1507940940881128,tm1:1507940940881757,tm2:1507940940916709(34952),tm3:1507940940916773(35016),tm4:1507940940916791(35034)]****[tm4-tm0]:35663\nfinish 115 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:34965\n116----rcs.size():2[tm0:1507940940947888,tm1:1507940940948433,tm2:1507940940983616(35183),tm3:1507940940983676(35243),tm4:1507940940983690(35257)]****[tm4-tm0]:35802\nfinish 116 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34924\n117\n117----rcs.size():2[tm0:1507940941018098,tm1:1507940941018682,tm2:1507940941053819(35137),tm3:1507940941053884(35202),tm4:1507940941053899(35217)]****[tm4-tm0]:35801\nfinish 117 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35149\n118----rcs.size():2[tm0:1507940941088760,tm1:1507940941089480,tm2:1507940941124877(35397),tm3:1507940941124926(35446),tm4:1507940941124940(35460)]****[tm4-tm0]:36180\nfinish 118 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35272\n119----rcs.size():2[tm0:1507940941156120,tm1:1507940941156674,tm2:1507940941192200(35526),tm3:1507940941192250(35576),tm4:1507940941192264(35590)]****[tm4-tm0]:36144\nfinish 119 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34991\n120----rcs.size():2[tm0:1507940941223599,tm1:1507940941224151,tm2:1507940941259370(35219),tm3:1507940941259420(35269),tm4:1507940941259434(35283)]****[tm4-tm0]:35835\nfinish 120 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35316\n121----rcs.size():2[tm0:1507940941291480,tm1:1507940941292052,tm2:1507940941327641(35589),tm3:1507940941327692(35640),tm4:1507940941327707(35655)]****[tm4-tm0]:36227\nfinish 121 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35225\n122----rcs.size():2[tm0:1507940941358485,tm1:1507940941359065,tm2:1507940941394527(35462),tm3:1507940941394579(35514),tm4:1507940941394593(35528)]****[tm4-tm0]:36108\nfinish 122 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35058\n123----rcs.size():2[tm0:1507940941425707,tm1:1507940941426305,tm2:1507940941461584(35279),tm3:1507940941461641(35336),tm4:1507940941461656(35351)]****[tm4-tm0]:35949\nfinish 123 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35060\n124----rcs.size():3[tm0:1507940941492106,tm1:1507940941492636,tm2:1507940941527950(35314),tm3:1507940941528024(35388),tm4:1507940941528035(35399)]****[tm4-tm0]:35929\nfinish 124 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34924\n125----rcs.size():3[tm0:1507940941559153,tm1:1507940941559790,tm2:1507940941594912(35122),tm3:1507940941595018(35228),tm4:1507940941595032(35242)]****[tm4-tm0]:35879\nfinish 125 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:34658\n126----rcs.size():3[tm0:1507940941630072,tm1:1507940941630637,tm2:1507940941665503(34866),tm3:1507940941665600(34963),tm4:1507940941665616(34979)]****[tm4-tm0]:35544\nfinish 126 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35040\n127----rcs.size():3[tm0:1507940941697328,tm1:1507940941697874,tm2:1507940941733202(35328),tm3:1507940941733266(35392),tm4:1507940941733315(35441)]****[tm4-tm0]:35987\nfinish 127 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34616\n128----rcs.size():3[tm0:1507940941764238,tm1:1507940941764834,tm2:1507940941799688(34854),tm3:1507940941799750(34916),tm4:1507940941799764(34930)]****[tm4-tm0]:35526\nfinish 128 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34938\n129----rcs.size():3[tm0:1507940941831118,tm1:1507940941831770,tm2:1507940941866943(35173),tm3:1507940941867024(35254),tm4:1507940941867041(35271)]****[tm4-tm0]:35923\nfinish 129 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34989\n130----rcs.size():3[tm0:1507940941898486,tm1:1507940941899072,tm2:1507940941934271(35199),tm3:1507940941934375(35303),tm4:1507940941934393(35321)]****[tm4-tm0]:35907\nfinish 130 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34773\n131----rcs.size():3[tm0:1507940941965545,tm1:1507940941966248,tm2:1507940942001283(35035),tm3:1507940942001364(35116),tm4:1507940942001381(35133)]****[tm4-tm0]:35836\nfinish 131 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34388\n132----rcs.size():3[tm0:1507940942032030,tm1:1507940942032610,tm2:1507940942067192(34582),tm3:1507940942067277(34667),tm4:1507940942067298(34688)]****[tm4-tm0]:35268\nfinish 132 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34799\n133----rcs.size():3[tm0:1507940942097807,tm1:1507940942098374,tm2:1507940942133414(35040),tm3:1507940942133497(35123),tm4:1507940942133510(35136)]****[tm4-tm0]:35703\nfinish 133 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35045\n134----rcs.size():2[tm0:1507940942163963,tm1:1507940942164519,tm2:1507940942199821(35302),tm3:1507940942199913(35394),tm4:1507940942199924(35405)]****[tm4-tm0]:35961\nfinish 134 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35072\n135----rcs.size():2[tm0:1507940942230494,tm1:1507940942231035,tm2:1507940942266411(35376),tm3:1507940942266466(35431),tm4:1507940942266477(35442)]****[tm4-tm0]:35983\nfinish 135 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35066\n136----rcs.size():2[tm0:1507940942298112,tm1:1507940942298659,tm2:1507940942334005(35346),tm3:1507940942334063(35404),tm4:1507940942334104(35445)]****[tm4-tm0]:35992\nfinish 136 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35327\n137----rcs.size():2[tm0:1507940942365922,tm1:1507940942366610,tm2:1507940942402237(35627),tm3:1507940942402318(35708),tm4:1507940942402341(35731)]****[tm4-tm0]:36419\nfinish 137 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35288\n138----rcs.size():2[tm0:1507940942433936,tm1:1507940942434548,tm2:1507940942470208(35660),tm3:1507940942470283(35735),tm4:1507940942470298(35750)]****[tm4-tm0]:36362\nfinish 138 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34994\n139----rcs.size():2[tm0:1507940942502135,tm1:1507940942502695,tm2:1507940942538037(35342),tm3:1507940942538118(35423),tm4:1507940942538132(35437)]****[tm4-tm0]:35997\nfinish 139 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35842\n140----rcs.size():2[tm0:1507940942569504,tm1:1507940942570244,tm2:1507940942606414(36170),tm3:1507940942606474(36230),tm4:1507940942606490(36246)]****[tm4-tm0]:36986\nfinish 140 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35348\n141----rcs.size():2[tm0:1507940942637493,tm1:1507940942638154,tm2:1507940942673877(35723),tm3:1507940942673952(35798),tm4:1507940942673968(35814)]****[tm4-tm0]:36475\nfinish 141 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35238\n142----rcs.size():2[tm0:1507940942705562,tm1:1507940942706135,tm2:1507940942741726(35591),tm3:1507940942741794(35659),tm4:1507940942741817(35682)]****[tm4-tm0]:36255\nfinish 142 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35262\n143----rcs.size():2[tm0:1507940942772935,tm1:1507940942773619,tm2:1507940942809192(35573),tm3:1507940942809269(35650),tm4:1507940942809284(35665)]****[tm4-tm0]:36349\nfinish 143 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35446\n144----rcs.size():3[tm0:1507940942840631,tm1:1507940942841252,tm2:1507940942877037(35785),tm3:1507940942877120(35868),tm4:1507940942877136(35884)]****[tm4-tm0]:36505\nfinish 144 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35171\n145----rcs.size():3[tm0:1507940942908617,tm1:1507940942909144,tm2:1507940942944612(35468),tm3:1507940942944732(35588),tm4:1507940942944743(35599)]****[tm4-tm0]:36126\nfinish 145 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35222\n146----rcs.size():3[tm0:1507940942975417,tm1:1507940942975983,tm2:1507940943011471(35488),tm3:1507940943011594(35611),tm4:1507940943011644(35661)]****[tm4-tm0]:36227\nfinish 146 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35182\n147----rcs.size():4[tm0:1507940943042706,tm1:1507940943043378,tm2:1507940943078849(35471),tm3:1507940943078935(35557),tm4:1507940943078953(35575)]****[tm4-tm0]:36247\nfinish 147 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35221\n148----rcs.size():4[tm0:1507940943110551,tm1:1507940943111086,tm2:1507940943146609(35523),tm3:1507940943146706(35620),tm4:1507940943146758(35672)]****[tm4-tm0]:36207\nfinish 148 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35403\n149----rcs.size():4[tm0:1507940943183665,tm1:1507940943184247,tm2:1507940943219997(35750),tm3:1507940943220077(35830),tm4:1507940943220101(35854)]****[tm4-tm0]:36436\nfinish 149 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35271\n150----rcs.size():4[tm0:1507940943251205,tm1:1507940943251876,tm2:1507940943287458(35582),tm3:1507940943287551(35675),tm4:1507940943287567(35691)]****[tm4-tm0]:36362\nfinish 150 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35277\n151----rcs.size():4[tm0:1507940943318466,tm1:1507940943318987,tm2:1507940943354612(35625),tm3:1507940943354705(35718),tm4:1507940943354722(35735)]****[tm4-tm0]:36256\nfinish 151 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35121\n152----rcs.size():3[tm0:1507940943385469,tm1:1507940943386004,tm2:1507940943421430(35426),tm3:1507940943421544(35540),tm4:1507940943421563(35559)]****[tm4-tm0]:36094\nfinish 152 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35025\n153----rcs.size():3[tm0:1507940943452236,tm1:1507940943452838,tm2:1507940943488219(35381),tm3:1507940943488296(35458),tm4:1507940943488314(35476)]****[tm4-tm0]:36078\nfinish 153 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35349\n154----rcs.size():3[tm0:1507940943518838,tm1:1507940943519402,tm2:1507940943555087(35685),tm3:1507940943555179(35777),tm4:1507940943555197(35795)]****[tm4-tm0]:36359\nfinish 154 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35280\n155----rcs.size():4[tm0:1507940943585916,tm1:1507940943586596,tm2:1507940943622189(35593),tm3:1507940943622276(35680),tm4:1507940943622359(35763)]****[tm4-tm0]:36443\nfinish 155 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35106\n156----rcs.size():5[tm0:1507940943652112,tm1:1507940943652641,tm2:1507940943688045(35404),tm3:1507940943688174(35533),tm4:1507940943688191(35550)]****[tm4-tm0]:36079\nfinish 156 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35154\n157----rcs.size():5[tm0:1507940943721829,tm1:1507940943722403,tm2:1507940943757922(35519),tm3:1507940943758021(35618),tm4:1507940943758047(35644)]****[tm4-tm0]:36218\nfinish 157 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35466\n158----rcs.size():5[tm0:1507940943789428,tm1:1507940943789989,tm2:1507940943825762(35773),tm3:1507940943825877(35888),tm4:1507940943825905(35916)]****[tm4-tm0]:36477\nfinish 158 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35302\n159----rcs.size():5[tm0:1507940943856188,tm1:1507940943856864,tm2:1507940943892496(35632),tm3:1507940943892614(35750),tm4:1507940943892641(35777)]****[tm4-tm0]:36453\nfinish 159 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35413\n160----rcs.size():5[tm0:1507940943923015,tm1:1507940943923653,tm2:1507940943959489(35836),tm3:1507940943959600(35947),tm4:1507940943959677(36024)]****[tm4-tm0]:36662\nfinish 160 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35271\n161----rcs.size():5[tm0:1507940943990673,tm1:1507940943991351,tm2:1507940944026944(35593),tm3:1507940944027061(35710),tm4:1507940944027087(35736)]****[tm4-tm0]:36414\nfinish 161 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35425\n162----rcs.size():5[tm0:1507940944062569,tm1:1507940944063284,tm2:1507940944099046(35762),tm3:1507940944099175(35891),tm4:1507940944099251(35967)]****[tm4-tm0]:36682\nfinish 162 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35443\n163----rcs.size():5[tm0:1507940944129199,tm1:1507940944129877,tm2:1507940944165737(35860),tm3:1507940944165843(35966),tm4:1507940944165923(36046)]****[tm4-tm0]:36724\nfinish 163 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35165\n164----rcs.size():5[tm0:1507940944200724,tm1:1507940944201290,tm2:1507940944236852(35562),tm3:1507940944236951(35661),tm4:1507940944236970(35680)]****[tm4-tm0]:36246\nfinish 164 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35266\n165----rcs.size():5[tm0:1507940944267580,tm1:1507940944268280,tm2:1507940944303932(35652),tm3:1507940944304049(35769),tm4:1507940944304068(35788)]****[tm4-tm0]:36488\nfinish 165 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35235\n166----rcs.size():5[tm0:1507940944333836,tm1:1507940944334406,tm2:1507940944370009(35603),tm3:1507940944370109(35703),tm4:1507940944370129(35723)]****[tm4-tm0]:36293\nfinish 166 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35477\n167----rcs.size():5[tm0:1507940944399962,tm1:1507940944400527,tm2:1507940944436359(35832),tm3:1507940944436480(35953),tm4:1507940944436501(35974)]****[tm4-tm0]:36539\nfinish 167 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35199\n168----rcs.size():5[tm0:1507940944466315,tm1:1507940944466906,tm2:1507940944502477(35571),tm3:1507940944502609(35703),tm4:1507940944502639(35733)]****[tm4-tm0]:36324\nfinish 168 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35650\n169----rcs.size():5[tm0:1507940944533474,tm1:1507940944534037,tm2:1507940944570072(36035),tm3:1507940944570209(36172),tm4:1507940944570238(36201)]****[tm4-tm0]:36764\nfinish 169 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35139\n170----rcs.size():5[tm0:1507940944600202,tm1:1507940944600783,tm2:1507940944636308(35525),tm3:1507940944636430(35647),tm4:1507940944636450(35667)]****[tm4-tm0]:36248\nfinish 170 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35278\n171----rcs.size():5[tm0:1507940944666206,tm1:1507940944666734,tm2:1507940944702396(35662),tm3:1507940944702522(35788),tm4:1507940944702542(35808)]****[tm4-tm0]:36336\nfinish 171 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35609\n172----rcs.size():5[tm0:1507940944734159,tm1:1507940944734699,tm2:1507940944770730(36031),tm3:1507940944770861(36162),tm4:1507940944770953(36254)]****[tm4-tm0]:36794\nfinish 172 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35318\n173----rcs.size():5[tm0:1507940944804164,tm1:1507940944804713,tm2:1507940944840432(35719),tm3:1507940944840549(35836),tm4:1507940944840570(35857)]****[tm4-tm0]:36406\nfinish 173 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35560\n174----rcs.size():5[tm0:1507940944870513,tm1:1507940944871062,tm2:1507940944907077(36015),tm3:1507940944907232(36170),tm4:1507940944907265(36203)]****[tm4-tm0]:36752\nfinish 174 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:35425\n175----rcs.size():5[tm0:1507940944942046,tm1:1507940944942599,tm2:1507940944978447(35848),tm3:1507940944978581(35982),tm4:1507940944978678(36079)]****[tm4-tm0]:36632\nfinish 175 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35608\n176----rcs.size():5[tm0:1507940945010476,tm1:1507940945010996,tm2:1507940945047277(36281),tm3:1507940945047413(36417),tm4:1507940945047445(36449)]****[tm4-tm0]:36969\nfinish 176 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35249\n177----rcs.size():5[tm0:1507940945081357,tm1:1507940945081938,tm2:1507940945117514(35576),tm3:1507940945117667(35729),tm4:1507940945117762(35824)]****[tm4-tm0]:36405\nfinish 177 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35942\n178----rcs.size():5[tm0:1507940945151632,tm1:1507940945152182,tm2:1507940945188710(36528),tm3:1507940945188840(36658),tm4:1507940945188872(36690)]****[tm4-tm0]:37240\nfinish 178 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35450\n179----rcs.size():5[tm0:1507940945223605,tm1:1507940945224171,tm2:1507940945260151(35980),tm3:1507940945260290(36119),tm4:1507940945260322(36151)]****[tm4-tm0]:36717\nfinish 179 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35975\n180----rcs.size():5[tm0:1507940945290512,tm1:1507940945291061,tm2:1507940945327753(36692),tm3:1507940945327880(36819),tm4:1507940945327981(36920)]****[tm4-tm0]:37469\nfinish 180 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36393\n181----rcs.size():5[tm0:1507940945359815,tm1:1507940945360378,tm2:1507940945397260(36882),tm3:1507940945397418(37040),tm4:1507940945397448(37070)]****[tm4-tm0]:37633\nfinish 181 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35527\n182----rcs.size():5[tm0:1507940945431986,tm1:1507940945432556,tm2:1507940945468536(35980),tm3:1507940945468674(36118),tm4:1507940945468695(36139)]****[tm4-tm0]:36709\nfinish 182 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35860\n183----rcs.size():5[tm0:1507940945498465,tm1:1507940945498980,tm2:1507940945535379(36399),tm3:1507940945535509(36529),tm4:1507940945535544(36564)]****[tm4-tm0]:37079\nfinish 183 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35814\n184----rcs.size():6[tm0:1507940945566449,tm1:1507940945567069,tm2:1507940945603368(36299),tm3:1507940945603520(36451),tm4:1507940945603552(36483)]****[tm4-tm0]:37103\nfinish 184 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35793\n185----rcs.size():6[tm0:1507940945638758,tm1:1507940945639410,tm2:1507940945675725(36315),tm3:1507940945675870(36460),tm4:1507940945675901(36491)]****[tm4-tm0]:37143\nfinish 185 