Repository: Shreeshrii/tessdata_shreetest Branch: master Commit: 226419f02431 Files: 29 Total size: 122.1 MB Directory structure: gitextract_o6nios1q/ ├── README.md ├── ara-amiri-3000.traineddata ├── brah.traineddata ├── digits-finetune-makedata.sh ├── digits-finetune.sh ├── digits.traineddata ├── digits1.traineddata ├── digits_comma.traineddata ├── digits_layer.traineddata ├── digitsall_layer.sh ├── digitsall_layer.traineddata ├── dotslayer.traineddata ├── eng.digits.numbers ├── eng.digits.punc ├── eng.digits.training_text ├── engmorse.traineddata ├── engrestrict-finetune.sh ├── engrestrict-makedata.sh ├── engrestrict.training_text ├── engrestrict_best.traineddata ├── engrestrict_best_int.traineddata ├── fas-minus-float.traineddata ├── fas-plus-float.traineddata ├── fas-script-float.traineddata ├── fas-tune-float.traineddata ├── frk.traineddata ├── mya430000.traineddata ├── san-chandas-float.traineddata └── san-siddhanta-float.traineddata ================================================ FILE CONTENTS ================================================ ================================================ FILE: README.md ================================================ # tessdata_shreetest finetuned traineddata files for tesseract 4.0.0 for testing ### digits.traineddata * float model * finetuned with about 10 [Non-italic fonts from the list](https://github.com/Shreeshrii/tessdata_shreetest/issues/1#issuecomment-425947492) * finetuned with 3000 iterations from tessdata_best/eng.traineddata * unicharset has digits 0-9, dash sign and decimal point ### digits1.traineddata * float model * finetuned with Arial font * finetuned with 300 iterations from tessdata_best/eng.traineddata * unicharset has digits 0-9, dash sign and decimal point ### digits_comma.traineddata * float model * finetuned with 27 fonts listed in [comment](https://github.com/Shreeshrii/tessdata_shreetest/issues/1#issuecomment-425947492) * finetuned with 3000 iterations from tessdata_best/eng.traineddata * unicharset has digits 0-9, dash sign, decimal point and comma ================================================ FILE: ara-amiri-3000.traineddata ================================================ [File too large to display: 13.0 MB] ================================================ FILE: digits-finetune-makedata.sh ================================================ #!/bin/bash ~/tesseract/src/training/tesstrain.sh \ --fonts_dir ~/.fonts \ --lang eng --linedata_only \ --noextract_font_properties \ --langdata_dir ~/langdata \ --tessdata_dir ~/tessdata_best \ --training_text ./eng.digits.training_text \ --workspace_dir ~/tmp \ --output_dir ~/tesstutorial/digits \ --fontlist \ "Arial Bold" \ "Arial" \ "Courier New Bold" \ "Courier New" \ "Times New Roman, Bold" \ "Times New Roman," \ "Georgia Bold" \ "Georgia" \ "Trebuchet MS Bold" \ "Trebuchet MS" \ "Verdana Bold" \ "Verdana" \ "FreeSerif" \ "FreeMono" \ "FreeSans" rm -rf ~/tesstutorial/digits_from_full ================================================ FILE: digits-finetune.sh ================================================ #!