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36371\n186----rcs.size():6[tm0:1507940945707200,tm1:1507940945707738,tm2:1507940945744682(36944),tm3:1507940945744846(37108),tm4:1507940945744883(37145)]****[tm4-tm0]:37683\nfinish 186 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36303\n187----rcs.size():6[tm0:1507940945776829,tm1:1507940945778573,tm2:1507940945816309(37736),tm3:1507940945816471(37898),tm4:1507940945816508(37935)]****[tm4-tm0]:39679\nfinish 187 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36338\n188----rcs.size():6[tm0:1507940945848518,tm1:1507940945849926,tm2:1507940945886805(36879),tm3:1507940945886993(37067),tm4:1507940945887113(37187)]****[tm4-tm0]:38595\nfinish 188 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35389\n189----rcs.size():6[tm0:1507940945917515,tm1:1507940945918083,tm2:1507940945954017(35934),tm3:1507940945954211(36128),tm4:1507940945954250(36167)]****[tm4-tm0]:36735\nfinish 189 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36424\n190----rcs.size():6[tm0:1507940945985380,tm1:1507940945986125,tm2:1507940946023092(36967),tm3:1507940946023254(37129),tm4:1507940946023295(37170)]****[tm4-tm0]:37915\nfinish 190 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36318\n191----rcs.size():6[tm0:1507940946054988,tm1:1507940946056461,tm2:1507940946094214(37753),tm3:1507940946094391(37930),tm4:1507940946094417(37956)]****[tm4-tm0]:39429\nfinish 191 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36582\n192----rcs.size():6[tm0:1507940946126350,tm1:1507940946127979,tm2:1507940946165184(37205),tm3:1507940946165366(37387),tm4:1507940946165404(37425)]****[tm4-tm0]:39054\nfinish 192 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36820\n193----rcs.size():6[tm0:1507940946196363,tm1:1507940946197056,tm2:1507940946234475(37419),tm3:1507940946234648(37592),tm4:1507940946234689(37633)]****[tm4-tm0]:38326\nfinish 193 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:36394\n194----rcs.size():6[tm0:1507940946267051,tm1:1507940946268524,tm2:1507940946305465(36941),tm3:1507940946305638(37114),tm4:1507940946305679(37155)]****[tm4-tm0]:38628\nfinish 194 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36349\n195----rcs.size():6[tm0:1507940946336186,tm1:1507940946336836,tm2:1507940946373818(36982),tm3:1507940946373994(37158),tm4:1507940946374034(37198)]****[tm4-tm0]:37848\nfinish 195 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37149\n196----rcs.size():6[tm0:1507940946405861,tm1:1507940946407325,tm2:1507940946445605(38280),tm3:1507940946445767(38442),tm4:1507940946445807(38482)]****[tm4-tm0]:39946\nfinish 196 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36633\n197----rcs.size():6[tm0:1507940946480010,tm1:1507940946481502,tm2:1507940946519254(37752),tm3:1507940946519450(37948),tm4:1507940946519491(37989)]****[tm4-tm0]:39481\nfinish 197 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36390\n198----rcs.size():6[tm0:1507940946551206,tm1:1507940946552565,tm2:1507940946589992(37427),tm3:1507940946590175(37610),tm4:1507940946590306(37741)]****[tm4-tm0]:39100\nfinish 198 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36872\n199----rcs.size():6[tm0:1507940946622122,tm1:1507940946623616,tm2:1507940946661599(37983),tm3:1507940946661799(38183),tm4:1507940946661838(38222)]****[tm4-tm0]:39716\nfinish 199 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36939\n200----rcs.size():6[tm0:1507940946693260,tm1:1507940946694948,tm2:1507940946733284(38336),tm3:1507940946733470(38522),tm4:1507940946733601(38653)]****[tm4-tm0]:40341\nfinish 200 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36999\n201----rcs.size():6[tm0:1507940946763324,tm1:1507940946764757,tm2:1507940946802931(38174),tm3:1507940946803117(38360),tm4:1507940946803170(38413)]****[tm4-tm0]:39846\nfinish 201 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36705\n202----rcs.size():6[tm0:1507940946834336,tm1:1507940946835817,tm2:1507940946873968(38151),tm3:1507940946874165(38348),tm4:1507940946874209(38392)]****[tm4-tm0]:39873\nfinish 202 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37257\n203----rcs.size():6[tm0:1507940946905434,tm1:1507940946906775,tm2:1507940946945242(38467),tm3:1507940946945411(38636),tm4:1507940946945453(38678)]****[tm4-tm0]:40019\nfinish 203 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36898\n204----rcs.size():6[tm0:1507940946976376,tm1:1507940946977982,tm2:1507940947016501(38519),tm3:1507940947016690(38708),tm4:1507940947016734(38752)]****[tm4-tm0]:40358\nfinish 204 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36961\n205----rcs.size():6[tm0:1507940947048413,tm1:1507940947049786,tm2:1507940947088026(38240),tm3:1507940947088215(38429),tm4:1507940947088372(38586)]****[tm4-tm0]:39959\nfinish 205 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36688\n206----rcs.size():6[tm0:1507940947120101,tm1:1507940947121462,tm2:1507940947159621(38159),tm3:1507940947159802(38340),tm4:1507940947159940(38478)]****[tm4-tm0]:39839\nfinish 206 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37580\n207----rcs.size():6[tm0:1507940947190790,tm1:1507940947192186,tm2:1507940947231320(39134),tm3:1507940947231506(39320),tm4:1507940947231644(39458)]****[tm4-tm0]:40854\nfinish 207 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37039\n208----rcs.size():6[tm0:1507940947262524,tm1:1507940947263902,tm2:1507940947302407(38505),tm3:1507940947302603(38701),tm4:1507940947302646(38744)]****[tm4-tm0]:40122\nfinish 208 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36782\n209----rcs.size():6[tm0:1507940947333789,tm1:1507940947335135,tm2:1507940947373455(38320),tm3:1507940947373652(38517),tm4:1507940947373699(38564)]****[tm4-tm0]:39910\nfinish 209 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37315\n210----rcs.size():7[tm0:1507940947404278,tm1:1507940947405684,tm2:1507940947444399(38715),tm3:1507940947444604(38920),tm4:1507940947444632(38948)]****[tm4-tm0]:40354\nfinish 210 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37019\n211----rcs.size():7[tm0:1507940947474901,tm1:1507940947476263,tm2:1507940947515044(38781),tm3:1507940947515290(39027),tm4:1507940947515349(39086)]****[tm4-tm0]:40448\nfinish 211 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37233\n212----rcs.size():7[tm0:1507940947546991,tm1:1507940947548358,tm2:1507940947587284(38926),tm3:1507940947587525(39167),tm4:1507940947587572(39214)]****[tm4-tm0]:40581\nfinish 212 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37245\n213----rcs.size():7[tm0:1507940947620951,tm1:1507940947622354,tm2:1507940947661330(38976),tm3:1507940947661556(39202),tm4:1507940947661607(39253)]****[tm4-tm0]:40656\nfinish 213 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37216\n214----rcs.size():7[tm0:1507940947693247,tm1:1507940947695051,tm2:1507940947734201(39150),tm3:1507940947734434(39383),tm4:1507940947734586(39535)]****[tm4-tm0]:41339\nfinish 214 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37019\n215----rcs.size():7[tm0:1507940947765571,tm1:1507940947766890,tm2:1507940947805719(38829),tm3:1507940947805934(39044),tm4:1507940947805982(39092)]****[tm4-tm0]:40411\nfinish 215 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37525\n216----rcs.size():7[tm0:1507940947837504,tm1:1507940947838825,tm2:1507940947878315(39490),tm3:1507940947878557(39732),tm4:1507940947878605(39780)]****[tm4-tm0]:41101\nfinish 216 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37434\n217----rcs.size():7[tm0:1507940947909461,tm1:1507940947911077,tm2:1507940947950893(39816),tm3:1507940947951109(40032),tm4:1507940947951298(40221)]****[tm4-tm0]:41837\nfinish 217 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37197\n218----rcs.size():7[tm0:1507940947981724,tm1:1507940947983159,tm2:1507940948021829(38670),tm3:1507940948022065(38906),tm4:1507940948022229(39070)]****[tm4-tm0]:40505\nfinish 218 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37458\n219----rcs.size():6[tm0:1507940948055987,tm1:1507940948057337,tm2:1507940948097256(39919),tm3:1507940948097478(40141),tm4:1507940948097622(40285)]****[tm4-tm0]:41635\nfinish 219 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37603\n220----rcs.size():6[tm0:1507940948128018,tm1:1507940948129399,tm2:1507940948169409(40010),tm3:1507940948169629(40230),tm4:1507940948169789(40390)]****[tm4-tm0]:41771\nfinish 220 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37631\n221----rcs.size():6[tm0:1507940948203032,tm1:1507940948204350,tm2:1507940948243740(39390),tm3:1507940948243965(39615),tm4:1507940948244114(39764)]****[tm4-tm0]:41082\nfinish 221 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37846\n222----rcs.size():6[tm0:1507940948274343,tm1:1507940948275664,tm2:1507940948315362(39698),tm3:1507940948315583(39919),tm4:1507940948315735(40071)]****[tm4-tm0]:41392\nfinish 222 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37656\n223----rcs.size():6[tm0:1507940948346235,tm1:1507940948347573,tm2:1507940948387787(40214),tm3:1507940948388026(40453),tm4:1507940948388264(40691)]****[tm4-tm0]:42029\nfinish 223 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37363\n224----rcs.size():6[tm0:1507940948418500,tm1:1507940948419863,tm2:1507940948458903(39040),tm3:1507940948459148(39285),tm4:1507940948459299(39436)]****[tm4-tm0]:40799\nfinish 224 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38521\n225----rcs.size():6[tm0:1507940948490287,tm1:1507940948491681,tm2:1507940948532456(40775),tm3:1507940948532687(41006),tm4:1507940948532848(41167)]****[tm4-tm0]:42561\nfinish 225 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:40304\n226----rcs.size():7[tm0:1507940948564404,tm1:1507940948566342,tm2:1507940948610326(43984),tm3:1507940948610542(44200),tm4:1507940948610573(44231)]****[tm4-tm0]:46169\nfinish 226 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37993\n227----rcs.size():7[tm0:1507940948644731,tm1:1507940948646000,tm2:1507940948686029(40029),tm3:1507940948686264(40264),tm4:1507940948686299(40299)]****[tm4-tm0]:41568\nfinish 227 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37623\n228----rcs.size():7[tm0:1507940948716248,tm1:1507940948717515,tm2:1507940948757595(40080),tm3:1507940948757819(40304),tm4:1507940948757852(40337)]****[tm4-tm0]:41604\nfinish 228 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37503\n229----rcs.size():7[tm0:1507940948792064,tm1:1507940948792617,tm2:1507940948832786(40169),tm3:1507940948833023(40406),tm4:1507940948833197(40580)]****[tm4-tm0]:41133\nfinish 229 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37039\n230----rcs.size():8[tm0:1507940948866556,tm1:1507940948867913,tm2:1507940948906808(38895),tm3:1507940948907056(39143),tm4:1507940948907092(39179)]****[tm4-tm0]:40536\nfinish 230 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37957\n231----rcs.size():8[tm0:1507940948942442,tm1:1507940948943985,tm2:1507940948984635(40650),tm3:1507940948984875(40890),tm4:1507940948985045(41060)]****[tm4-tm0]:42603\nfinish 231 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37653\n232----rcs.size():8[tm0:1507940949015788,tm1:1507940949016397,tm2:1507940949056441(40044),tm3:1507940949056681(40284),tm4:1507940949056869(40472)]****[tm4-tm0]:41081\nfinish 232 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37668\n233----rcs.size():8[tm0:1507940949089996,tm1:1507940949091375,tm2:1507940949131554(40179),tm3:1507940949131792(40417),tm4:1507940949131829(40454)]****[tm4-tm0]:41833\nfinish 233 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38355\n234----rcs.size():8[tm0:1507940949162638,tm1:1507940949163990,tm2:1507940949204872(40882),tm3:1507940949205102(41112),tm4:1507940949205165(41175)]****[tm4-tm0]:42527\nfinish 234 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38342\n235----rcs.size():8[tm0:1507940949235482,tm1:1507940949236116,tm2:1507940949276480(40364),tm3:1507940949276748(40632),tm4:1507940949276936(40820)]****[tm4-tm0]:41454\nfinish 235 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38297\n236----rcs.size():8[tm0:1507940949310555,tm1:1507940949312177,tm2:1507940949353124(40947),tm3:1507940949353383(41206),tm4:1507940949353568(41391)]****[tm4-tm0]:43013\nfinish 236 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38018\n237----rcs.size():8[tm0:1507940949384550,tm1:1507940949385239,tm2:1507940949425974(40735),tm3:1507940949426220(40981),tm4:1507940949426256(41017)]****[tm4-tm0]:41706\nfinish 237 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38081\n238----rcs.size():8[tm0:1507940949455497,tm1:1507940949456056,tm2:1507940949496759(40703),tm3:1507940949496996(40940),tm4:1507940949497033(40977)]****[tm4-tm0]:41536\nfinish 238 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35869\n239----rcs.size():7[tm0:1507940949527827,tm1:1507940949528519,tm2:1507940949564848(36329),tm3:1507940949565121(36602),tm4:1507940949565275(36756)]****[tm4-tm0]:37448\nfinish 239 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35575\n240----rcs.size():7[tm0:1507940949594659,tm1:1507940949595326,tm2:1507940949631395(36069),tm3:1507940949631625(36299),tm4:1507940949631656(36330)]****[tm4-tm0]:36997\nfinish 240 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35546\n241----rcs.size():7[tm0:1507940949660688,tm1:1507940949661354,tm2:1507940949697470(36116),tm3:1507940949697676(36322),tm4:1507940949697706(36352)]****[tm4-tm0]:37018\nfinish 241 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36058\n242----rcs.size():7[tm0:1507940949729110,tm1:1507940949729675,tm2:1507940949766296(36621),tm3:1507940949766502(36827),tm4:1507940949766649(36974)]****[tm4-tm0]:37539\nfinish 242 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36560\n243----rcs.size():7[tm0:1507940949798326,tm1:1507940949799640,tm2:1507940949836753(37113),tm3:1507940949836988(37348),tm4:1507940949837136(37496)]****[tm4-tm0]:38810\nfinish 243 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36302\n244----rcs.size():7[tm0:1507940949867871,tm1:1507940949868585,tm2:1507940949905532(36947),tm3:1507940949905762(37177),tm4:1507940949905810(37225)]****[tm4-tm0]:37939\nfinish 244 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36421\n245----rcs.size():7[tm0:1507940949937692,tm1:1507940949939101,tm2:1507940949976058(36957),tm3:1507940949976299(37198),tm4:1507940949976454(37353)]****[tm4-tm0]:38762\nfinish 245 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36008\n246----rcs.size():7[tm0:1507940950008719,tm1:1507940950009267,tm2:1507940950045776(36509),tm3:1507940950045991(36724),tm4:1507940950046021(36754)]****[tm4-tm0]:37302\nfinish 246 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35509\n247----rcs.size():7[tm0:1507940950079478,tm1:1507940950080046,tm2:1507940950116013(35967),tm3:1507940950116238(36192),tm4:1507940950116284(36238)]****[tm4-tm0]:36806\nfinish 247 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36457\n248----rcs.size():7[tm0:1507940950151503,tm1:1507940950152210,tm2:1507940950189296(37086),tm3:1507940950189517(37307),tm4:1507940950189548(37338)]****[tm4-tm0]:38045\nfinish 248 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37236\n249----rcs.size():7[tm0:1507940950222981,tm1:1507940950224348,tm2:1507940950263843(39495),tm3:1507940950264088(39740),tm4:1507940950264120(39772)]****[tm4-tm0]:41139\nfinish 249 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36347\n250----rcs.size():7[tm0:1507940950299445,tm1:1507940950300739,tm2:1507940950338332(37593),tm3:1507940950338579(37840),tm4:1507940950338625(37886)]****[tm4-tm0]:39180\nfinish 250 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:35481\n251----rcs.size():7[tm0:1507940950368964,tm1:1507940950369564,tm2:1507940950405522(35958),tm3:1507940950405744(36180),tm4:1507940950405792(36228)]****[tm4-tm0]:36828\nfinish 251 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36136\n252----rcs.size():7[tm0:1507940950439929,tm1:1507940950440649,tm2:1507940950477332(36683),tm3:1507940950477620(36971),tm4:1507940950477773(37124)]****[tm4-tm0]:37844\nfinish 252 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35772\n253----rcs.size():7[tm0:1507940950510755,tm1:1507940950512131,tm2:1507940950549204(37073),tm3:1507940950549431(37300),tm4:1507940950549479(37348)]****[tm4-tm0]:38724\nfinish 253 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36092\n254----rcs.size():7[tm0:1507940950580638,tm1:1507940950581977,tm2:1507940950619541(37564),tm3:1507940950619773(37796),tm4:1507940950619927(37950)]****[tm4-tm0]:39289\nfinish 254 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36074\n255----rcs.size():7[tm0:1507940950650847,tm1:1507940950652245,tm2:1507940950689731(37486),tm3:1507940950689963(37718),tm4:1507940950690118(37873)]****[tm4-tm0]:39271\nfinish 255 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36375\n256----rcs.size():7[tm0:1507940950725569,tm1:1507940950726955,tm2:1507940950764800(37845),tm3:1507940950765037(38082),tm4:1507940950765203(38248)]****[tm4-tm0]:39634\nfinish 256 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36603\n257----rcs.size():7[tm0:1507940950796558,tm1:1507940950797880,tm2:1507940950835583(37703),tm3:1507940950835847(37967),tm4:1507940950836004(38124)]****[tm4-tm0]:39446\nfinish 257 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36602\n258----rcs.size():7[tm0:1507940950871812,tm1:1507940950873117,tm2:1507940950910984(37867),tm3:1507940950911248(38131),tm4:1507940950911299(38182)]****[tm4-tm0]:39487\nfinish 258 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36481\n259----rcs.size():7[tm0:1507940950941614,tm1:1507940950942938,tm2:1507940950980718(37780),tm3:1507940950980955(38017),tm4:1507940950981005(38067)]****[tm4-tm0]:39391\nfinish 259 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36326\n260----rcs.size():7[tm0:1507940951011736,tm1:1507940951013074,tm2:1507940951050762(37688),tm3:1507940951051023(37949),tm4:1507940951051056(37982)]****[tm4-tm0]:39320\nfinish 260 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36181\n261----rcs.size():7[tm0:1507940951082649,tm1:1507940951083945,tm2:1507940951121134(37189),tm3:1507940951121402(37457),tm4:1507940951121457(37512)]****[tm4-tm0]:38808\nfinish 261 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:36003\n262----rcs.size():7[tm0:1507940951153932,tm1:1507940951155317,tm2:1507940951192457(37140),tm3:1507940951192743(37426),tm4:1507940951192806(37489)]****[tm4-tm0]:38874\nfinish 262 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37308\n263----rcs.size():7[tm0:1507940951223316,tm1:1507940951224691,tm2:1507940951263588(38897),tm3:1507940951263865(39174),tm4:1507940951263920(39229)]****[tm4-tm0]:40604\nfinish 263 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36397\n264----rcs.size():7[tm0:1507940951293894,tm1:1507940951295332,tm2:1507940951332954(37622),tm3:1507940951333219(37887),tm4:1507940951333253(37921)]****[tm4-tm0]:39359\nfinish 264 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36718\n265----rcs.size():7[tm0:1507940951363653,tm1:1507940951364952,tm2:1507940951403040(38088),tm3:1507940951403290(38338),tm4:1507940951403323(38371)]****[tm4-tm0]:39670\nfinish 265 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37514\n266----rcs.size():7[tm0:1507940951434569,tm1:1507940951435995,tm2:1507940951475276(39281),tm3:1507940951475533(39538),tm4:1507940951475709(39714)]****[tm4-tm0]:41140\nfinish 266 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37490\n267----rcs.size():7[tm0:1507940951506451,tm1:1507940951507800,tm2:1507940951546908(39108),tm3:1507940951547187(39387),tm4:1507940951547338(39538)]****[tm4-tm0]:40887\nfinish 267 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37309\n268----rcs.size():7[tm0:1507940951582555,tm1:1507940951583955,tm2:1507940951622626(38671),tm3:1507940951622882(38927),tm4:1507940951622931(38976)]****[tm4-tm0]:40376\nfinish 268 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37426\n269----rcs.size():7[tm0:1507940951653877,tm1:1507940951655302,tm2:1507940951694922(39620),tm3:1507940951695175(39873),tm4:1507940951695226(39924)]****[tm4-tm0]:41349\nfinish 269 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35831\n270----rcs.size():6[tm0:1507940951725335,tm1:1507940951726819,tm2:1507940951763123(36304),tm3:1507940951763376(36557),tm4:1507940951763403(36584)]****[tm4-tm0]:38068\nfinish 270 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35592\n271----rcs.size():6[tm0:1507940951793832,tm1:1507940951794572,tm2:1507940951830631(36059),tm3:1507940951830829(36257),tm4:1507940951830869(36297)]****[tm4-tm0]:37037\nfinish 271 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:34579\n272----rcs.size():6[tm0:1507940951861221,tm1:1507940951861834,tm2:1507940951896799(34965),tm3:1507940951897009(35175),tm4:1507940951897053(35219)]****[tm4-tm0]:35832\nfinish 272 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35241\n273----rcs.size():6[tm0:1507940951927324,tm1:1507940951927945,tm2:1507940951963632(35687),tm3:1507940951963829(35884),tm4:1507940951963872(35927)]****[tm4-tm0]:36548\nfinish 273 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35440\n274----rcs.size():6[tm0:1507940951993879,tm1:1507940951994538,tm2:1507940952030443(35905),tm3:1507940952030660(36122),tm4:1507940952030703(36165)]****[tm4-tm0]:36824\nfinish 274 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35459\n275----rcs.size():6[tm0:1507940952060762,tm1:1507940952061436,tm2:1507940952097341(35905),tm3:1507940952097548(36112),tm4:1507940952097592(36156)]****[tm4-tm0]:36830\nfinish 275 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35610\n276----rcs.size():6[tm0:1507940952127870,tm1:1507940952128423,tm2:1507940952164481(36058),tm3:1507940952164701(36278),tm4:1507940952164746(36323)]****[tm4-tm0]:36876\nfinish 276 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36001\n277----rcs.size():6[tm0:1507940952194967,tm1:1507940952195561,tm2:1507940952232139(36578),tm3:1507940952232428(36867),tm4:1507940952232456(36895)]****[tm4-tm0]:37489\nfinish 277 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36046\n278----rcs.size():6[tm0:1507940952262379,tm1:1507940952262934,tm2:1507940952299507(36573),tm3:1507940952299817(36883),tm4:1507940952299955(37021)]****[tm4-tm0]:37576\nfinish 278 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35333\n279----rcs.size():6[tm0:1507940952329263,tm1:1507940952329825,tm2:1507940952365547(35722),tm3:1507940952365762(35937),tm4:1507940952365791(35966)]****[tm4-tm0]:36528\nfinish 279 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35566\n280----rcs.size():6[tm0:1507940952395488,tm1:1507940952396086,tm2:1507940952432062(35976),tm3:1507940952432383(36297),tm4:1507940952432413(36327)]****[tm4-tm0]:36925\nfinish 280 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36098\n281----rcs.size():6[tm0:1507940952462228,tm1:1507940952462885,tm2:1507940952499523(36638),tm3:1507940952499744(36859),tm4:1507940952499795(36910)]****[tm4-tm0]:37567\nfinish 281 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35816\n282----rcs.size():6[tm0:1507940952530019,tm1:1507940952530603,tm2:1507940952566951(36348),tm3:1507940952567183(36580),tm4:1507940952567228(36625)]****[tm4-tm0]:37209\nfinish 282 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35806\n283----rcs.size():7[tm0:1507940952602205,tm1:1507940952602776,tm2:1507940952639078(36302),tm3:1507940952639371(36595),tm4:1507940952639522(36746)]****[tm4-tm0]:37317\nfinish 283 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35214\n284----rcs.size():7[tm0:1507940952668175,tm1:1507940952668689,tm2:1507940952704295(35606),tm3:1507940952704573(35884),tm4:1507940952704621(35932)]****[tm4-tm0]:36446\nfinish 284 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36017\n285----rcs.size():7[tm0:1507940952735497,tm1:1507940952736069,tm2:1507940952772599(36530),tm3:1507940952772878(36809),tm4:1507940952773036(36967)]****[tm4-tm0]:37539\nfinish 285 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36055\n286----rcs.size():7[tm0:1507940952805481,tm1:1507940952806046,tm2:1507940952842722(36676),tm3:1507940952843008(36962),tm4:1507940952843178(37132)]****[tm4-tm0]:37697\nfinish 286 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35722\n287----rcs.size():7[tm0:1507940952873232,tm1:1507940952873770,tm2:1507940952909989(36219),tm3:1507940952910245(36475),tm4:1507940952910277(36507)]****[tm4-tm0]:37045\nfinish 287 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35946\n288----rcs.size():7[tm0:1507940952939300,tm1:1507940952939844,tm2:1507940952976376(36532),tm3:1507940952976627(36783),tm4:1507940952976660(36816)]****[tm4-tm0]:37360\nfinish 288 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35885\n289----rcs.size():7[tm0:1507940953006426,tm1:1507940953007131,tm2:1507940953043560(36429),tm3:1507940953043809(36678),tm4:1507940953043971(36840)]****[tm4-tm0]:37545\nfinish 289 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35632\n290----rcs.size():7[tm0:1507940953077096,tm1:1507940953077728,tm2:1507940953113927(36199),tm3:1507940953114192(36464),tm4:1507940953114371(36643)]****[tm4-tm0]:37275\nfinish 290 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35871\n291----rcs.size():7[tm0:1507940953146400,tm1:1507940953147072,tm2:1507940953183462(36390),tm3:1507940953183730(36658),tm4:1507940953183781(36709)]****[tm4-tm0]:37381\nfinish 291 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35706\n292----rcs.size():7[tm0:1507940953213902,tm1:1507940953214444,tm2:1507940953250669(36225),tm3:1507940953250958(36514),tm4:1507940953251150(36706)]****[tm4-tm0]:37248\nfinish 292 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35896\n293----rcs.size():6[tm0:1507940953280652,tm1:1507940953281213,tm2:1507940953317623(36410),tm3:1507940953317883(36670),tm4:1507940953317913(36700)]****[tm4-tm0]:37261\nfinish 293 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35698\n294----rcs.size():6[tm0:1507940953348366,tm1:1507940953348946,tm2:1507940953385189(36243),tm3:1507940953385474(36528),tm4:1507940953385526(36580)]****[tm4-tm0]:37160\nfinish 294 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36074\n295----rcs.size():6[tm0:1507940953418567,tm1:1507940953419140,tm2:1507940953455863(36723),tm3:1507940953456101(36961),tm4:1507940953456132(36992)]****[tm4-tm0]:37565\nfinish 295 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36216\n296----rcs.size():6[tm0:1507940953486231,tm1:1507940953487503,tm2:1507940953524978(37475),tm3:1507940953525269(37766),tm4:1507940953525301(37798)]****[tm4-tm0]:39070\nfinish 296 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36669\n297----rcs.size():6[tm0:1507940953556433,tm1:1507940953557745,tm2:1507940953595814(38069),tm3:1507940953596059(38314),tm4:1507940953596237(38492)]****[tm4-tm0]:39804\nfinish 297 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36712\n298----rcs.size():6[tm0:1507940953626801,tm1:1507940953628218,tm2:1507940953666095(37877),tm3:1507940953666346(38128),tm4:1507940953666380(38162)]****[tm4-tm0]:39579\nfinish 298 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36387\n299----rcs.size():6[tm0:1507940953698856,tm1:1507940953700208,tm2:1507940953738020(37812),tm3:1507940953738279(38071),tm4:1507940953738446(38238)]****[tm4-tm0]:39590\nfinish 299 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36223\n300----rcs.size():6[tm0:1507940953770839,tm1:1507940953771406,tm2:1507940953808277(36871),tm3:1507940953808526(37120),tm4:1507940953808693(37287)]****[tm4-tm0]:37854\nfinish 300 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36677\n301----rcs.size():6[tm0:1507940953839491,tm1:1507940953840954,tm2:1507940953878686(37732),tm3:1507940953878934(37980),tm4:1507940953879123(38169)]****[tm4-tm0]:39632\nfinish 301 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36535\n302----rcs.size():6[tm0:1507940953911881,tm1:1507940953913300,tm2:1507940953951271(37971),tm3:1507940953951521(38221),tm4:1507940953951693(38393)]****[tm4-tm0]:39812\nfinish 302 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36766\n303----rcs.size():6[tm0:1507940953982756,tm1:1507940953984162,tm2:1507940954022283(38121),tm3:1507940954022550(38388),tm4:1507940954022728(38566)]****[tm4-tm0]:39972\nfinish 303 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36590\n304----rcs.size():6[tm0:1507940954052968,tm1:1507940954054300,tm2:1507940954092049(37749),tm3:1507940954092308(38008),tm4:1507940954092359(38059)]****[tm4-tm0]:39391\nfinish 304 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37269\n305----rcs.size():6[tm0:1507940954122571,tm1:1507940954123939,tm2:1507940954162293(38354),tm3:1507940954162538(38599),tm4:1507940954162588(38649)]****[tm4-tm0]:40017\nfinish 305 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37102\n306----rcs.size():6[tm0:1507940954192663,tm1:1507940954194311,tm2:1507940954232662(38351),tm3:1507940954232912(38601),tm4:1507940954232963(38652)]****[tm4-tm0]:40300\nfinish 306 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37272\n307----rcs.size():6[tm0:1507940954263947,tm1:1507940954265389,tm2:1507940954303941(38552),tm3:1507940954304216(38827),tm4:1507940954304270(38881)]****[tm4-tm0]:40323\nfinish 307 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36672\n308----rcs.size():6[tm0:1507940954334287,tm1:1507940954335618,tm2:1507940954373330(37712),tm3:1507940954373584(37966),tm4:1507940954373618(38000)]****[tm4-tm0]:39331\nfinish 308 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36700\n309----rcs.size():7[tm0:1507940954403295,tm1:1507940954404605,tm2:1507940954442347(37742),tm3:1507940954442636(38031),tm4:1507940954442673(38068)]****[tm4-tm0]:39378\nfinish 309 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36703\n310----rcs.size():7[tm0:1507940954472562,tm1:1507940954473871,tm2:1507940954511553(37682),tm3:1507940954511836(37965),tm4:1507940954511872(38001)]****[tm4-tm0]:39310\nfinish 310 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36545\n311----rcs.size():7[tm0:1507940954542991,tm1:1507940954544508,tm2:1507940954582111(37603),tm3:1507940954582463(37955),tm4:1507940954582501(37993)]****[tm4-tm0]:39510\nfinish 311 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36913\n312----rcs.size():7[tm0:1507940954612441,tm1:1507940954613729,tm2:1507940954651929(38200),tm3:1507940954652228(38499),tm4:1507940954652286(38557)]****[tm4-tm0]:39845\nfinish 312 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36389\n313----rcs.size():8[tm0:1507940954688401,tm1:1507940954689760,tm2:1507940954727229(37469),tm3:1507940954727509(37749),tm4:1507940954727708(37948)]****[tm4-tm0]:39307\nfinish 313 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36963\n314----rcs.size():8[tm0:1507940954760469,tm1:1507940954761888,tm2:1507940954800035(38147),tm3:1507940954800345(38457),tm4:1507940954800405(38517)]****[tm4-tm0]:39936\nfinish 314 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36895\n315----rcs.size():8[tm0:1507940954831518,tm1:1507940954832856,tm2:1507940954870897(38041),tm3:1507940954871222(38366),tm4:1507940954871284(38428)]****[tm4-tm0]:39766\nfinish 315 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37461\n316----rcs.size():8[tm0:1507940954903221,tm1:1507940954904619,tm2:1507940954943476(38857),tm3:1507940954943782(39163),tm4:1507940954943844(39225)]****[tm4-tm0]:40623\nfinish 316 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37332\n317----rcs.size():8[tm0:1507940954974608,tm1:1507940954976219,tm2:1507940955015375(39156),tm3:1507940955015678(39459),tm4:1507940955015740(39521)]****[tm4-tm0]:41132\nfinish 317 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36906\n318----rcs.size():8[tm0:1507940955048189,tm1:1507940955049511,tm2:1507940955087884(38373),tm3:1507940955088195(38684),tm4:1507940955088414(38903)]****[tm4-tm0]:40225\nfinish 318 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37391\n319----rcs.size():8[tm0:1507940955121188,tm1:1507940955122460,tm2:1507940955161287(38827),tm3:1507940955161578(39118),tm4:1507940955161619(39159)]****[tm4-tm0]:40431\nfinish 319 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37406\n320----rcs.size():8[tm0:1507940955194609,tm1:1507940955195876,tm2:1507940955235023(39147),tm3:1507940955235331(39455),tm4:1507940955235399(39523)]****[tm4-tm0]:40790\nfinish 320 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37208\n321----rcs.size():8[tm0:1507940955265861,tm1:1507940955267203,tm2:1507940955306463(39260),tm3:1507940955306777(39574),tm4:1507940955306848(39645)]****[tm4-tm0]:40987\nfinish 321 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37298\n322----rcs.size():8[tm0:1507940955338880,tm1:1507940955340326,tm2:1507940955379794(39468),tm3:1507940955380116(39790),tm4:1507940955380247(39921)]****[tm4-tm0]:41367\nfinish 322 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37110\n323----rcs.size():8[tm0:1507940955410336,tm1:1507940955411736,tm2:1507940955450896(39160),tm3:1507940955451223(39487),tm4:1507940955451291(39555)]****[tm4-tm0]:40955\nfinish 323 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37531\n324----rcs.size():8[tm0:1507940955481231,tm1:1507940955482641,tm2:1507940955521938(39297),tm3:1507940955522253(39612),tm4:1507940955522319(39678)]****[tm4-tm0]:41088\nfinish 324 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37232\n325----rcs.size():8[tm0:1507940955556638,tm1:1507940955557982,tm2:1507940955597223(39241),tm3:1507940955597547(39565),tm4:1507940955597614(39632)]****[tm4-tm0]:40976\nfinish 325 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37057\n326----rcs.size():8[tm0:1507940955631816,tm1:1507940955633219,tm2:1507940955672411(39192),tm3:1507940955672754(39535),tm4:1507940955672800(39581)]****[tm4-tm0]:40984\nfinish 326 