/bin/bash echo "/n ****** Finetune one of the fully-trained existing models: ***********" ##########rm -rf ~/tesstutorial/digits_from_full mkdir -p ~/tesstutorial/digits_from_full combine_tessdata -e ~/tessdata_best/eng.traineddata \ ~/tesstutorial/digits_from_full/eng.lstm lstmtraining \ --model_output ~/tesstutorial/digits_from_full/digits_plus \ --traineddata ~/tesstutorial/digits/eng/eng.traineddata \ --continue_from ~/tesstutorial/digits_from_full/eng.lstm \ --old_traineddata ~/tessdata_best/eng.traineddata \ --train_listfile ~/tesstutorial/digits/eng.training_files.txt \ --debug_interval -1 \ --max_iterations 3000 lstmtraining \ --stop_training \ --traineddata ~/tesstutorial/digits/eng/eng.traineddata \ --continue_from ~/tesstutorial/digits_from_full/digits_plus_checkpoint \ --model_output digits_plus.traineddata lstmeval --model ~/tessdata_best/eng.traineddata --eval_listfile ~/tesstutorial/digits/eng.training_files.txt lstmeval --model ~/tessdata_best/script/Latin.traineddata --eval_listfile ~/tesstutorial/digits/eng.training_files.txt lstmeval --model ~/tesstutorial/digits_from_full/digits_plus_checkpoint --traineddata ~/tesstutorial/digits/eng/eng.traineddata --eval_listfile ~/tesstutorial/digits/eng.training_files.txt ================================================ FILE: digits.traineddata ================================================ [File too large to display: 10.8 MB] ================================================ FILE: digits1.traineddata ================================================ [File too large to display: 10.8 MB] ================================================ FILE: digits_comma.traineddata ================================================ [File too large to display: 10.8 MB] ================================================ FILE: digitsall_layer.sh ================================================ #!/bin/bash echo -e "\n ****** Finetune one of the fully-trained existing models: ***********" ~/tesseract/src/training/tesstrain.sh \ --fonts_dir ~/.fonts \ --lang eng --linedata_only \ --noextract_font_properties \ --langdata_dir ~/langdata \ --tessdata_dir ~/tessdata_best \ --training_text ./eng.digits.training_text \ --exposures "0" \ --save_box_tiff \ --distort_image true \ --maxpages 0 \ --workspace_dir ~/tmp \ --output_dir ~/tesstutorial/digitsalldistort \ --fontlist \ "Adobe Devanagari" \ "Akchyarunicode" \ "Aksharyogini2" \ "Amiri" \ "Annapurna SIL Bold" \ "Annapurna SIL" \ "Antinoou" \ "Arial Bold Italic" \ "Arial Bold" \ "Arial Condensed" \ "Arial Heavy" \ "Arial Italic" \ "Arial Unicode MS" \ "Arial" \ "Awami Nastaliq" \ "Book Antiqua Bold Italic" \ "Book Antiqua Bold" \ "Book Antiqua Italic" \ "Book Antiqua" \ "Bookman Old Style Light Italic" \ "Bookman Old Style Light" \ "Bookman Old Style Semi-Bold Italic" \ "Bookman Old Style Semi-Bold" \ "Calibri Bold Italic" \ "Calibri Bold" \ "Calibri Italic" \ "Calibri Light Italic" \ "Calibri Light" \ "Calibri" \ "Cambria Bold Italic" \ "Cambria Bold" \ "Cambria Italic" \ "Candara Bold Italic" \ "Candara Bold" \ "Candara Italic" \ "Candara" \ "Century Gothic Bold Italic" \ "Century Gothic Bold" \ "Century Gothic Italic" \ "Century Gothic" \ "Century Schoolbook Bold Italic" \ "Century Schoolbook Bold" \ "Century Schoolbook Italic" \ "Century Schoolbook" \ "Century" \ "Chandas" \ "Comic Sans MS Bold Italic" \ "Comic Sans MS Bold" \ "Comic Sans MS Italic" \ "Comic Sans MS" \ "Consolas