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37913\n327----rcs.size():8[tm0:1507940955702899,tm1:1507940955704244,tm2:1507940955744571(40327),tm3:1507940955744901(40657),tm4:1507940955744965(40721)]****[tm4-tm0]:42066\nfinish 327 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37933\n328----rcs.size():7[tm0:1507940955775163,tm1:1507940955776691,tm2:1507940955816674(39983),tm3:1507940955817014(40323),tm4:1507940955817078(40387)]****[tm4-tm0]:41915\nfinish 328 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37230\n329----rcs.size():8[tm0:1507940955848990,tm1:1507940955850261,tm2:1507940955889868(39607),tm3:1507940955890314(40053),tm4:1507940955890358(40097)]****[tm4-tm0]:41368\nfinish 329 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38218\n330----rcs.size():7[tm0:1507940955921118,tm1:1507940955922568,tm2:1507940955963584(41016),tm3:1507940955963930(41362),tm4:1507940955963971(41403)]****[tm4-tm0]:42853\nfinish 330 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37662\n331----rcs.size():7[tm0:1507940955993589,tm1:1507940955994922,tm2:1507940956035125(40203),tm3:1507940956035479(40557),tm4:1507940956035535(40613)]****[tm4-tm0]:41946\nfinish 331 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37803\n332----rcs.size():6[tm0:1507940956065773,tm1:1507940956067092,tm2:1507940956107454(40362),tm3:1507940956107719(40627),tm4:1507940956107775(40683)]****[tm4-tm0]:42002\nfinish 332 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37874\n333----rcs.size():6[tm0:1507940956139046,tm1:1507940956139637,tm2:1507940956180361(40724),tm3:1507940956180614(40977),tm4:1507940956180668(41031)]****[tm4-tm0]:41622\nfinish 333 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38434\n334----rcs.size():7[tm0:1507940956210807,tm1:1507940956212263,tm2:1507940956253489(41226),tm3:1507940956253797(41534),tm4:1507940956253838(41575)]****[tm4-tm0]:43031\nfinish 334 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38193\n335----rcs.size():7[tm0:1507940956287595,tm1:1507940956288166,tm2:1507940956328534(40368),tm3:1507940956328834(40668),tm4:1507940956328889(40723)]****[tm4-tm0]:41294\nfinish 335 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37595\n336----rcs.size():6[tm0:1507940956359690,tm1:1507940956361095,tm2:1507940956401082(39987),tm3:1507940956401382(40287),tm4:1507940956401438(40343)]****[tm4-tm0]:41748\nfinish 336 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38584\n337----rcs.size():7[tm0:1507940956431795,tm1:1507940956433155,tm2:1507940956474355(41200),tm3:1507940956474685(41530),tm4:1507940956474741(41586)]****[tm4-tm0]:42946\nfinish 337 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39764\n338----rcs.size():6[tm0:1507940956504175,tm1:1507940956504796,tm2:1507940956547736(42940),tm3:1507940956548045(43249),tm4:1507940956548081(43285)]****[tm4-tm0]:43906\nfinish 338 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38559\n339----rcs.size():6[tm0:1507940956581514,tm1:1507940956582103,tm2:1507940956624149(42046),tm3:1507940956624473(42370),tm4:1507940956624527(42424)]****[tm4-tm0]:43013\nfinish 339 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:39805\n340----rcs.size():7[tm0:1507940956654126,tm1:1507940956654816,tm2:1507940956697977(43161),tm3:1507940956698320(43504),tm4:1507940956698378(43562)]****[tm4-tm0]:44252\nfinish 340 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38292\n341----rcs.size():6[tm0:1507940956728084,tm1:1507940956728642,tm2:1507940956769521(40879),tm3:1507940956769794(41152),tm4:1507940956769833(41191)]****[tm4-tm0]:41749\nfinish 341 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38666\n342----rcs.size():6[tm0:1507940956801910,tm1:1507940956802459,tm2:1507940956844479(42020),tm3:1507940956844708(42249),tm4:1507940956844888(42429)]****[tm4-tm0]:42978\nfinish 342 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37960\n343----rcs.size():6[tm0:1507940956877748,tm1:1507940956878318,tm2:1507940956919087(40769),tm3:1507940956919325(41007),tm4:1507940956919376(41058)]****[tm4-tm0]:41628\nfinish 343 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:39707\n344----rcs.size():6[tm0:1507940956949789,tm1:1507940956950446,tm2:1507940956993332(42886),tm3:1507940956993559(43113),tm4:1507940956993598(43152)]****[tm4-tm0]:43809\nfinish 344 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38723\n345----rcs.size():6[tm0:1507940957027776,tm1:1507940957028351,tm2:1507940957070348(41997),tm3:1507940957070593(42242),tm4:1507940957070643(42292)]****[tm4-tm0]:42867\nfinish 345 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39498\n346----rcs.size():6[tm0:1507940957104523,tm1:1507940957105090,tm2:1507940957147684(42594),tm3:1507940957147913(42823),tm4:1507940957147963(42873)]****[tm4-tm0]:43440\nfinish 346 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38879\n347----rcs.size():6[tm0:1507940957181602,tm1:1507940957182330,tm2:1507940957224655(42325),tm3:1507940957224886(42556),tm4:1507940957224936(42606)]****[tm4-tm0]:43334\nfinish 347 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38718\n348----rcs.size():6[tm0:1507940957255186,tm1:1507940957255745,tm2:1507940957298015(42270),tm3:1507940957298264(42519),tm4:1507940957298315(42570)]****[tm4-tm0]:43129\nfinish 348 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39081\n349----rcs.size():6[tm0:1507940957331633,tm1:1507940957332374,tm2:1507940957374759(42385),tm3:1507940957374995(42621),tm4:1507940957375045(42671)]****[tm4-tm0]:43412\nfinish 349 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39148\n350----rcs.size():6[tm0:1507940957411722,tm1:1507940957412259,tm2:1507940957454720(42461),tm3:1507940957454957(42698),tm4:1507940957455008(42749)]****[tm4-tm0]:43286\nfinish 350 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39285\n351----rcs.size():6[tm0:1507940957485864,tm1:1507940957486451,tm2:1507940957529182(42731),tm3:1507940957529420(42969),tm4:1507940957529471(43020)]****[tm4-tm0]:43607\nfinish 351 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39766\n352----rcs.size():6[tm0:1507940957561951,tm1:1507940957562652,tm2:1507940957605813(43161),tm3:1507940957606132(43480),tm4:1507940957606190(43538)]****[tm4-tm0]:44239\nfinish 352 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39263\n353----rcs.size():6[tm0:1507940957639231,tm1:1507940957639830,tm2:1507940957683611(43781),tm3:1507940957683930(44100),tm4:1507940957683978(44148)]****[tm4-tm0]:44747\nfinish 353 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36536\n354----rcs.size():5[tm0:1507940957719342,tm1:1507940957719923,tm2:1507940957757523(37600),tm3:1507940957757753(37830),tm4:1507940957757781(37858)]****[tm4-tm0]:38439\nfinish 354 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36651\n355----rcs.size():6[tm0:1507940957792026,tm1:1507940957793638,tm2:1507940957831619(37981),tm3:1507940957831938(38300),tm4:1507940957831982(38344)]****[tm4-tm0]:39956\nfinish 355 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37430\n356----rcs.size():6[tm0:1507940957863683,tm1:1507940957865128,tm2:1507940957904154(39026),tm3:1507940957904467(39339),tm4:1507940957904509(39381)]****[tm4-tm0]:40826\nfinish 356 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36884\n357----rcs.size():6[tm0:1507940957939376,tm1:1507940957940732,tm2:1507940957979133(38401),tm3:1507940957979457(38725),tm4:1507940957979506(38774)]****[tm4-tm0]:40130\nfinish 357 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37245\n358----rcs.size():6[tm0:1507940958013260,tm1:1507940958014598,tm2:1507940958053242(38644),tm3:1507940958053469(38871),tm4:1507940958053622(39024)]****[tm4-tm0]:40362\nfinish 358 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36937\n359----rcs.size():6[tm0:1507940958084589,tm1:1507940958085894,tm2:1507940958124368(38474),tm3:1507940958124688(38794),tm4:1507940958124720(38826)]****[tm4-tm0]:40131\nfinish 359 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37265\n360----rcs.size():6[tm0:1507940958156221,tm1:1507940958157580,tm2:1507940958196621(39041),tm3:1507940958196829(39249),tm4:1507940958196980(39400)]****[tm4-tm0]:40759\nfinish 360 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37161\n361----rcs.size():6[tm0:1507940958229034,tm1:1507940958230364,tm2:1507940958269036(38672),tm3:1507940958269256(38892),tm4:1507940958269409(39045)]****[tm4-tm0]:40375\nfinish 361 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37068\n362----rcs.size():6[tm0:1507940958300192,tm1:1507940958301524,tm2:1507940958339990(38466),tm3:1507940958340245(38721),tm4:1507940958340290(38766)]****[tm4-tm0]:40098\nfinish 362 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36874\n363----rcs.size():6[tm0:1507940958372058,tm1:1507940958373402,tm2:1507940958412624(39222),tm3:1507940958412850(39448),tm4:1507940958413009(39607)]****[tm4-tm0]:40951\nfinish 363 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37399\n364----rcs.size():6[tm0:1507940958443346,tm1:1507940958444724,tm2:1507940958483878(39154),tm3:1507940958484106(39382),tm4:1507940958484276(39552)]****[tm4-tm0]:40930\nfinish 364 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37271\n365----rcs.size():6[tm0:1507940958521248,tm1:1507940958522546,tm2:1507940958561654(39108),tm3:1507940958561866(39320),tm4:1507940958561909(39363)]****[tm4-tm0]:40661\nfinish 365 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37779\n366----rcs.size():6[tm0:1507940958596407,tm1:1507940958597724,tm2:1507940958637334(39610),tm3:1507940958637563(39839),tm4:1507940958637606(39882)]****[tm4-tm0]:41199\nfinish 366 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37428\n367----rcs.size():6[tm0:1507940958668579,tm1:1507940958669993,tm2:1507940958709549(39556),tm3:1507940958709786(39793),tm4:1507940958709829(39836)]****[tm4-tm0]:41250\nfinish 367 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37154\n368----rcs.size():6[tm0:1507940958740531,tm1:1507940958742158,tm2:1507940958781437(39279),tm3:1507940958781679(39521),tm4:1507940958781722(39564)]****[tm4-tm0]:41191\nfinish 368 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37560\n369----rcs.size():6[tm0:1507940958812854,tm1:1507940958814265,tm2:1507940958854231(39966),tm3:1507940958854555(40290),tm4:1507940958854600(40335)]****[tm4-tm0]:41746\nfinish 369 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36209\n370----rcs.size():5[tm0:1507940958886225,tm1:1507940958887551,tm2:1507940958924240(36689),tm3:1507940958924459(36908),tm4:1507940958924496(36945)]****[tm4-tm0]:38271\nfinish 370 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35794\n371----rcs.size():5[tm0:1507940958954571,tm1:1507940958955173,tm2:1507940958991447(36274),tm3:1507940958991618(36445),tm4:1507940958991653(36480)]****[tm4-tm0]:37082\nfinish 371 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36346\n372----rcs.size():5[tm0:1507940959022056,tm1:1507940959022630,tm2:1507940959059511(36881),tm3:1507940959059686(37056),tm4:1507940959059721(37091)]****[tm4-tm0]:37665\nfinish 372 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35958\n373----rcs.size():5[tm0:1507940959090331,tm1:1507940959090910,tm2:1507940959127400(36490),tm3:1507940959127571(36661),tm4:1507940959127606(36696)]****[tm4-tm0]:37275\nfinish 373 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35820\n374----rcs.size():5[tm0:1507940959160217,tm1:1507940959160885,tm2:1507940959197296(36411),tm3:1507940959197471(36586),tm4:1507940959197507(36622)]****[tm4-tm0]:37290\nfinish 374 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35891\n375----rcs.size():5[tm0:1507940959231521,tm1:1507940959232219,tm2:1507940959268672(36453),tm3:1507940959268846(36627),tm4:1507940959268882(36663)]****[tm4-tm0]:37361\nfinish 375 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35777\n376----rcs.size():5[tm0:1507940959299504,tm1:1507940959300108,tm2:1507940959336385(36277),tm3:1507940959336560(36452),tm4:1507940959336599(36491)]****[tm4-tm0]:37095\nfinish 376 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35864\n377----rcs.size():5[tm0:1507940959367173,tm1:1507940959367858,tm2:1507940959404253(36395),tm3:1507940959404431(36573),tm4:1507940959404469(36611)]****[tm4-tm0]:37296\nfinish 377 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35819\n378----rcs.size():5[tm0:1507940959435623,tm1:1507940959436273,tm2:1507940959472657(36384),tm3:1507940959472852(36579),tm4:1507940959472888(36615)]****[tm4-tm0]:37265\nfinish 378 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35641\n379----rcs.size():5[tm0:1507940959502378,tm1:1507940959502976,tm2:1507940959539117(36141),tm3:1507940959539290(36314),tm4:1507940959539326(36350)]****[tm4-tm0]:36948\nfinish 379 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35441\n380----rcs.size():5[tm0:1507940959569525,tm1:1507940959570176,tm2:1507940959606105(35929),tm3:1507940959606284(36108),tm4:1507940959606320(36144)]****[tm4-tm0]:36795\nfinish 380 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35565\n381----rcs.size():5[tm0:1507940959636342,tm1:1507940959637030,tm2:1507940959673071(36041),tm3:1507940959673264(36234),tm4:1507940959673301(36271)]****[tm4-tm0]:36959\nfinish 381 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36110\n382----rcs.size():5[tm0:1507940959703484,tm1:1507940959704063,tm2:1507940959740681(36618),tm3:1507940959740867(36804),tm4:1507940959740907(36844)]****[tm4-tm0]:37423\nfinish 382 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35892\n383----rcs.size():5[tm0:1507940959771178,tm1:1507940959771731,tm2:1507940959808108(36377),tm3:1507940959808320(36589),tm4:1507940959808358(36627)]****[tm4-tm0]:37180\nfinish 383 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36204\n384----rcs.size():5[tm0:1507940959840776,tm1:1507940959841327,tm2:1507940959878442(37115),tm3:1507940959878611(37284),tm4:1507940959878648(37321)]****[tm4-tm0]:37872\nfinish 384 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36595\n385----rcs.size():5[tm0:1507940959913368,tm1:1507940959914713,tm2:1507940959952363(37650),tm3:1507940959952534(37821),tm4:1507940959952576(37863)]****[tm4-tm0]:39208\nfinish 385 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36681\n386----rcs.size():5[tm0:1507940959987554,tm1:1507940959988886,tm2:1507940960026777(37891),tm3:1507940960026961(38075),tm4:1507940960027000(38114)]****[tm4-tm0]:39446\nfinish 386 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36800\n387----rcs.size():5[tm0:1507940960057157,tm1:1507940960057695,tm2:1507940960095345(37650),tm3:1507940960095516(37821),tm4:1507940960095554(37859)]****[tm4-tm0]:38397\nfinish 387 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36036\n388----rcs.size():5[tm0:1507940960126130,tm1:1507940960127505,tm2:1507940960164944(37439),tm3:1507940960165153(37648),tm4:1507940960165181(37676)]****[tm4-tm0]:39051\nfinish 388 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36081\n389----rcs.size():5[tm0:1507940960195890,tm1:1507940960197191,tm2:1507940960234486(37295),tm3:1507940960234669(37478),tm4:1507940960234698(37507)]****[tm4-tm0]:38808\nfinish 389 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36661\n390----rcs.size():5[tm0:1507940960265628,tm1:1507940960266211,tm2:1507940960303543(37332),tm3:1507940960303728(37517),tm4:1507940960303755(37544)]****[tm4-tm0]:38127\nfinish 390 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37527\n391----rcs.size():5[tm0:1507940960335407,tm1:1507940960336784,tm2:1507940960375459(38675),tm3:1507940960375652(38868),tm4:1507940960375691(38907)]****[tm4-tm0]:40284\nfinish 391 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36873\n392----rcs.size():5[tm0:1507940960409860,tm1:1507940960411244,tm2:1507940960449280(38036),tm3:1507940960449456(38212),tm4:1507940960449496(38252)]****[tm4-tm0]:39636\nfinish 392 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36108\n393----rcs.size():6[tm0:1507940960481036,tm1:1507940960482356,tm2:1507940960519915(37559),tm3:1507940960520177(37821),tm4:1507940960520217(37861)]****[tm4-tm0]:39181\nfinish 393 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37239\n394----rcs.size():6[tm0:1507940960551713,tm1:1507940960553033,tm2:1507940960591548(38515),tm3:1507940960591801(38768),tm4:1507940960591841(38808)]****[tm4-tm0]:40128\nfinish 394 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36596\n395----rcs.size():6[tm0:1507940960623374,tm1:1507940960624660,tm2:1507940960662620(37960),tm3:1507940960662873(38213),tm4:1507940960662905(38245)]****[tm4-tm0]:39531\nfinish 395 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37207\n396----rcs.size():6[tm0:1507940960693933,tm1:1507940960695334,tm2:1507940960733895(38561),tm3:1507940960734102(38768),tm4:1507940960734266(38932)]****[tm4-tm0]:40333\nfinish 396 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36762\n397----rcs.size():6[tm0:1507940960766033,tm1:1507940960767472,tm2:1507940960805572(38100),tm3:1507940960805816(38344),tm4:1507940960805875(38403)]****[tm4-tm0]:39842\nfinish 397 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37526\n398----rcs.size():6[tm0:1507940960837872,tm1:1507940960839256,tm2:1507940960878315(39059),tm3:1507940960878558(39302),tm4:1507940960878711(39455)]****[tm4-tm0]:40839\nfinish 398 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37057\n399----rcs.size():6[tm0:1507940960911366,tm1:1507940960912696,tm2:1507940960951048(38352),tm3:1507940960951271(38575),tm4:1507940960951444(38748)]****[tm4-tm0]:40078\nfinish 399 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36640\n400----rcs.size():6[tm0:1507940960983044,tm1:1507940960984408,tm2:1507940961022174(37766),tm3:1507940961022408(38000),tm4:1507940961022602(38194)]****[tm4-tm0]:39558\nfinish 400 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37816\n401----rcs.size():6[tm0:1507940961052324,tm1:1507940961053686,tm2:1507940961093507(39821),tm3:1507940961093735(40049),tm4:1507940961093898(40212)]****[tm4-tm0]:41574\nfinish 401 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37315\n402----rcs.size():6[tm0:1507940961123858,tm1:1507940961125335,tm2:1507940961164674(39339),tm3:1507940961164908(39573),tm4:1507940961165069(39734)]****[tm4-tm0]:41211\nfinish 402 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37007\n403----rcs.size():6[tm0:1507940961195302,tm1:1507940961196626,tm2:1507940961235476(38850),tm3:1507940961235714(39088),tm4:1507940961235763(39137)]****[tm4-tm0]:40461\nfinish 403 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36939\n404----rcs.size():6[tm0:1507940961266120,tm1:1507940961267490,tm2:1507940961306383(38893),tm3:1507940961306626(39136),tm4:1507940961306793(39303)]****[tm4-tm0]:40673\nfinish 404 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37229\n405----rcs.size():6[tm0:1507940961343566,tm1:1507940961344878,tm2:1507940961384049(39171),tm3:1507940961384286(39408),tm4:1507940961384458(39580)]****[tm4-tm0]:40892\nfinish 405 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36875\n406----rcs.size():6[tm0:1507940961421626,tm1:1507940961423030,tm2:1507940961461950(38920),tm3:1507940961462197(39167),tm4:1507940961462371(39341)]****[tm4-tm0]:40745\nfinish 406 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37648\n407----rcs.size():6[tm0:1507940961495378,tm1:1507940961496729,tm2:1507940961536707(39978),tm3:1507940961536950(40221),tm4:1507940961537121(40392)]****[tm4-tm0]:41743\nfinish 407 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37882\n408----rcs.size():6[tm0:1507940961570460,tm1:1507940961571821,tm2:1507940961611488(39667),tm3:1507940961611735(39914),tm4:1507940961611788(39967)]****[tm4-tm0]:41328\nfinish 408 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37627\n409----rcs.size():6[tm0:1507940961641939,tm1:1507940961643389,tm2:1507940961682805(39416),tm3:1507940961683046(39657),tm4:1507940961683228(39839)]****[tm4-tm0]:41289\nfinish 409 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37360\n410----rcs.size():6[tm0:1507940961713889,tm1:1507940961715287,tm2:1507940961754453(39166),tm3:1507940961754692(39405),tm4:1507940961754748(39461)]****[tm4-tm0]:40859\nfinish 410 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38764\n411----rcs.size():6[tm0:1507940961784984,tm1:1507940961786317,tm2:1507940961828377(42060),tm3:1507940961828585(42268),tm4:1507940961828619(42302)]****[tm4-tm0]:43635\nfinish 411 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38057\n412----rcs.size():6[tm0:1507940961859206,tm1:1507940961859780,tm2:1507940961900473(40693),tm3:1507940961900716(40936),tm4:1507940961900875(41095)]****[tm4-tm0]:41669\nfinish 412 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38138\n413----rcs.size():6[tm0:1507940961932421,tm1:1507940961933880,tm2:1507940961974789(40909),tm3:1507940961975039(41159),tm4:1507940961975207(41327)]****[tm4-tm0]:42786\nfinish 413 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:37613\n414----rcs.size():6[tm0:1507940962006013,tm1:1507940962007412,tm2:1507940962047482(40070),tm3:1507940962047730(40318),tm4:1507940962047891(40479)]****[tm4-tm0]:41878\nfinish 414 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37660\n415----rcs.size():6[tm0:1507940962082406,tm1:1507940962083777,tm2:1507940962123774(39997),tm3:1507940962124029(40252),tm4:1507940962124075(40298)]****[tm4-tm0]:41669\nfinish 415 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38741\n416----rcs.size():6[tm0:1507940962154603,tm1:1507940962156001,tm2:1507940962197800(41799),tm3:1507940962198031(42030),tm4:1507940962198080(42079)]****[tm4-tm0]:43477\nfinish 416 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38342\n417----rcs.size():6[tm0:1507940962228997,tm1:1507940962229573,tm2:1507940962270254(40681),tm3:1507940962270524(40951),tm4:1507940962270686(41113)]****[tm4-tm0]:41689\nfinish 417 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38189\n418----rcs.size():5[tm0:1507940962301704,tm1:1507940962303106,tm2:1507940962343753(40647),tm3:1507940962343974(40868),tm4:1507940962344134(41028)]****[tm4-tm0]:42430\nfinish 418 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38038\n419----rcs.size():5[tm0:1507940962374412,tm1:1507940962375165,tm2:1507940962415840(40675),tm3:1507940962416031(40866),tm4:1507940962416181(41016)]****[tm4-tm0]:41769\nfinish 419 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:37473\n420----rcs.size():5[tm0:1507940962446278,tm1:1507940962446813,tm2:1507940962486449(39636),tm3:1507940962486631(39818),tm4:1507940962486666(39853)]****[tm4-tm0]:40388\nfinish 420 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37429\n421----rcs.size():5[tm0:1507940962518079,tm1:1507940962519431,tm2:1507940962558483(39052),tm3:1507940962558684(39253),tm4:1507940962558796(39365)]****[tm4-tm0]:40717\nfinish 421 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35950\n422----rcs.size():4[tm0:1507940962590179,tm1:1507940962591722,tm2:1507940962628197(36475),tm3:1507940962628369(36647),tm4:1507940962628456(36734)]****[tm4-tm0]:38277\nfinish 422 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35463\n423----rcs.size():4[tm0:1507940962658845,tm1:1507940962659429,tm2:1507940962695296(35867),tm3:1507940962695431(36002),tm4:1507940962695459(36030)]****[tm4-tm0]:36614\nfinish 423 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35506\n424----rcs.size():4[tm0:1507940962725896,tm1:1507940962726438,tm2:1507940962762391(35953),tm3:1507940962762529(36091),tm4:1507940962762617(36179)]****[tm4-tm0]:36721\nfinish 424 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35223\n425----rcs.size():5[tm0:1507940962793105,tm1:1507940962793685,tm2:1507940962829307(35622),tm3:1507940962829535(35850),tm4:1507940962829561(35876)]****[tm4-tm0]:36456\nfinish 425 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36067\n426----rcs.size():5[tm0:1507940962859948,tm1:1507940962860524,tm2:1507940962897038(36514),tm3:1507940962897284(36760),tm4:1507940962897378(36854)]****[tm4-tm0]:37430\nfinish 426 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35350\n427----rcs.size():5[tm0:1507940962927758,tm1:1507940962928376,tm2:1507940962964124(35748),tm3:1507940962964351(35975),tm4:1507940962964383(36007)]****[tm4-tm0]:36625\nfinish 427 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35701\n428----rcs.size():5[tm0:1507940962994555,tm1:1507940962995100,tm2:1507940963031289(36189),tm3:1507940963031426(36326),tm4:1507940963031535(36435)]****[tm4-tm0]:36980\nfinish 428 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35114\n429----rcs.size():5[tm0:1507940963061744,tm1:1507940963062269,tm2:1507940963097800(35531),tm3:1507940963097948(35679),tm4:1507940963097971(35702)]****[tm4-tm0]:36227\nfinish 429 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35545\n430----rcs.size():5[tm0:1507940963127938,tm1:1507940963128578,tm2:1507940963164555(35977),tm3:1507940963164711(36133),tm4:1507940963164820(36242)]****[tm4-tm0]:36882\nfinish 430 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35530\n431----rcs.size():5[tm0:1507940963195047,tm1:1507940963195586,tm2:1507940963231619(36033),tm3:1507940963231865(36279),tm4:1507940963231975(36389)]****[tm4-tm0]:36928\nfinish 431 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35582\n432----rcs.size():5[tm0:1507940963262518,tm1:1507940963263110,tm2:1507940963299203(36093),tm3:1507940963299352(36242),tm4:1507940963299467(36357)]****[tm4-tm0]:36949\nfinish 432 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35896\n433----rcs.size():5[tm0:1507940963329633,tm1:1507940963330209,tm2:1507940963366652(36443),tm3:1507940963366821(36612),tm4:1507940963366856(36647)]****[tm4-tm0]:37223\nfinish 433 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35707\n434----rcs.size():5[tm0:1507940963399304,tm1:1507940963399842,tm2:1507940963436073(36231),tm3:1507940963436245(36403),tm4:1507940963436283(36441)]****[tm4-tm0]:36979\nfinish 434 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35457\n435----rcs.size():5[tm0:1507940963466763,tm1:1507940963467331,tm2:1507940963503246(35915),tm3:1507940963503409(36078),tm4:1507940963503444(36113)]****[tm4-tm0]:36681\nfinish 435 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35907\n436----rcs.size():5[tm0:1507940963536187,tm1:1507940963536772,tm2:1507940963573159(36387),tm3:1507940963573327(36555),tm4:1507940963573361(36589)]****[tm4-tm0]:37174\nfinish 436 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35994\n437----rcs.size():5[tm0:1507940963608889,tm1:1507940963609510,tm2:1507940963646061(36551),tm3:1507940963646225(36715),tm4:1507940963646339(36829)]****[tm4-tm0]:37450\nfinish 437 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36533\n438----rcs.size():5[tm0:1507940963678231,tm1:1507940963679567,tm2:1507940963717297(37730),tm3:1507940963717448(37881),tm4:1507940963717581(38014)]****[tm4-tm0]:39350\nfinish 438 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35671\n439----rcs.size():5[tm0:1507940963747693,tm1:1507940963748238,tm2:1507940963784443(36205),tm3:1507940963784597(36359),tm4:1507940963784631(36393)]****[tm4-tm0]:36938\nfinish 439 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35833\n440----rcs.size():5[tm0:1507940963814930,tm1:1507940963815463,tm2:1507940963851775(36312),tm3:1507940963851927(36464),tm4:1507940963851962(36499)]****[tm4-tm0]:37032\nfinish 440 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35697\n441----rcs.size():5[tm0:1507940963881898,tm1:1507940963882472,tm2:1507940963918703(36231),tm3:1507940963918854(36382),tm4:1507940963918890(36418)]****[tm4-tm0]:36992\nfinish 441 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36034\n442----rcs.size():5[tm0:1507940963948856,tm1:1507940963949458,tm2:1507940963986061(36603),tm3:1507940963986224(36766),tm4:1507940963986259(36801)]****[tm4-tm0]:37403\nfinish 442 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36260\n443----rcs.size():5[tm0:1507940964017703,tm1:1507940964019083,tm2:1507940964056750(37667),tm3:1507940964056904(37821),tm4:1507940964056941(37858)]****[tm4-tm0]:39238\nfinish 443 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36464\n444----rcs.size():5[tm0:1507940964087333,tm1:1507940964088039,tm2:1507940964125095(37056),tm3:1507940964125272(37233),tm4:1507940964125309(37270)]****[tm4-tm0]:37976\nfinish 444 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36558\n445----rcs.size():5[tm0:1507940964157127,tm1:1507940964158787,tm2:1507940964196580(37793),tm3:1507940964196817(38030),tm4:1507940964196853(38066)]****[tm4-tm0]:39726\nfinish 445 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36103\n446----rcs.size():6[tm0:1507940964228939,tm1:1507940964230306,tm2:1507940964267473(37167),tm3:1507940964267725(37419),tm4:1507940964267762(37456)]****[tm4-tm0]:38823\nfinish 446 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:35688\n447----rcs.size():6[tm0:1507940964301126,tm1:1507940964302415,tm2:1507940964339462(37047),tm3:1507940964339718(37303),tm4:1507940964339745(37330)]****[tm4-tm0]:38619\nfinish 447 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37206\n448----rcs.size():6[tm0:1507940964370566,tm1:1507940964371883,tm2:1507940964410353(38470),tm3:1507940964410592(38709),tm4:1507940964410621(38738)]****[tm4-tm0]:40055\nfinish 448 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36929\n449----rcs.size():6[tm0:1507940964441689,tm1:1507940964443084,tm2:1507940964481426(38342),tm3:1507940964481612(38528),tm4:1507940964481641(38557)]****[tm4-tm0]:39952\nfinish 449 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:36919\n450----rcs.size():6[tm0:1507940964513177,tm1:1507940964514507,tm2:1507940964552575(38068),tm3:1507940964552775(38268),tm4:1507940964552806(38299)]****[tm4-tm0]:39629\nfinish 450 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36356\n451----rcs.size():6[tm0:1507940964581774,tm1:1507940964583114,tm2:1507940964620760(37646),tm3:1507940964620979(37865),tm4:1507940964621008(37894)]****[tm4-tm0]:39234\nfinish 451 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37070\n452----rcs.size():6[tm0:1507940964651043,tm1:1507940964652357,tm2:1507940964690692(38335),tm3:1507940964690879(38522),tm4:1507940964690908(38551)]****[tm4-tm0]:39865\nfinish 452 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37396\n453----rcs.size():6[tm0:1507940964722069,tm1:1507940964723485,tm2:1507940964762532(39047),tm3:1507940964762717(39232),tm4:1507940964762747(39262)]****[tm4-tm0]:40678\nfinish 453 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37134\n454----rcs.size():6[tm0:1507940964793370,tm1:1507940964794734,tm2:1507940964833027(38293),tm3:1507940964833230(38496),tm4:1507940964833260(38526)]****[tm4-tm0]:39890\nfinish 454 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36711\n455----rcs.size():6[tm0:1507940964866640,tm1:1507940964867948,tm2:1507940964905807(37859),tm3:1507940964906006(38058),tm4:1507940964906049(38101)]****[tm4-tm0]:39409\nfinish 455 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36777\n456----rcs.size():6[tm0:1507940964941902,tm1:1507940964943222,tm2:1507940964981235(38013),tm3:1507940964981441(38219),tm4:1507940964981471(38249)]****[tm4-tm0]:39569\nfinish 456 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36787\n457----rcs.size():6[tm0:1507940965011870,tm1:1507940965013236,tm2:1507940965051282(38046),tm3:1507940965051481(38245),tm4:1507940965051522(38286)]****[tm4-tm0]:39652\nfinish 457 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37359\n458----rcs.size():6[tm0:1507940965083366,tm1:1507940965084700,tm2:1507940965123423(38723),tm3:1507940965123614(38914),tm4:1507940965123760(39060)]****[tm4-tm0]:40394\nfinish 458 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37141\n459----rcs.size():6[tm0:1507940965155199,tm1:1507940965156579,tm2:1507940965195717(39138),tm3:1507940965195926(39347),tm4:1507940965196069(39490)]****[tm4-tm0]:40870\nfinish 459 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:36736\n460----rcs.size():6[tm0:1507940965227588,tm1:1507940965228984,tm2:1507940965267435(38451),tm3:1507940965267630(38646),tm4:1507940965267778(38794)]****[tm4-tm0]:40190\nfinish 460 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36888\n461----rcs.size():6[tm0:1507940965300640,tm1:1507940965301962,tm2:1507940965340286(38324),tm3:1507940965340508(38546),tm4:1507940965340656(38694)]****[tm4-tm0]:40016\nfinish 461 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37073\n462----rcs.size():6[tm0:1507940965373749,tm1:1507940965375376,tm2:1507940965414296(38920),tm3:1507940965414522(39146),tm4:1507940965414566(39190)]****[tm4-tm0]:40817\nfinish 462 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37339\n463----rcs.size():6[tm0:1507940965445247,tm1:1507940965446560,tm2:1507940965485543(38983),tm3:1507940965485752(39192),tm4:1507940965485793(39233)]****[tm4-tm0]:40546\nfinish 463 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37219\n464----rcs.size():6[tm0:1507940965517601,tm1:1507940965518991,tm2:1507940965557974(38983),tm3:1507940965558182(39191),tm4:1507940965558229(39238)]****[tm4-tm0]:40628\nfinish 464 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37070\n465----rcs.size():6[tm0:1507940965588496,tm1:1507940965589824,tm2:1507940965628817(38993),tm3:1507940965629019(39195),tm4:1507940965629065(39241)]****[tm4-tm0]:40569\nfinish 465 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37084\n466----rcs.size():6[tm0:1507940965659360,tm1:1507940965660681,tm2:1507940965699605(38924),tm3:1507940965699813(39132),tm4:1507940965699845(39164)]****[tm4-tm0]:40485\nfinish 466 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37191\n467----rcs.size():6[tm0:1507940965730432,tm1:1507940965731769,tm2:1507940965770942(39173),tm3:1507940965771158(39389),tm4:1507940965771206(39437)]****[tm4-tm0]:40774\nfinish 467 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37075\n468----rcs.size():6[tm0:1507940965801863,tm1:1507940965803200,tm2:1507940965842277(39077),tm3:1507940965842489(39289),tm4:1507940965842536(39336)]****[tm4-tm0]:40673\nfinish 