Bold Italic" \ "Consolas Bold" \ "Consolas Italic" \ "Consolas" \ "Constantia Bold Italic" \ "Constantia Bold" \ "Constantia Italic" \ "Constantia" \ "Corbel Bold Italic" \ "Corbel Bold" \ "Corbel Italic" \ "Corbel" \ "Courier New Bold Italic" \ "Courier New Bold" \ "Courier New Italic" \ "Courier New" \ "Ebrima Bold" \ "Ebrima" \ "Ek Mukta Bold" \ "Ek Mukta Light" \ "Ek Mukta Medium" \ "Ek Mukta Semi-Bold" \ "Ek Mukta Ultra-Bold" \ "Ek Mukta" \ "Franklin Gothic Medium, Italic" \ "Franklin Gothic Medium," \ "FreeMono Bold Italic" \ "FreeMono Bold" \ "FreeMono Italic" \ "FreeMono" \ "FreeSans Italic" \ "FreeSans Semi-Bold Italic" \ "FreeSans Semi-Bold" \ "FreeSans" \ "FreeSerif Bold Italic" \ "FreeSerif Bold" \ "FreeSerif Italic" \ "FreeSerif" \ "FreeSerifAthanasius" \ "FreeSerifAvvaShenouda" \ "FreeSerifCopt" \ "FreeSerifCopticMS" \ "FreeSerifCoptoMS" \ "FreeSerifKoptosMS" \ "FreeSerifPishoi" \ "Gabriola" \ "Gadugi Bold" \ "Gadugi" \ "Garamond Bold" \ "Garamond Italic" \ "Garamond" \ "Georgia Bold Italic" \ "Georgia Bold" \ "Georgia Italic" \ "Georgia" \ "IFAO-Grec Unicode Bold" \ "IFAO-Grec Unicode" \ "Impact Condensed" \ "Javanese Text" \ "K24 Kurdish Light, Light" \ "Kristen ITC Semi-Expanded" \ "Leelawadee UI Bold" \ "Leelawadee UI Semi-Light" \ "Leelawadee UI" \ "Lohit Devanagari" \ "Lucida Console Semi-Condensed" \ "Lucida Sans Unicode" \ "MS Reference Sans Serif" \ "MV Boli" \ "Microsoft New Tai Lue Bold" \ "Microsoft New Tai Lue" \ "Microsoft PhagsPa Bold" \ "Microsoft PhagsPa" \ "Microsoft Sans Serif" \ "Microsoft Tai Le Bold" \ "Microsoft Tai Le" \ "Mistral" \ "Monotype Corsiva Italic" \ "Myanmar Text Bold" \ "Myanmar Text" \ "NRT Reg" \ "Nakula" \ "Nawatura beta" \ "New Athena Unicode Bold Italic" \ "New Athena Unicode Bold" \ "New Athena Unicode Italic" \ "New Athena Unicode" \ "New Kramawirya" \ "Nirmala UI Bold" \ "Nirmala UI Semi-Light" \ "Nirmala UI" \ "Palatino Linotype Bold Italic" \ "Palatino Linotype Bold" \ "Palatino Linotype Italic" \ "Palatino Linotype" \ "Prada" \ "Pringgandani" \ "Pristina" \ "RudawRegular" \ "SILDoulos PigLatinDemo" \ "Sahadeva" \ "Sahel" \ "Sakkal Majalla" \ "Segoe Print Bold" \ "Segoe Print" \ "Segoe Script Bold" \ "Segoe Script" \ "Segoe UI Bold Italic" \ "Segoe UI Bold" \ "Segoe UI Emoji" \ "Segoe UI Heavy Italic" \ "Segoe UI Heavy" \ "Segoe UI Italic" \ "Segoe UI Light Italic" \ "Segoe UI Light" \ "Segoe UI Semi-Bold Italic" \ "Segoe UI Semi-Bold" \ "Segoe UI Semi-Light Italic" \ "Segoe UI Semi-Light" \ "Segoe UI Symbol" \ "Segoe UI" \ "Shobhika Bold" \ "Shobhika" \ "Siddhanta" \ "Siddhanta-Calcutta" \ "Siddhanta-Nepali" \ "Siddhanta-cakravat" \ "Sylfaen" \ "Symbola Semi-Condensed" \ "Tahoma Bold" \ "Tahoma" \ "Times New Roman, Bold Italic" \ "Times New Roman, Bold" \ "Times New Roman, Italic" \ "Times New Roman," \ "Trebuchet MS Bold Italic" \ "Trebuchet MS Bold" \ "Trebuchet MS Italic" \ "Trebuchet MS" \ "Unikurd Goran" \ "Unikurd Hejar" \ "Unikurd Roonak" \ "Unikurd Web" \ "Urdu Typesetting" \ "Uttara" \ "Verdana Bold Italic" \ "Verdana Bold" \ "Verdana Italic" \ "Verdana" \ rm -rf ~/tesstutorial/digitsalldistort_from_full mkdir -p ~/tesstutorial/digitsall_from_full combine_tessdata -e ~/tessdata_best/eng.traineddata \ ~/tesstutorial/digitsall_from_full/eng.lstm lstmtraining \ --model_output ~/tesstutorial/digitsall_from_full/digitsall_layer \ --traineddata ~/tesstutorial/digitsall/eng/eng.traineddata \ --continue_from ~/tesstutorial/digitsall_from_full/eng.lstm \ --append_index 5 --net_spec '[Lfx192 O1c1]' \ --train_listfile ~/tesstutorial/digitsall/eng.training_files.txt \ --debug_interval 0 \ --max_iterations 200000 lstmtraining \ --stop_training \ --traineddata ~/tesstutorial/digitsall/eng/eng.traineddata \ --continue_from ~/tesstutorial/digitsall_from_full/digitsall_layer_checkpoint \ --model_output digitsall_layer.traineddata cp digitsall_layer.traineddata ~/tessdata_best/ ## lstmeval --model ~/tessdata_best/eng.traineddata --eval_listfile ~/tesstutorial/digitsall/eng.training_files.txt ## lstmeval --verbosity 0 --model ~/tesstutorial/digitsall_from_full/digitsall_layer_checkpoint --traineddata ~/tesstutorial/digitsall/eng/eng.traineddata --eval_listfile ~/tesstutorial/digitsall/eng.training_files.txt ================================================ FILE: eng.digits.numbers ================================================ - . . . . . . . . . . . . . . . . . . . . . . . . . . . - - - - - . - . - . . ================================================ FILE: eng.digits.punc ================================================ . - ================================================ FILE: eng.digits.training_text ================================================ 14.16 24) -832.36 17.54) 7/16/1892 16.4) 7.31 68921-2802 (68.66) 8.5) 49526,30 9-1 28/05/1764 13.64) 12 -502.95 12.7 15.81) 25/01/1974 20:23:46 1658 9-13 18.30 4.70) 7-31 3.54 5.40 48. 18.26) -560.25 295.92 8.32 9.80) 8.35 502087988 2.27) 14.46) 16.63 11.62) 4-21 4-23 -432.66 11.51) 18.13) 246529 19.67) 13.44 20.19 1203579. 151.00 13.73 4.3 59,30 368313 32) 7/11/2014 291 12.9) 5.59) (85.16) 6957 18.22 021833460 10 6-26 3.7) 11.61) 10/12/1939 8 0 88 99 8.87 (416.45) 15.51) -643.31 15.57 789 -6923.05 1,234,567,89. 14320 185. 06/2028 -33.47 (644.56) 12.1 46 110,00,00,00,00 59,34 14.9 0519607 8/11/1956 15:22:32 7/21/2043 04:27:35 2.59) 2.64 11.38) 29/04/1914 01:05:05 19.89 19.56 -304.38 438522 1.51 3-62 -437.99 1113 26) 17.80) 7/22/1913 -554.40 16.18 112.24 134.73 0.53 54. 18.76 (558.27) 186) 4-37 4.77) 5-95 6.65 9.18 13.21) 3.13) -843.77 28/10/1918 9599 8469213 16.64 8-56 29/09/1991 12.42) .02 3.93 6/2019 15.15) 13) 1-29 1.76 15 19 (4105.90) 13.94 10946479 11 12.64 1-412-851-0920 2-50 4/01/2019 03/2021 13/08/98 11.74 -786.39 5.43 2-33 2.86) 8.41 51113144357 12.5) 4-44 44. 1-95 5.69) 8025/03/2019 56/36564 3/2019 921833460 (80.13) 56 189.06 16.26 19.79 19.8) 9/17/1749 2.62) 61. 9-86 (505) 500-3609 1-16 6-48 5-42 13.20) 7.73) 48) 11.80) 7.28 0.141000032425 9.14 269.62 9-4 7.99 12/01/1963 17.9) 67/26817 6/24/1821 (495.75) 182) 190. 37) 2-23 6-19 3/2025 02/2020 2359(07 282582 647784 1 6.2 7.52 18.7) -766.55 13.65 5-29 13.69) 7.84 021946 11.24) 4.64 7.22) 5/10/1735 7099165 35 35 -959.06 4.71) 14.45) 18.7 7.13 -133.29 9070.04 2-31 5.1) 6.88 27/01/1799 155) 7-21 60656 9 15 6 1 8.39) 5.9 14.37) 25508,25 9/14/2029 09:45:27 23) 5.88 9129 16 1999-08-24 173583 9-97 -913.36 36193,52 17.99 1/04/1944 19:51:28 7-17 11171917 11 7.80 75.99 -34.91862 8.87 166.78 3-87 9.52) 506325066 8/4/1949 150.28 100. 