468 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36996\n469----rcs.size():6[tm0:1507940965873174,tm1:1507940965874743,tm2:1507940965913894(39151),tm3:1507940965914105(39362),tm4:1507940965914148(39405)]****[tm4-tm0]:40974\nfinish 469 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37252\n470----rcs.size():6[tm0:1507940965948510,tm1:1507940965949846,tm2:1507940965988802(38956),tm3:1507940965989056(39210),tm4:1507940965989100(39254)]****[tm4-tm0]:40590\nfinish 470 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38033\n471----rcs.size():6[tm0:1507940966019638,tm1:1507940966020974,tm2:1507940966060751(39777),tm3:1507940966060977(40003),tm4:1507940966061118(40144)]****[tm4-tm0]:41480\nfinish 471 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37311\n472----rcs.size():6[tm0:1507940966091622,tm1:1507940966093056,tm2:1507940966132213(39157),tm3:1507940966132428(39372),tm4:1507940966132470(39414)]****[tm4-tm0]:40848\nfinish 472 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38286\n473----rcs.size():5[tm0:1507940966163711,tm1:1507940966165033,tm2:1507940966205274(40241),tm3:1507940966205473(40440),tm4:1507940966205508(40475)]****[tm4-tm0]:41797\nfinish 473 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37346\n474----rcs.size():4[tm0:1507940966237041,tm1:1507940966238414,tm2:1507940966276928(38514),tm3:1507940966277103(38689),tm4:1507940966277135(38721)]****[tm4-tm0]:40094\nfinish 474 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37275\n475----rcs.size():5[tm0:1507940966308933,tm1:1507940966310273,tm2:1507940966348822(38549),tm3:1507940966349025(38752),tm4:1507940966349048(38775)]****[tm4-tm0]:40115\nfinish 475 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37363\n476----rcs.size():5[tm0:1507940966380614,tm1:1507940966381982,tm2:1507940966420825(38843),tm3:1507940966421029(39047),tm4:1507940966421152(39170)]****[tm4-tm0]:40538\nfinish 476 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37615\n477----rcs.size():6[tm0:1507940966452823,tm1:1507940966454253,tm2:1507940966493116(38863),tm3:1507940966493374(39121),tm4:1507940966493410(39157)]****[tm4-tm0]:40587\nfinish 477 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36853\n478----rcs.size():6[tm0:1507940966530240,tm1:1507940966531571,tm2:1507940966569780(38209),tm3:1507940966569998(38427),tm4:1507940966570035(38464)]****[tm4-tm0]:39795\nfinish 478 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37360\n479----rcs.size():6[tm0:1507940966601572,tm1:1507940966602939,tm2:1507940966642047(39108),tm3:1507940966642290(39351),tm4:1507940966642330(39391)]****[tm4-tm0]:40758\nfinish 479 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36863\n480----rcs.size():6[tm0:1507940966672322,tm1:1507940966673705,tm2:1507940966711977(38272),tm3:1507940966712177(38472),tm4:1507940966712217(38512)]****[tm4-tm0]:39895\nfinish 480 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36986\n481----rcs.size():6[tm0:1507940966744081,tm1:1507940966745546,tm2:1507940966784235(38689),tm3:1507940966784437(38891),tm4:1507940966784490(38944)]****[tm4-tm0]:40409\nfinish 481 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36852\n482----rcs.size():6[tm0:1507940966815498,tm1:1507940966816811,tm2:1507940966855614(38803),tm3:1507940966855813(39002),tm4:1507940966855844(39033)]****[tm4-tm0]:40346\nfinish 482 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37119\n483----rcs.size():6[tm0:1507940966886748,tm1:1507940966888115,tm2:1507940966926922(38807),tm3:1507940966927182(39067),tm4:1507940966927223(39108)]****[tm4-tm0]:40475\nfinish 483 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36861\n484----rcs.size():6[tm0:1507940966958453,tm1:1507940966959812,tm2:1507940966998322(38510),tm3:1507940966998534(38722),tm4:1507940966998565(38753)]****[tm4-tm0]:40112\nfinish 484 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37043\n485----rcs.size():6[tm0:1507940967030110,tm1:1507940967031460,tm2:1507940967070496(39036),tm3:1507940967070743(39283),tm4:1507940967070786(39326)]****[tm4-tm0]:40676\nfinish 485 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37552\n486----rcs.size():6[tm0:1507940967102754,tm1:1507940967104164,tm2:1507940967143642(39478),tm3:1507940967143828(39664),tm4:1507940967143875(39711)]****[tm4-tm0]:41121\nfinish 486 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37185\n487----rcs.size():6[tm0:1507940967179956,tm1:1507940967181299,tm2:1507940967220419(39120),tm3:1507940967220608(39309),tm4:1507940967220653(39354)]****[tm4-tm0]:40697\nfinish 487 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37199\n488----rcs.size():6[tm0:1507940967252787,tm1:1507940967254134,tm2:1507940967293196(39062),tm3:1507940967293386(39252),tm4:1507940967293431(39297)]****[tm4-tm0]:40644\nfinish 488 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37325\n489----rcs.size():6[tm0:1507940967329321,tm1:1507940967330709,tm2:1507940967369812(39103),tm3:1507940967370022(39313),tm4:1507940967370064(39355)]****[tm4-tm0]:40743\nfinish 489 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37744\n490----rcs.size():6[tm0:1507940967401095,tm1:1507940967402448,tm2:1507940967441921(39473),tm3:1507940967442147(39699),tm4:1507940967442190(39742)]****[tm4-tm0]:41095\nfinish 490 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37729\n491----rcs.size():6[tm0:1507940967474519,tm1:1507940967475918,tm2:1507940967515420(39502),tm3:1507940967515629(39711),tm4:1507940967515672(39754)]****[tm4-tm0]:41153\nfinish 491 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37606\n492----rcs.size():6[tm0:1507940967547180,tm1:1507940967548576,tm2:1507940967588013(39437),tm3:1507940967588223(39647),tm4:1507940967588268(39692)]****[tm4-tm0]:41088\nfinish 492 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37853\n493----rcs.size():6[tm0:1507940967619451,tm1:1507940967620742,tm2:1507940967660998(40256),tm3:1507940967661223(40481),tm4:1507940967661269(40527)]****[tm4-tm0]:41818\nfinish 493 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38072\n494----rcs.size():6[tm0:1507940967693345,tm1:1507940967694654,tm2:1507940967735298(40644),tm3:1507940967735541(40887),tm4:1507940967735588(40934)]****[tm4-tm0]:42243\nfinish 494 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37483\n495----rcs.size():6[tm0:1507940967772213,tm1:1507940967773750,tm2:1507940967813737(39987),tm3:1507940967814016(40266),tm4:1507940967814080(40330)]****[tm4-tm0]:41867\nfinish 495 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37996\n496----rcs.size():6[tm0:1507940967848818,tm1:1507940967850214,tm2:1507940967890399(40185),tm3:1507940967890624(40410),tm4:1507940967890780(40566)]****[tm4-tm0]:41962\nfinish 496 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38544\n497----rcs.size():6[tm0:1507940967925701,tm1:1507940967927046,tm2:1507940967967793(40747),tm3:1507940967968019(40973),tm4:1507940967968184(41138)]****[tm4-tm0]:42483\nfinish 497 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38381\n498----rcs.size():6[tm0:1507940967999719,tm1:1507940968001099,tm2:1507940968042050(40951),tm3:1507940968042272(41173),tm4:1507940968042432(41333)]****[tm4-tm0]:42713\nfinish 498 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37018\n499----rcs.size():6[tm0:1507940968073698,tm1:1507940968075237,tm2:1507940968114369(39132),tm3:1507940968114600(39363),tm4:1507940968114734(39497)]****[tm4-tm0]:41036\nfinish 499 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37803\n500----rcs.size():6[tm0:1507940968146110,tm1:1507940968147506,tm2:1507940968187695(40189),tm3:1507940968187936(40430),tm4:1507940968188076(40570)]****[tm4-tm0]:41966\nfinish 500 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37377\n501----rcs.size():6[tm0:1507940968220183,tm1:1507940968221548,tm2:1507940968260859(39311),tm3:1507940968261090(39542),tm4:1507940968261235(39687)]****[tm4-tm0]:41052\nfinish 501 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37736\n502----rcs.size():6[tm0:1507940968291470,tm1:1507940968292929,tm2:1507940968332950(40021),tm3:1507940968333234(40305),tm4:1507940968333394(40465)]****[tm4-tm0]:41924\nfinish 502 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36242\n503----rcs.size():5[tm0:1507940968364198,tm1:1507940968365648,tm2:1507940968402899(37251),tm3:1507940968403100(37452),tm4:1507940968403208(37560)]****[tm4-tm0]:39010\nfinish 503 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36472\n504----rcs.size():5[tm0:1507940968438339,tm1:1507940968439023,tm2:1507940968476058(37035),tm3:1507940968476248(37225),tm4:1507940968476355(37332)]****[tm4-tm0]:38016\nfinish 504 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35789\n505----rcs.size():5[tm0:1507940968506352,tm1:1507940968507317,tm2:1507940968543656(36339),tm3:1507940968543840(36523),tm4:1507940968543946(36629)]****[tm4-tm0]:37594\nfinish 505 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36153\n506----rcs.size():5[tm0:1507940968573653,tm1:1507940968574440,tm2:1507940968611167(36727),tm3:1507940968611357(36917),tm4:1507940968611467(37027)]****[tm4-tm0]:37814\nfinish 506 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35783\n507----rcs.size():5[tm0:1507940968641647,tm1:1507940968642351,tm2:1507940968678668(36317),tm3:1507940968678857(36506),tm4:1507940968678972(36621)]****[tm4-tm0]:37325\nfinish 507 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35545\n508----rcs.size():5[tm0:1507940968709110,tm1:1507940968709673,tm2:1507940968745643(35970),tm3:1507940968745797(36124),tm4:1507940968745911(36238)]****[tm4-tm0]:36801\nfinish 508 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35609\n509----rcs.size():5[tm0:1507940968778221,tm1:1507940968778901,tm2:1507940968814989(36088),tm3:1507940968815171(36270),tm4:1507940968815284(36383)]****[tm4-tm0]:37063\nfinish 509 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35775\n510----rcs.size():5[tm0:1507940968849012,tm1:1507940968849706,tm2:1507940968885969(36263),tm3:1507940968886134(36428),tm4:1507940968886176(36470)]****[tm4-tm0]:37164\nfinish 510 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:35759\n511----rcs.size():5[tm0:1507940968919561,tm1:1507940968920141,tm2:1507940968956350(36209),tm3:1507940968956523(36382),tm4:1507940968956549(36408)]****[tm4-tm0]:36988\nfinish 511 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:35824\n512----rcs.size():5[tm0:1507940968985691,tm1:1507940968986272,tm2:1507940969022663(36391),tm3:1507940969022822(36550),tm4:1507940969022940(36668)]****[tm4-tm0]:37249\nfinish 512 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36010\n513----rcs.size():5[tm0:1507940969053440,tm1:1507940969053997,tm2:1507940969090510(36513),tm3:1507940969090740(36743),tm4:1507940969090860(36863)]****[tm4-tm0]:37420\nfinish 513 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36148\n514----rcs.size():5[tm0:1507940969120844,tm1:1507940969121428,tm2:1507940969158091(36663),tm3:1507940969158277(36849),tm4:1507940969158304(36876)]****[tm4-tm0]:37460\nfinish 514 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37090\n515----rcs.size():4[tm0:1507940969190564,tm1:1507940969191313,tm2:1507940969229416(38103),tm3:1507940969229590(38277),tm4:1507940969229621(38308)]****[tm4-tm0]:39057\nfinish 515 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36498\n516----rcs.size():5[tm0:1507940969261467,tm1:1507940969262832,tm2:1507940969300946(38114),tm3:1507940969301187(38355),tm4:1507940969301217(38385)]****[tm4-tm0]:39750\nfinish 516 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36347\n517----rcs.size():5[tm0:1507940969333755,tm1:1507940969335223,tm2:1507940969372997(37774),tm3:1507940969373240(38017),tm4:1507940969373341(38118)]****[tm4-tm0]:39586\nfinish 517 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36564\n518----rcs.size():5[tm0:1507940969404681,tm1:1507940969406105,tm2:1507940969443993(37888),tm3:1507940969444235(38130),tm4:1507940969444359(38254)]****[tm4-tm0]:39678\nfinish 518 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37104\n519----rcs.size():5[tm0:1507940969477684,tm1:1507940969479051,tm2:1507940969517711(38660),tm3:1507940969517868(38817),tm4:1507940969517904(38853)]****[tm4-tm0]:40220\nfinish 519 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36583\n520----rcs.size():5[tm0:1507940969551513,tm1:1507940969552904,tm2:1507940969590975(38071),tm3:1507940969591161(38257),tm4:1507940969591197(38293)]****[tm4-tm0]:39684\nfinish 520 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36989\n521----rcs.size():5[tm0:1507940969622786,tm1:1507940969624584,tm2:1507940969663287(38703),tm3:1507940969663530(38946),tm4:1507940969663569(38985)]****[tm4-tm0]:40783\nfinish 521 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37397\n522----rcs.size():5[tm0:1507940969695517,tm1:1507940969696892,tm2:1507940969735412(38520),tm3:1507940969735647(38755),tm4:1507940969735687(38795)]****[tm4-tm0]:40170\nfinish 522 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36400\n523----rcs.size():5[tm0:1507940969767093,tm1:1507940969768535,tm2:1507940969806506(37971),tm3:1507940969806685(38150),tm4:1507940969806723(38188)]****[tm4-tm0]:39630\nfinish 523 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36532\n524----rcs.size():5[tm0:1507940969838134,tm1:1507940969839581,tm2:1507940969878044(38463),tm3:1507940969878220(38639),tm4:1507940969878257(38676)]****[tm4-tm0]:40123\nfinish 524 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37252\n525----rcs.size():5[tm0:1507940969909887,tm1:1507940969911203,tm2:1507940969949701(38498),tm3:1507940969949883(38680),tm4:1507940969949921(38718)]****[tm4-tm0]:40034\nfinish 525 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37209\n526----rcs.size():5[tm0:1507940969981857,tm1:1507940969983271,tm2:1507940970021748(38477),tm3:1507940970021934(38663),tm4:1507940970021971(38700)]****[tm4-tm0]:40114\nfinish 526 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37402\n527----rcs.size():5[tm0:1507940970053577,tm1:1507940970054930,tm2:1507940970093702(38772),tm3:1507940970093887(38957),tm4:1507940970093928(38998)]****[tm4-tm0]:40351\nfinish 527 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37329\n528----rcs.size():5[tm0:1507940970125625,tm1:1507940970126945,tm2:1507940970166443(39498),tm3:1507940970166644(39699),tm4:1507940970166683(39738)]****[tm4-tm0]:41058\nfinish 528 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:36997\n529----rcs.size():5[tm0:1507940970198452,tm1:1507940970199859,tm2:1507940970238472(38613),tm3:1507940970238659(38800),tm4:1507940970238695(38836)]****[tm4-tm0]:40243\nfinish 529 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37331\n530----rcs.size():5[tm0:1507940970270449,tm1:1507940970271852,tm2:1507940970311107(39255),tm3:1507940970311304(39452),tm4:1507940970311344(39492)]****[tm4-tm0]:40895\nfinish 530 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37497\n531----rcs.size():5[tm0:1507940970344110,tm1:1507940970345497,tm2:1507940970384682(39185),tm3:1507940970384853(39356),tm4:1507940970384896(39399)]****[tm4-tm0]:40786\nfinish 531 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37726\n532----rcs.size():5[tm0:1507940970416788,tm1:1507940970418266,tm2:1507940970457877(39611),tm3:1507940970458070(39804),tm4:1507940970458116(39850)]****[tm4-tm0]:41328\nfinish 532 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37113\n533----rcs.size():5[tm0:1507940970489541,tm1:1507940970491257,tm2:1507940970530082(38825),tm3:1507940970530311(39054),tm4:1507940970530351(39094)]****[tm4-tm0]:40810\nfinish 533 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37359\n534----rcs.size():5[tm0:1507940970562744,tm1:1507940970564202,tm2:1507940970603357(39155),tm3:1507940970603548(39346),tm4:1507940970603588(39386)]****[tm4-tm0]:40844\nfinish 534 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37610\n535----rcs.size():5[tm0:1507940970635539,tm1:1507940970636991,tm2:1507940970676375(39384),tm3:1507940970676549(39558),tm4:1507940970676608(39617)]****[tm4-tm0]:41069\nfinish 535 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37618\n536----rcs.size():4[tm0:1507940970708258,tm1:1507940970709603,tm2:1507940970749191(39588),tm3:1507940970749354(39751),tm4:1507940970749390(39787)]****[tm4-tm0]:41132\nfinish 536 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37365\n537----rcs.size():4[tm0:1507940970779757,tm1:1507940970781255,tm2:1507940970820549(39294),tm3:1507940970820705(39450),tm4:1507940970820741(39486)]****[tm4-tm0]:40984\nfinish 537 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37457\n538----rcs.size():4[tm0:1507940970851032,tm1:1507940970852445,tm2:1507940970891887(39442),tm3:1507940970892043(39598),tm4:1507940970892083(39638)]****[tm4-tm0]:41051\nfinish 538 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37419\n539----rcs.size():4[tm0:1507940970922397,tm1:1507940970923930,tm2:1507940970963469(39539),tm3:1507940970963625(39695),tm4:1507940970963662(39732)]****[tm4-tm0]:41265\nfinish 539 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37357\n540----rcs.size():4[tm0:1507940970994264,tm1:1507940970995666,tm2:1507940971034918(39252),tm3:1507940971035057(39391),tm4:1507940971035093(39427)]****[tm4-tm0]:40829\nfinish 540 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37607\n541----rcs.size():5[tm0:1507940971066191,tm1:1507940971067555,tm2:1507940971107306(39751),tm3:1507940971107513(39958),tm4:1507940971107550(39995)]****[tm4-tm0]:41359\nfinish 541 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37439\n542----rcs.size():5[tm0:1507940971138093,tm1:1507940971139677,tm2:1507940971179448(39771),tm3:1507940971179646(39969),tm4:1507940971179689(40012)]****[tm4-tm0]:41596\nfinish 542 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37785\n543----rcs.size():5[tm0:1507940971209889,tm1:1507940971211245,tm2:1507940971251346(40101),tm3:1507940971251546(40301),tm4:1507940971251589(40344)]****[tm4-tm0]:41700\nfinish 543 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37978\n544----rcs.size():5[tm0:1507940971282236,tm1:1507940971283634,tm2:1507940971323782(40148),tm3:1507940971323995(40361),tm4:1507940971324038(40404)]****[tm4-tm0]:41802\nfinish 544 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37825\n545----rcs.size():5[tm0:1507940971354229,tm1:1507940971355597,tm2:1507940971395630(40033),tm3:1507940971395844(40247),tm4:1507940971395877(40280)]****[tm4-tm0]:41648\nfinish 545 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37808\n546----rcs.size():5[tm0:1507940971432427,tm1:1507940971433892,tm2:1507940971474238(40346),tm3:1507940971474449(40557),tm4:1507940971474480(40588)]****[tm4-tm0]:42053\nfinish 546 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37858\n547----rcs.size():5[tm0:1507940971506281,tm1:1507940971507773,tm2:1507940971547958(40185),tm3:1507940971548158(40385),tm4:1507940971548189(40416)]****[tm4-tm0]:41908\nfinish 547 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38068\n548----rcs.size():5[tm0:1507940971579344,tm1:1507940971580733,tm2:1507940971621329(40596),tm3:1507940971621520(40787),tm4:1507940971621683(40950)]****[tm4-tm0]:42339\nfinish 548 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38588\n549----rcs.size():5[tm0:1507940971652754,tm1:1507940971654409,tm2:1507940971695531(41122),tm3:1507940971695733(41324),tm4:1507940971695900(41491)]****[tm4-tm0]:43146\nfinish 549 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38165\n550----rcs.size():5[tm0:1507940971726182,tm1:1507940971727483,tm2:1507940971767810(40327),tm3:1507940971767998(40515),tm4:1507940971768044(40561)]****[tm4-tm0]:41862\nfinish 550 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38111\n551----rcs.size():5[tm0:1507940971799872,tm1:1507940971801192,tm2:1507940971842109(40917),tm3:1507940971842308(41116),tm4:1507940971842339(41147)]****[tm4-tm0]:42467\nfinish 551 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38239\n552----rcs.size():5[tm0:1507940971870461,tm1:1507940971871004,tm2:1507940971912351(41347),tm3:1507940971912532(41528),tm4:1507940971912567(41563)]****[tm4-tm0]:42106\nfinish 552 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38236\n553----rcs.size():5[tm0:1507940971941446,tm1:1507940971942014,tm2:1507940971982886(40872),tm3:1507940971983063(41049),tm4:1507940971983096(41082)]****[tm4-tm0]:41650\nfinish 553 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38054\n554----rcs.size():5[tm0:1507940972011937,tm1:1507940972012525,tm2:1507940972053218(40693),tm3:1507940972053400(40875),tm4:1507940972053432(40907)]****[tm4-tm0]:41495\nfinish 554 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38894\n555----rcs.size():5[tm0:1507940972087208,tm1:1507940972087786,tm2:1507940972129699(41913),tm3:1507940972129892(42106),tm4:1507940972129922(42136)]****[tm4-tm0]:42714\nfinish 555 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38361\n556----rcs.size():5[tm0:1507940972158731,tm1:1507940972159306,tm2:1507940972200412(41106),tm3:1507940972200596(41290),tm4:1507940972200626(41320)]****[tm4-tm0]:41895\nfinish 556 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37427\n557----rcs.size():5[tm0:1507940972229532,tm1:1507940972230130,tm2:1507940972269772(39642),tm3:1507940972269988(39858),tm4:1507940972270150(40020)]****[tm4-tm0]:40618\nfinish 557 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38038\n558----rcs.size():5[tm0:1507940972300193,tm1:1507940972301524,tm2:1507940972341390(39866),tm3:1507940972341603(40079),tm4:1507940972341755(40231)]****[tm4-tm0]:41562\nfinish 558 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38500\n559----rcs.size():5[tm0:1507940972371414,tm1:1507940972372868,tm2:1507940972414615(41747),tm3:1507940972414820(41952),tm4:1507940972414989(42121)]****[tm4-tm0]:43575\nfinish 559 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36825\n560----rcs.size():4[tm0:1507940972444680,tm1:1507940972446016,tm2:1507940972484622(38606),tm3:1507940972484806(38790),tm4:1507940972484933(38917)]****[tm4-tm0]:40253\nfinish 560 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37552\n561----rcs.size():4[tm0:1507940972518667,tm1:1507940972520023,tm2:1507940972559591(39568),tm3:1507940972559728(39705),tm4:1507940972559858(39835)]****[tm4-tm0]:41191\nfinish 561 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37333\n562----rcs.size():4[tm0:1507940972589623,tm1:1507940972590975,tm2:1507940972630211(39236),tm3:1507940972630364(39389),tm4:1507940972630497(39522)]****[tm4-tm0]:40874\nfinish 562 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37424\n563----rcs.size():4[tm0:1507940972660380,tm1:1507940972661750,tm2:1507940972701105(39355),tm3:1507940972701255(39505),tm4:1507940972701389(39639)]****[tm4-tm0]:41009\nfinish 563 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37803\n564----rcs.size():4[tm0:1507940972731472,tm1:1507940972732814,tm2:1507940972772752(39938),tm3:1507940972772899(40085),tm4:1507940972772924(40110)]****[tm4-tm0]:41452\nfinish 564 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37738\n565----rcs.size():4[tm0:1507940972802323,tm1:1507940972803621,tm2:1507940972843325(39704),tm3:1507940972843474(39853),tm4:1507940972843500(39879)]****[tm4-tm0]:41177\nfinish 565 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37764\n566----rcs.size():4[tm0:1507940972874314,tm1:1507940972875756,tm2:1507940972915668(39912),tm3:1507940972915826(40070),tm4:1507940972915855(40099)]****[tm4-tm0]:41541\nfinish 566 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38264\n567----rcs.size():4[tm0:1507940972947516,tm1:1507940972948891,tm2:1507940972989100(40209),tm3:1507940972989250(40359),tm4:1507940972989289(40398)]****[tm4-tm0]:41773\nfinish 567 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37980\n568----rcs.size():4[tm0:1507940973023850,tm1:1507940973025302,tm2:1507940973065261(39959),tm3:1507940973065407(40105),tm4:1507940973065443(40141)]****[tm4-tm0]:41593\nfinish 568 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37755\n569----rcs.size():4[tm0:1507940973100141,tm1:1507940973101468,tm2:1507940973141301(39833),tm3:1507940973141435(39967),tm4:1507940973141460(39992)]****[tm4-tm0]:41319\nfinish 569 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36659\n570----rcs.size():4[tm0:1507940973175027,tm1:1507940973176384,tm2:1507940973215015(38631),tm3:1507940973215184(38800),tm4:1507940973215211(38827)]****[tm4-tm0]:40184\nfinish 570 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38092\n571----rcs.size():4[tm0:1507940973250262,tm1:1507940973251605,tm2:1507940973291607(40002),tm3:1507940973291753(40148),tm4:1507940973291792(40187)]****[tm4-tm0]:41530\nfinish 571 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37818\n572----rcs.size():4[tm0:1507940973322527,tm1:1507940973324012,tm2:1507940973364363(40351),tm3:1507940973364509(40497),tm4:1507940973364544(40532)]****[tm4-tm0]:42017\nfinish 572 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37362\n573----rcs.size():4[tm0:1507940973395520,tm1:1507940973396986,tm2:1507940973436451(39465),tm3:1507940973436600(39614),tm4:1507940973436634(39648)]****[tm4-tm0]:41114\nfinish 573 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36822\n574----rcs.size():3[tm0:1507940973469594,tm1:1507940973470979,tm2:1507940973509761(38782),tm3:1507940973509914(38935),tm4:1507940973509940(38961)]****[tm4-tm0]:40346\nfinish 574 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36636\n575----rcs.size():3[tm0:1507940973541794,tm1:1507940973543172,tm2:1507940973581327(38155),tm3:1507940973581452(38280),tm4:1507940973581479(38307)]****[tm4-tm0]:39685\nfinish 575 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36773\n576----rcs.size():3[tm0:1507940973613281,tm1:1507940973614764,tm2:1507940973653390(38626),tm3:1507940973653499(38735),tm4:1507940973653521(38757)]****[tm4-tm0]:40240\nfinish 576 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36626\n577----rcs.size():3[tm0:1507940973686036,tm1:1507940973687437,tm2:1507940973725790(38353),tm3:1507940973725901(38464),tm4:1507940973725928(38491)]****[tm4-tm0]:39892\nfinish 577 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36595\n578----rcs.size():3[tm0:1507940973757772,tm1:1507940973759142,tm2:1507940973797277(38135),tm3:1507940973797392(38250),tm4:1507940973797496(38354)]****[tm4-tm0]:39724\nfinish 578 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36513\n579----rcs.size():3[tm0:1507940973831595,tm1:1507940973832964,tm2:1507940973871337(38373),tm3:1507940973871468(38504),tm4:1507940973871496(38532)]****[tm4-tm0]:39901\nfinish 579 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36467\n580----rcs.size():3[tm0:1507940973906785,tm1:1507940973908169,tm2:1507940973946500(38331),tm3:1507940973946616(38447),tm4:1507940973946720(38551)]****[tm4-tm0]:39935\nfinish 580 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36991\n581----rcs.size():3[tm0:1507940973983115,tm1:1507940973984496,tm2:1507940974023442(38946),tm3:1507940974023575(39079),tm4:1507940974023605(39109)]****[tm4-tm0]:40490\nfinish 581 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37128\n582----rcs.size():3[tm0:1507940974058623,tm1:1507940974059997,tm2:1507940974098638(38641),tm3:1507940974098796(38799),tm4:1507940974098839(38842)]****[tm4-tm0]:40216\nfinish 582 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36911\n583----rcs.size():3[tm0:1507940974130484,tm1:1507940974131884,tm2:1507940974170711(38827),tm3:1507940974170844(38960),tm4:1507940974170872(38988)]****[tm4-tm0]:40388\nfinish 583 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37243\n584----rcs.size():3[tm0:1507940974202012,tm1:1507940974203327,tm2:1507940974242510(39183),tm3:1507940974242639(39312),tm4:1507940974242672(39345)]****[tm4-tm0]:40660\nfinish 584 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36812\n585----rcs.size():3[tm0:1507940974274561,tm1:1507940974275872,tm2:1507940974314164(38292),tm3:1507940974314276(38404),tm4:1507940974314298(38426)]****[tm4-tm0]:39737\nfinish 585 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36674\n586----rcs.size():3[tm0:1507940974344996,tm1:1507940974346290,tm2:1507940974384333(38043),tm3:1507940974384478(38188),tm4:1507940974384501(38211)]****[tm4-tm0]:39505\nfinish 586 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36728\n587----rcs.size():3[tm0:1507940974415078,tm1:1507940974416368,tm2:1507940974454935(38567),tm3:1507940974455063(38695),tm4:1507940974455086(38718)]****[tm4-tm0]:40008\nfinish 587 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37015\n588----rcs.size():3[tm0:1507940974486374,tm1:1507940974487760,tm2:1507940974527156(39396),tm3:1507940974527277(39517),tm4:1507940974527309(39549)]****[tm4-tm0]:40935\nfinish 588 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37077\n589----rcs.size():3[tm0:1507940974562608,tm1:1507940974564258,tm2:1507940974603416(39158),tm3:1507940974603554(39296),tm4:1507940974603587(39329)]****[tm4-tm0]:40979\nfinish 589 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37631\n590----rcs.size():3[tm0:1507940974634973,tm1:1507940974636368,tm2:1507940974675776(39408),tm3:1507940974675912(39544),tm4:1507940974676030(39662)]****[tm4-tm0]:41057\nfinish 590 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37437\n591----rcs.size():3[tm0:1507940974708124,tm1:1507940974709499,tm2:1507940974748811(39312),tm3:1507940974748933(39434),tm4:1507940974748966(39467)]****[tm4-tm0]:40842\nfinish 591 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36730\n592----rcs.size():3[tm0:1507940974781053,tm1:1507940974782312,tm2:1507940974821056(38744),tm3:1507940974821200(38888),tm4:1507940974821223(38911)]****[tm4-tm0]:40170\nfinish 592 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36988\n593----rcs.size():3[tm0:1507940974852008,tm1:1507940974853276,tm2:1507940974892192(38916),tm3:1507940974892326(39050),tm4:1507940974892349(39073)]****[tm4-tm0]:40341\nfinish 593 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37326\n594----rcs.size():3[tm0:1507940974923343,tm1:1507940974924685,tm2:1507940974963666(38981),tm3:1507940974963799(39114),tm4:1507940974963826(39141)]****[tm4-tm0]:40483\nfinish 594 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37431\n595----rcs.size():3[tm0:1507940974995768,tm1:1507940974997182,tm2:1507940975036462(39280),tm3:1507940975036605(39423),tm4:1507940975036638(39456)]****[tm4-tm0]:40870\nfinish 595 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37621\n596----rcs.size():3[tm0:1507940975067535,tm1:1507940975068850,tm2:1507940975108375(39525),tm3:1507940975108515(39665),tm4:1507940975108550(39700)]****[tm4-tm0]:41015\nfinish 596 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37812\n597----rcs.size():3[tm0:1507940975139261,tm1:1507940975140654,tm2:1507940975180626(39972),tm3:1507940975180770(40116),tm4:1507940975180804(40150)]****[tm4-tm0]:41543\nfinish 597 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37390\n598----rcs.size():3[tm0:1507940975211811,tm1:1507940975213106,tm2:1507940975252712(39606),tm3:1507940975252842(39736),tm4:1507940975252877(39771)]****[tm4-tm0]:41066\nfinish 598 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38710\n599----rcs.size():3[tm0:1507940975283451,tm1:1507940975284757,tm2:1507940975325626(40869),tm3:1507940975325786(41029),tm4:1507940975325821(41064)]****[tm4-tm0]:42370\nfinish 599 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37844\n600----rcs.size():3[tm0:1507940975356440,tm1:1507940975357871,tm2:1507940975397910(40039),tm3:1507940975398039(40168),tm4:1507940975398075(40204)]****[tm4-tm0]:41635\nfinish 600 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37592\n601----rcs.size():3[tm0:1507940975430504,tm1:1507940975431785,tm2:1507940975471653(39868),tm3:1507940975471783(39998),tm4:1507940975471820(40035)]****[tm4-tm0]:41316\nfinish 601 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38683\n602----rcs.size():3[tm0:1507940975501604,tm1:1507940975502939,tm2:1507940975543664(40725),tm3:1507940975543791(40852),tm4:1507940975543827(40888)]****[tm4-tm0]:42223\nfinish 602 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38072\n603----rcs.size():3[tm0:1507940975573950,tm1:1507940975575274,tm2:1507940975615255(39981),tm3:1507940975615403(40129),tm4:1507940975615437(40163)]****[tm4-tm0]:41487\nfinish 603 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37937\n604----rcs.size():3[tm0:1507940975650048,tm1:1507940975651354,tm2:1507940975691253(39899),tm3:1507940975691421(40067),tm4:1507940975691453(40099)]****[tm4-tm0]:41405\nfinish 604 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37770\n605----rcs.size():3[tm0:1507940975722058,tm1:1507940975723515,tm2:1507940975763764(40249),tm3:1507940975763896(40381),tm4:1507940975763928(40413)]****[tm4-tm0]:41870\nfinish 605 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38045\n606----rcs.size():2[tm0:1507940975794265,tm1:1507940975795572,tm2:1507940975835610(40038),tm3:1507940975835735(40163),tm4:1507940975835763(40191)]****[tm4-tm0]:41498\nfinish 606 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38339\n607----rcs.size():2[tm0:1507940975865727,tm1:1507940975867043,tm2:1507940975907515(40472),tm3:1507940975907612(40569),tm4:1507940975907638(40595)]****[tm4-tm0]:41911\nfinish 607 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38558\n608----rcs.size():2[tm0:1507940975937487,tm1:1507940975939025,tm2:1507940975981494(42469),tm3:1507940975981570(42545),tm4:1507940975981588(42563)]****[tm4-tm0]:44101\nfinish 608 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38805\n609----rcs.size():2[tm0:1507940976012019,tm1:1507940976012683,tm2:1507940976055695(43012),tm3:1507940976055771(43088),tm4:1507940976055790(43107)]****[tm4-tm0]:43771\nfinish 609 