4.95) 12.26) 34072280742617 23178 11 -358.08 13.17 -503.89 68685 16.37) 41521042 14.51) 128.43 1/76625 18.45) 17.12 -321.64 9-12 6-99 17.51 8.61 11.26 4-47 14.83) 4.33) 18.83 2579,62 11/08/1924 253 911 3-92 11.15 20/02/2024 22:50:14 8-30 19.60 996532 3.17) 69.59 7-44 15.16 29/10/2019 3-46 03/09/1901 4617 5.34 7.29) 8-46 1998-08-13 127. 16.26) -291.70 0.203999996185 18.68 6.54 2 31 6.98) 6.86 3.87 8/2020 4-45 -555514.78 9.39) 2.92 8-54 .47 5425.29 8.47 5.29) 6-89 -105.26 16.11) 41,23 13.74) 05 7120.776208 1/93429 05/2019 (752.04) 11.18 49) 204.40 3.24 9/10 5-25 (784.25) 52. 54083.8 (4863.55) 4.27) -823.90 17.74 7.27 12/01/2022 01:58:55 1.6 94048,28 16.67) 9-18 13.27) 9.66) 2.60 87.416 544558 6.34) 2/01/1908 (757.38) 037018 16.56 72. 4.24) 19.84 17638,27 14.52 12.81) 11/2027 243235.915651 707140 604238 15.79 -129.89 4-15 9.75 9.45 3-77 5.37) 3641 30 1.52 8.68 14.71 5.52) -829.17 17.14 21,47 3-9 7-43 10375193 6.9) 13.19 2.39) 8/06/2021 05:27:52 12.50 12.6) 12.52) -73.40 984512 2.29 5-62 5-7 2.19 12.8) 152. 757675 945500 54,48 9-25 1.50 2.00 0.99 (681.36) 371.31 17.82 91646077 6-83 11.32) 6-13 5-79 (569.10) 19.62 12/11/2024 -329.38 9164607 7 4-11 8.12 (892.95) -258.87 13.16) 776700 5405.93 -622.28 65.99 12.52 (645.80) 1.55 -799.33 7.11) 149. 6.97 12.38) 6.61 (6799.86) 4/55302 1267.29 00 000 0.025 8.67 5-32 0.190999984741 4/5/1922 7-95 5-82 8/28/2029 02:48:05 70499 501870 773548 6-27 5-8 345.14 2/04/1912 7-84 0845470 19.45) 07/2022 60 6/03/2049 11:44:13 11/11/1753 12.4) 34) 5.53) 1.74) 1-81 983115 44 47 76. 63359,39 6-11 117541.539888 -370.29 5-77 8.64) 13.63) -761.90 11.23 (469.23) 3.71) 6.87) 47 48 5821 160. 72385-6573 5.55) -712.35 10/03/2046 02:41:15 162462 11/18/2037 04:40:53 (844.41) 86786.513304 8/15/1992 13.30) 15.21) 8/01/1618 8.99 153. 5.15 18.47) 16.3) 8-97 6/2021 9.88 13.66 9.92 19.68) 13.76 17.1) 97. 26/05/1953 16:16:10 12.87) 169717 9-50 12.99) -446.88 3.15 10/12/1888 6.44) 22 9 1 2 9 16 (621.81) 6.78) 24/12/2019 4-41 77782.2 (223) 379-8482 20 16290567 4 19.87) 9.89 11171917 11 1.66) 110. 7.52) 16.93 7. 12.59 357234 14.95) 16.18) -775.08 49620250 23 5 1.97 173436 3.27) 5.11 11/30/2044 03:03:45 8.95 2007,2010,2013 1.78) 15.34 71509,53 8-83 -2485457.201918 15.59 1/12/1804 110.19 (876.07) 14.66 6.38 11.65) 15.29) 530 394.72 16.5) 8/09/2019 5.7 18/08/1924 88.99 17.24 97043 17.3) 06/2020 1-38 3.44) 8.44 17.21 13.39) 3.14) 11.29) 950102882 47 8-7 17.91) 15.11 -253892.045 6.39 47,39 6.75 6.86) 62. 19.26 -259.87 17/05/1957 19.15 14.50) 23/74567 7.24) 18.66 5-83 8-90 17.61 17.28 23/09/1994 06:55:53 7/10/2012 14:31:58 9.11) 3.2) 111314476 2429.45 -528.82 15.41 8-77 73.99 18.79) 89/0389/2015 2.51 19.21 4.36) 1.76) 22. 8/04/2017 19:16:32 (774.28) 13.5 -281.97 195) 3-55 61 11.92) 16.51) 1-3 -419578.442740 13 45326 1.38) -420.95 15.6 8/11865 8-98 122472 4-18 2969 8-33 3-83 174567 -213.21 19.5) 8.8 -822.73 14.22) 2.24) 5/29/1946 1-28 8.92) 3/01/2003 01:06:46 70.99 5-71 5 6.14 5.54 837842938 (672.48) 7.72) 12/03/1983 9.90) 15.48) 138.69 3-33 14.40 133) 6.63) 9.27) 508553 15787256 1.49 8.99 10929904 3.79) 123 18.74 15909545 16 3-71 28/01/1734 921105 (9783.14) 18.38) 7.65) 16.42) 16.37 8.14) 15.12 200945 3-89 938,26 9.29) 18.31) 8-65 635173 158576 83. 5.60) -310.74 5.49 17.85 2.44 13.79) 24.99 31 16.53 2-32 11.10) 19.32) 1/4 04/2021 -545.94 2846 1,234,567.89 1.59 11.5) (606.15) 4.56 49. 6.13) 8.28) 517364 42 -483.42 6-5 6. 15.62) 2.70) 5-33 2002-10-24 02:05:34 160101302 6.73 9.21 67. 13.47) 5247 -267.61 -536.09 4/61350 16.73 7677158 17.76 25/08/2020 2057/10/03 13.35) 32 67 69 459 5.14 168.28 71714,53 3.40) 16.81) 1063998.215971 75) -995.70 -155.54 4.19 5/13/1980 9.1 6-74 7.35) -622.48 2.70 -379.53 3.99) 8.40) -33.45 7-55 13.28 2-71 78/147279 16.60 16.12 971513704 19.81) 5.43) 31/08/2019 2912 4-5 8.22 1931104 7 5-87 21 49 (814.05) 6.42) 144. 3-98 181. 5-91 -213.86 16.46) 5.60 7-41 -440.81 154.62 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51,42 3-47 8 17.41) 14.84 8.22) 4.33 12.99 19.97) 9715 13 704 16.96) 11.76) 112019 102. 0090000% 8-95 5.77 1.6) 287.97 1.39 305073 8/09/1975 8738 18.3 2/24/1828 -355.48 6891 1,234 17.47) 9.97) 266065889 34 16.22 13.27 1/95840 87990,29 11.25) 15.61 56/33311 14 611061 20 191. 4.82) 4004699 -94.75 1417.88 17.72) 16.60) 9.74) 1.99) 5.16) 86.99 8.14 13.23) 82) 6.44 41) 11.25 -612.91 9-36 294 967 11.69 12.67) 02 972512 476635 8.38) 606354.853977 14.14 12.83) 925 -159.37 2-8 8.64 6-28 19.88) -142.69 614217 917664 (648.28) 3) 8.4) 15.89) 16.78) 12.24) 5.4 26/07/1911 88664.3444 6.55) 334.84 -565.41 9, 6.11) 13.54) 11/12/1993 398280 -62.49 1/93740 6.72 1-32 11.73) 8.17 3.88 8088998.87 8.65 936228931 26 9.37) 1/04/2029 03:10:52 5-38 -132.33 -40.81397 11.93) (449.54) 123456 44 12.1) 2.65 905983 9.99 (839.74) 1576 1684135217 1 (64.04) 8.52) 347592 35 54 1/14/1912 8/25/1870 17836,64 90 88 60 1-79 16.52) 2/79304 13.76) -242.33 19.82) 1474 ================================================ FILE: engmorse.traineddata ================================================ [File too large to display: 11.9 MB] ================================================ FILE: engrestrict-finetune.sh ================================================ #!/bin/bash echo "/n ****** Finetune one of the fully-trained existing models: ***********" mkdir -p ./engrestrict_from_full combine_tessdata -e ~/tessdata_best/eng.traineddata \ ./engrestrict_from_full/eng.lstm lstmtraining \ --model_output ./engrestrict_from_full/engrestrict_plus \ --traineddata ./engrestrict/eng/eng.traineddata \ --continue_from ./engrestrict_from_full/eng.lstm \ --old_traineddata ~/tessdata_best/eng.traineddata \ --train_listfile ./engrestrict/eng.training_files.txt \ --debug_interval -1 \ --max_iterations 400 lstmtraining \ --stop_training \ --traineddata ./engrestrict/eng/eng.traineddata \ --continue_from ./engrestrict_from_full/engrestrict_plus_checkpoint \ --model_output ./engrestrict_plus.traineddata OMP_THREAD_LIMIT=1 lstmeval \ --model ./engrestrict_from_full/engrestrict_plus_checkpoint \ --traineddata ./engrestrict/eng/eng.traineddata \ --eval_listfile ./engrestrict/eng.training_files.txt OMP_THREAD_LIMIT=1 lstmeval \ --verbosity 0 \ --model ~/tessdata_best/eng.traineddata \ --eval_listfile ./engrestrict/eng.training_files.txt ================================================ FILE: engrestrict-makedata.sh ================================================ #!