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38877\n610----rcs.size():2[tm0:1507940976086745,tm1:1507940976087393,tm2:1507940976130894(43501),tm3:1507940976130977(43584),tm4:1507940976131007(43614)]****[tm4-tm0]:44262\nfinish 610 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38867\n611----rcs.size():2[tm0:1507940976164279,tm1:1507940976164818,tm2:1507940976207926(43108),tm3:1507940976208022(43204),tm4:1507940976208049(43231)]****[tm4-tm0]:43770\nfinish 611 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39485\n612----rcs.size():2[tm0:1507940976237964,tm1:1507940976238880,tm2:1507940976282750(43870),tm3:1507940976282825(43945),tm4:1507940976282843(43963)]****[tm4-tm0]:44879\nfinish 612 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38683\n613----rcs.size():2[tm0:1507940976312516,tm1:1507940976313047,tm2:1507940976355549(42502),tm3:1507940976355628(42581),tm4:1507940976355648(42601)]****[tm4-tm0]:43132\nfinish 613 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39014\n614----rcs.size():2[tm0:1507940976386081,tm1:1507940976386649,tm2:1507940976430130(43481),tm3:1507940976430217(43568),tm4:1507940976430236(43587)]****[tm4-tm0]:44155\nfinish 614 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39211\n615----rcs.size():2[tm0:1507940976463716,tm1:1507940976464349,tm2:1507940976507798(43449),tm3:1507940976507881(43532),tm4:1507940976507928(43579)]****[tm4-tm0]:44212\nfinish 615 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39516\n616----rcs.size():2[tm0:1507940976540304,tm1:1507940976541006,tm2:1507940976584598(43592),tm3:1507940976584676(43670),tm4:1507940976584696(43690)]****[tm4-tm0]:44392\nfinish 616 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:39757\n617----rcs.size():2[tm0:1507940976614867,tm1:1507940976615436,tm2:1507940976659038(43602),tm3:1507940976659125(43689),tm4:1507940976659230(43794)]****[tm4-tm0]:44363\nfinish 617 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39309\n618----rcs.size():2[tm0:1507940976689538,tm1:1507940976690081,tm2:1507940976732901(42820),tm3:1507940976732985(42904),tm4:1507940976733012(42931)]****[tm4-tm0]:43474\nfinish 618 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39983\n619----rcs.size():2[tm0:1507940976768470,tm1:1507940976769014,tm2:1507940976813831(44817),tm3:1507940976813915(44901),tm4:1507940976814013(44999)]****[tm4-tm0]:45543\nfinish 619 frame\n(inpython)encode one frame cost time:t2-t1:1, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37222\n620----rcs.size():1[tm0:1507940976850157,tm1:1507940976850693,tm2:1507940976889806(39113),tm3:1507940976889884(39191),tm4:1507940976889929(39236)]****[tm4-tm0]:39772\nfinish 620 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:40119\n621----rcs.size():2[tm0:1507940976921550,tm1:1507940976923189,tm2:1507940976968750(45561),tm3:1507940976968836(45647),tm4:1507940976968933(45744)]****[tm4-tm0]:47383\nfinish 621 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:40533\n622----rcs.size():2[tm0:1507940976999222,tm1:1507940976999886,tm2:1507940977045210(45324),tm3:1507940977045298(45412),tm4:1507940977045402(45516)]****[tm4-tm0]:46180\nfinish 622 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:40212\n623----rcs.size():2[tm0:1507940977079956,tm1:1507940977080561,tm2:1507940977125658(45097),tm3:1507940977125745(45184),tm4:1507940977125850(45289)]****[tm4-tm0]:45894\nfinish 623 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:40598\n624----rcs.size():2[tm0:1507940977160011,tm1:1507940977160609,tm2:1507940977206704(46095),tm3:1507940977206784(46175),tm4:1507940977206804(46195)]****[tm4-tm0]:46793\nfinish 624 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39852\n625----rcs.size():2[tm0:1507940977237294,tm1:1507940977237914,tm2:1507940977283261(45347),tm3:1507940977283365(45451),tm4:1507940977283385(45471)]****[tm4-tm0]:46091\nfinish 625 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39681\n626----rcs.size():2[tm0:1507940977318977,tm1:1507940977319540,tm2:1507940977364933(45393),tm3:1507940977365020(45480),tm4:1507940977365048(45508)]****[tm4-tm0]:46071\nfinish 626 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:39193\n627----rcs.size():2[tm0:1507940977395731,tm1:1507940977396311,tm2:1507940977439430(43119),tm3:1507940977439519(43208),tm4:1507940977439546(43235)]****[tm4-tm0]:43815\nfinish 627 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38316\n628----rcs.size():1[tm0:1507940977470207,tm1:1507940977470840,tm2:1507940977511709(40869),tm3:1507940977511822(40982),tm4:1507940977511841(41001)]****[tm4-tm0]:41634\nfinish 628 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37471\n629----rcs.size():1[tm0:1507940977544707,tm1:1507940977546006,tm2:1507940977585682(39676),tm3:1507940977585735(39729),tm4:1507940977585750(39744)]****[tm4-tm0]:41043\nfinish 629 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38094\n630----rcs.size():1[tm0:1507940977616976,tm1:1507940977618354,tm2:1507940977658473(40119),tm3:1507940977658525(40171),tm4:1507940977658536(40182)]****[tm4-tm0]:41560\nfinish 630 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37489\n631----rcs.size():1[tm0:1507940977690175,tm1:1507940977691473,tm2:1507940977731235(39762),tm3:1507940977731304(39831),tm4:1507940977731333(39860)]****[tm4-tm0]:41158\nfinish 631 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:37879\n632----rcs.size():1[tm0:1507940977763995,tm1:1507940977765360,tm2:1507940977805607(40247),tm3:1507940977805660(40300),tm4:1507940977805675(40315)]****[tm4-tm0]:41680\nfinish 632 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38174\n633----rcs.size():1[tm0:1507940977837941,tm1:1507940977839618,tm2:1507940977880492(40874),tm3:1507940977880574(40956),tm4:1507940977880589(40971)]****[tm4-tm0]:42648\nfinish 633 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37977\n634----rcs.size():1[tm0:1507940977916526,tm1:1507940977917831,tm2:1507940977958212(40381),tm3:1507940977958266(40435),tm4:1507940977958281(40450)]****[tm4-tm0]:41755\nfinish 634 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38143\n635----rcs.size():1[tm0:1507940977989906,tm1:1507940977991337,tm2:1507940978031991(40654),tm3:1507940978032062(40725),tm4:1507940978032074(40737)]****[tm4-tm0]:42168\nfinish 635 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36742\n636----rcs.size():1[tm0:1507940978066432,tm1:1507940978067761,tm2:1507940978107095(39334),tm3:1507940978107161(39400),tm4:1507940978107177(39416)]****[tm4-tm0]:40745\nfinish 636 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38313\n637----rcs.size():1[tm0:1507940978137670,tm1:1507940978139248,tm2:1507940978180230(40982),tm3:1507940978180283(41035),tm4:1507940978180312(41064)]****[tm4-tm0]:42642\nfinish 637 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37955\n638----rcs.size():1[tm0:1507940978211224,tm1:1507940978212489,tm2:1507940978252568(40079),tm3:1507940978252653(40164),tm4:1507940978252665(40176)]****[tm4-tm0]:41441\nfinish 638 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38491\n639----rcs.size():1[tm0:1507940978282998,tm1:1507940978284291,tm2:1507940978325357(41066),tm3:1507940978325427(41136),tm4:1507940978325438(41147)]****[tm4-tm0]:42440\nfinish 639 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38188\n640----rcs.size():1[tm0:1507940978356425,tm1:1507940978357692,tm2:1507940978399146(41454),tm3:1507940978399215(41523),tm4:1507940978399227(41535)]****[tm4-tm0]:42802\nfinish 640 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37899\n641----rcs.size():1[tm0:1507940978430162,tm1:1507940978431427,tm2:1507940978471982(40555),tm3:1507940978472056(40629),tm4:1507940978472106(40679)]****[tm4-tm0]:41944\nfinish 641 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:34\n(incpp)call encode cost time:tmd-tmc:38980\n642----rcs.size():1[tm0:1507940978503785,tm1:1507940978505453,tm2:1507940978547660(42207),tm3:1507940978547718(42265),tm4:1507940978547769(42316)]****[tm4-tm0]:43984\nfinish 642 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38300\n643----rcs.size():1[tm0:1507940978579888,tm1:1507940978581208,tm2:1507940978622151(40943),tm3:1507940978622206(40998),tm4:1507940978622219(41011)]****[tm4-tm0]:42331\nfinish 643 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38770\n644----rcs.size():1[tm0:1507940978654032,tm1:1507940978655836,tm2:1507940978697415(41579),tm3:1507940978697473(41637),tm4:1507940978697486(41650)]****[tm4-tm0]:43454\nfinish 644 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38271\n645----rcs.size():1[tm0:1507940978729950,tm1:1507940978731315,tm2:1507940978772493(41178),tm3:1507940978772568(41253),tm4:1507940978772578(41263)]****[tm4-tm0]:42628\nfinish 645 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38521\n646----rcs.size():1[tm0:1507940978803026,tm1:1507940978804266,tm2:1507940978847106(42840),tm3:1507940978847169(42903),tm4:1507940978847180(42914)]****[tm4-tm0]:44154\nfinish 646 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:32\n(incpp)call encode cost time:tmd-tmc:37877\n647----rcs.size():1[tm0:1507940978877862,tm1:1507940978878410,tm2:1507940978919508(41098),tm3:1507940978919581(41171),tm4:1507940978919592(41182)]****[tm4-tm0]:41730\nfinish 647 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:38037\n648----rcs.size():1[tm0:1507940978950258,tm1:1507940978951541,tm2:1507940978991891(40350),tm3:1507940978991981(40440),tm4:1507940978991991(40450)]****[tm4-tm0]:41733\nfinish 648 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:37374\n649----rcs.size():1[tm0:1507940979024186,tm1:1507940979025423,tm2:1507940979064975(39552),tm3:1507940979065047(39624),tm4:1507940979065057(39634)]****[tm4-tm0]:40871\nfinish 649 frame\n(inpython)encode one frame cost time:t2-t1:0, t3-t1:33\n(incpp)call encode cost time:tmd-tmc:36864\n650----rcs.size():1[tm0:1507940979102104,tm1:1507940979103377,tm2:1507940979141779(38402),tm3:1507940979141879(38502),tm4:1507940979141888(38511)]****[tm4-tm0]:39784\nfinish 650 frame\n651----rcs.size():0[tm0:1507940979173738,tm1:1507940979174990,tm2:1507940979174990(0),tm3:1507940979174998(8),tm4:1507940979174999(9)][tm4-tm0]:1261\nfinish 651 frame\n652----rcs.size():0[tm0:1507940979209989,tm1:1507940979210517,tm2:1507940979210517(0),tm3:1507940979210525(8),tm4:1507940979210525(8)][tm4-tm0]:536\nfinish 652 frame\n653----rcs.size():0[tm0:1507940979244670,tm1:1507940979245184,tm2:1507940979245184(0),tm3:1507940979245191(7),tm4:1507940979245192(8)][tm4-tm0]:522\nfinish 653 frame\n654----rcs.size():0[tm0:1507940979279766,tm1:1507940979280296,tm2:1507940979280296(0),tm3:1507940979280304(8),tm4:1507940979280304(8)][tm4-tm0]:538\nfinish 654 frame\n655----rcs.size():0[tm0:1507940979315209,tm1:1507940979315784,tm2:1507940979315784(0),tm3:1507940979315792(8),tm4:1507940979315792(8)][tm4-tm0]:583\nfinish 655 frame\n656----rcs.size():0[tm0:1507940979350510,tm1:1507940979351045,tm2:1507940979351045(0),tm3:1507940979351053(8),tm4:1507940979351053(8)][tm4-tm0]:543\nfinish 656 frame\n657----rcs.size():0[tm0:1507940979385371,tm1:1507940979385971,tm2:1507940979385971(0),tm3:1507940979385979(8),tm4:1507940979385979(8)][tm4-tm0]:608\nfinish 657 frame\n658----rcs.size():0[tm0:1507940979420325,tm1:1507940979420898,tm2:1507940979420898(0),tm3:1507940979420906(8),tm4:1507940979420906(8)][tm4-tm0]:581\nfinish 658 frame\n659----rcs.size():0[tm0:1507940979455517,tm1:1507940979456197,tm2:1507940979456197(0),tm3:1507940979456203(6),tm4:1507940979456203(6)][tm4-tm0]:686\nfinish 659 frame\n660----rcs.size():0[tm0:1507940979490756,tm1:1507940979491266,tm2:1507940979491266(0),tm3:1507940979491272(6),tm4:1507940979491272(6)][tm4-tm0]:516\nfinish 660 frame\n661----rcs.size():0[tm0:1507940979525604,tm1:1507940979526130,tm2:1507940979526130(0),tm3:1507940979526138(8),tm4:1507940979526139(9)][tm4-tm0]:535\nfinish 661 frame\n662----rcs.size():0[tm0:1507940979560967,tm1:1507940979561516,tm2:1507940979561516(0),tm3:1507940979561522(6),tm4:1507940979561523(7)][tm4-tm0]:556\nfinish 662 frame\n663----rcs.size():0[tm0:1507940979595989,tm1:1507940979596602,tm2:1507940979596602(0),tm3:1507940979596609(7),tm4:1507940979596609(7)][tm4-tm0]:620\nfinish 663 frame\n664----rcs.size():0[tm0:1507940979631581,tm1:1507940979632146,tm2:1507940979632146(0),tm3:1507940979632152(6),tm4:1507940979632153(7)][tm4-tm0]:572\nfinish 664 frame\n665----rcs.size():0[tm0:1507940979666257,tm1:1507940979666851,tm2:1507940979666851(0),tm3:1507940979666856(5),tm4:1507940979666857(6)][tm4-tm0]:600\nfinish 665 frame\n666----rcs.size():0[tm0:1507940979701511,tm1:1507940979702019,tm2:1507940979702019(0),tm3:1507940979702025(6),tm4:1507940979702025(6)][tm4-tm0]:514\nfinish 666 frame\n667----rcs.size():0[tm0:1507940979736373,tm1:1507940979736883,tm2:1507940979736883(0),tm3:1507940979736889(6),tm4:1507940979736889(6)][tm4-tm0]:516\nfinish 667 frame\n668----rcs.size():0[tm0:1507940979771944,tm1:1507940979772588,tm2:1507940979772588(0),tm3:1507940979772610(22),tm4:1507940979772610(22)][tm4-tm0]:666\nfinish 668 frame\n669----rcs.size():0[tm0:1507940979808757,tm1:1507940979809306,tm2:1507940979809306(0),tm3:1507940979809311(5),tm4:1507940979809312(6)][tm4-tm0]:555\nfinish 669 frame\n670----rcs.size():0[tm0:1507940979844662,tm1:1507940979845291,tm2:1507940979845291(0),tm3:1507940979845297(6),tm4:1507940979845298(7)][tm4-tm0]:636\nfinish 670 frame\n671----rcs.size():0[tm0:1507940979880218,tm1:1507940979880778,tm2:1507940979880778(0),tm3:1507940979880784(6),tm4:1507940979880784(6)][tm4-tm0]:566\nfinish 671 frame\n672----rcs.size():0[tm0:1507940979916017,tm1:1507940979916538,tm2:1507940979916538(0),tm3:1507940979916544(6),tm4:1507940979916544(6)][tm4-tm0]:527\nfinish 672 frame\n673----rcs.size():0[tm0:1507940979951673,tm1:1507940979952203,tm2:1507940979952203(0),tm3:1507940979952208(5),tm4:1507940979952209(6)][tm4-tm0]:536\nfinish 673 frame\n674----rcs.size():0[tm0:1507940979988935,tm1:1507940979989512,tm2:1507940979989512(0),tm3:1507940979989518(6),tm4:1507940979989518(6)][tm4-tm0]:583\nfinish 674 frame\n675----rcs.size():0[tm0:1507940980024742,tm1:1507940980025273,tm2:1507940980025273(0),tm3:1507940980025279(6),tm4:1507940980025279(6)][tm4-tm0]:537\nfinish 675 frame\n676----rcs.size():0[tm0:1507940980059644,tm1:1507940980060174,tm2:1507940980060174(0),tm3:1507940980060179(5),tm4:1507940980060180(6)][tm4-tm0]:536\nfinish 676 frame\n677----rcs.size():0[tm0:1507940980094977,tm1:1507940980095506,tm2:1507940980095506(0),tm3:1507940980095512(6),tm4:1507940980095513(7)][tm4-tm0]:536\nfinish 677 frame\n678----rcs.size():0[tm0:1507940980132473,tm1:1507940980133053,tm2:1507940980133053(0),tm3:1507940980133059(6),tm4:1507940980133059(6)][tm4-tm0]:586\nfinish 678 frame\n679----rcs.size():0[tm0:1507940980169730,tm1:1507940980170293,tm2:1507940980170293(0),tm3:1507940980170299(6),tm4:1507940980170300(7)][tm4-tm0]:570\nfinish 679 frame\n"
  },
  {
    "path": "make.sh",
    "content": "#!/bin/bash\n\nfunction getbazel(){\n\tLINE=`readlink -f /home/$USER/code1/tensorflow-1.4.0-rc0/bazel-bin/`\n\n\tPOS1=\"_bazel_$USER/\"\n\tSTR=${LINE##*$POS1}\n\n\tBAZEL=${STR:0:32}\n\n\techo $BAZEL\n}\n\n\n\nBAZEL=`getbazel`\n\n\n\n\nIINCLUDE=\"-I/home/$USER/code/test/pp/opencvlib/include -I/usr/local/include -I/home/$USER/.cache/bazel/_bazel_$USER/$BAZEL/external/eigen_archive/Eigen -I/home/$USER/code1/tbb-2018_U1/include/tbb -I/home/$USER/code1/tbb-2018_U1/include\"\n\n\nLLIBPATH=\"-L/home/$USER/code/test/pp/opencvlib/lib -L/usr/local/lib -L/home/$USER/code1/DS/deepsort/FeatureGetter -L/home/$USER/code1/tbb-2018_U1/build/linux_intel64_gcc_cc5.4.0_libc2.17_kernel3.10.0_release \"\n\nrm DS -rf\n\n\nfunction BOPENMP(){\n\tLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz  -lopencv_highguixyz -lFeatureGetter -lboost_system -lglog -ltcmalloc\"\n\tg++ --std=c++14 -O3 -fopenmp -DUDL -o DS $IINCLUDE $LLIBPATH  deepsort/munkres/munkres.cpp deepsort/munkres/adapters/adapter.cpp deepsort/munkres/adapters/boostmatrixadapter.cpp  NT.cpp fdsst/fdssttracker.cpp fdsst/fhog.cpp Main.cpp $LLIBS\n}\n\n\nfunction BTBB(){\n\tLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz -lopencv_highguixyz -lFeatureGetter -lboost_system -lglog -ltbb\"\n\tg++ --std=c++14 -DUSETBB -o DS $IINCLUDE $LLIBPATH deepsort/munkres/munkres.cpp deepsort/munkres/adapters/adapter.cpp deepsort/munkres/adapters/boostmatrixadapter.cpp  NT.cpp Main.cpp $LLIBS\n}\n\n\nfunction BOPENMPHOG(){\n\tLLIBS=\"-lopencv_corexyz -lopencv_imgprocxyz  -lopencv_highguixyz  -lboost_system -lglog -ltcmalloc\"\n\tg++ --std=c++14 -O3 -fopenmp -o DS $IINCLUDE $LLIBPATH  deepsort/munkres/munkres.cpp deepsort/munkres/adapters/adapter.cpp deepsort/munkres/adapters/boostmatrixadapter.cpp  NT.cpp fdsst/fdssttracker.cpp fdsst/fhog.cpp Main.cpp $LLIBS\n}\n\nBOPENMPHOG\n\n\n\n\n"
  },
  {
    "path": "t.sh",
    "content": "#!/bin/bash\n\n\nps aux | grep DS | grep -v grep | awk '{print $2}'  | xargs -i -t kill -9 {}\n\n"
  }
]