/bin/bash rm -rf ./engrestrict ~/tesseract/src/training/tesstrain.sh \ --fonts_dir ~/.fonts \ --lang eng --linedata_only \ --noextract_font_properties \ --langdata_dir ~/langdata \ --tessdata_dir ~/tessdata_best \ --training_text ./engrestrict.training_text \ --exposures "0" \ --save_box_tiff \ --maxpages 0 \ --workspace_dir ~/tmp \ --output_dir ./engrestrict \ --fontlist \ "Andale Mono" \ "Anonymous Pro" \ "Bitstream Vera Sans Mono" \ "Consolas" \ "Courier New Bold" \ "Courier New" \ "Cousine" \ "Cutive Mono" \ "DejaVu Sans Mono" \ "Fira Mono" \ "FreeMono" \ "IBM Plex Mono" \ "Inconsolata" \ "Letter Gothic Std" \ "Liberation Mono" \ "Lucida Console Semi-Condensed" \ "Lucida Sans Typewriter Semi-Condensed" \ "Merchant Copy Doublesize" \ "Merchant Copy" \ "Miriam Mono CLM" \ "Noto Mono" \ "PT Mono" \ "QuickType II Mono" \ "Source Code Pro" \ "Space Mono" \ "Ubuntu Mono" rm -rf ./engrestrict_from_full ================================================ FILE: engrestrict.training_text ================================================ different New Articles page 23 a To Service a details DC that don t as 7 Date 1 AZ Music am search this Please time each How at Online (7) get quality Advanced can may such a August Us 2 100 experience From you My US Copyright (RefSeq) I free two 30, Account On MORE Public where C Program questions 8 this ) Other because 1 has character NCBI was back - SEARCH Click there to an may from Search , that NBA LCD ... 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Email in MP3 these that GenBank am Search From Find only Free more some for , Page CD AbstractPlus most Page , over Other reference 40 should a Posts my the search (1) Map Sports 25,000 Back so does Related SNP we TX at been 5, 7. some good 25 now this J User INDEX had help 6 all iGoogle if in Ca years you even 2007 pages also 500 9 The like here need video good going We over is FL 50 NEXT and ToolKit 2005 Copyright can up BNET York on being have HTML OR because Privacy lm View a TMZ dbGaP 25, 1, more all add US all 2 Map United MEDLINE under used UK PDF Review CA last 4, does YOU OH 30 them its 1 comments are November URL Reply of a San a I ve some The to services the Community use Texas Information and GEO but Advanced content details FAQ is free Health New on (6) had Forum 2008, 24, as MEDLINE are from their was Rights College Jobs which 2006 no between 6. version and 1 are (Weighted) Privacy Copyright For Policy new we like comment been including 15, Links More have during 3. the Forum comment Company many for St. The required be Home of other to of made Dr. like GPS off our RJ Size THIS MD 3, any can t his Post with Send about 3G Video also 10 -- from about 2007, data March 5 also a Send From ================================================ FILE: engrestrict_best.traineddata ================================================ [File too large to display: 14.4 MB] ================================================ FILE: frk.traineddata ================================================ [File too large to display: 16.8 MB] ================================================ FILE: san-chandas-float.traineddata ================================================ [File too large to display: 16.8 MB] ================================================ FILE: san-siddhanta-float.traineddata ================================================ [File too large to display: 16.8 MB]