Repository: oylz/DS
Branch: master
Commit: b26320abcfe1
Files: 49
Total size: 11.7 MB
Directory structure:
gitextract_zv8h4xpo/
├── LICENSE
├── Main.cpp
├── NT.cpp
├── NT.h
├── NTN.h
├── README.md
├── StrCommon.h
├── data/
│ └── tt1.pb
├── deepsort/
│ ├── Detection.h
│ ├── FeatureGetter/
│ │ ├── CaffeShuffeNetFeatureGetter.cpp
│ │ ├── FaceNetFeatureGetter.cpp
│ │ ├── FeatureGetter.cpp
│ │ ├── FeatureGetter.h
│ │ ├── MobileNetFeatureGetter.cpp
│ │ └── make.sh
│ ├── HungarianOper.h
│ ├── KalmanTracker.h
│ ├── iou_matching.h
│ ├── kalman_filter.h
│ ├── linear_assignment.h
│ ├── munkres/
│ │ ├── adapters/
│ │ │ ├── adapter.cpp
│ │ │ ├── adapter.h
│ │ │ ├── boostmatrixadapter.cpp
│ │ │ └── boostmatrixadapter.h
│ │ ├── matrix.cpp
│ │ ├── matrix.h
│ │ ├── munkres.cpp
│ │ └── munkres.h
│ ├── nn_matching.h
│ └── tracker.h
├── fdsst/
│ ├── SSE2NEON.h
│ ├── fdssttracker.cpp
│ ├── fdssttracker.hpp
│ ├── ffttools.hpp
│ ├── fhog.cpp
│ ├── fhog.h
│ ├── fhogbk/
│ │ ├── fhog.cpp
│ │ └── fhog.h
│ ├── labdata.hpp
│ ├── recttools.hpp
│ ├── sse.hpp
│ └── tracker.h
├── lmake.sh
├── log.txt
├── logn10.txt
├── logn15.txt
├── logn20.txt
├── make.sh
└── t.sh
================================================
FILE CONTENTS
================================================
================================================
FILE: LICENSE
================================================
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Copyright (C)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see .
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
Copyright (C)
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
.
================================================
FILE: Main.cpp
================================================
#include
#include "NT.h"
#include "StrCommon.h"
NT *_tt = NULL;
void DrawData(cv::Mat mm, cv::Mat frame, const std::map &map,
const std::vector &outRcs,
bool detect){
std::map::const_iterator it;
for(it = map.begin(); it != map.end(); ++it){
CvScalar clr = cvScalar(0, 255, 0);
cv::Rect rc = it->second.rc_;
cv::rectangle(frame, rc, clr);
std::string disp = toStr(it->first);
cv::putText(frame,
disp,
cvPoint(rc.x, rc.y),
CV_FONT_HERSHEY_SIMPLEX,
0.6,
cv::Scalar(0, 0, 255));
}
//
CvScalar clr = cvScalar(0, 0, 255);
for(cv::Rect rc:outRcs){
cv::rectangle(mm, rc, clr);
if(detect){
std::string disp = "detect";
cv::putText(frame,
disp,
cvPoint(100, 100),
CV_FONT_HERSHEY_SIMPLEX,
1,
cv::Scalar(0, 0, 255));
}
}
}
void ReadFileContent(const std::string &file, std::string &content){
FILE *fl = fopen(file.c_str(), "rb");
if(fl == NULL){
return;
}
fseek(fl, 0, SEEK_END);
int len = ftell(fl);
if(len <= 0){
return;
}
fseek(fl, 0, SEEK_SET);
char *buf = new char[len+1];
memset(buf, 0, len+1);
fread(buf, 1, len, fl);
content = std::string(buf);
delete []buf;
fclose(fl);
}
std::map> _rcMap;
void ReadRcFileTotal(const std::string &file) {
std::string content = "";
ReadFileContent(file, content);
std::vector lines;
splitStr(content, "\n", lines);
std::vector rcs;
int num = -1;
int tmpNum = -1;
for (int i = 0; i < lines.size(); i++) {
std::vector cols;
splitStr(lines[i], ",", cols);
if (cols.size() < 6) {
continue;
}
tmpNum = toInt(trim(cols[0]));
if (num!=-1 && tmpNum!=num) {
_rcMap.insert(std::make_pair(num, rcs));
rcs.clear();
num = tmpNum;
}
if (num == -1) {
num = tmpNum;
}
cv::Rect rc;
rc.x = toInt(trim(cols[2]));
rc.y = toInt(trim(cols[3]));
rc.width = toInt(trim(cols[4]));
rc.height = toInt(trim(cols[5]));
rcs.push_back(rc);
}
if (!rcs.empty()) {
_rcMap.insert(std::make_pair(tmpNum, rcs));
}
}
std::string _rcFile = "";
std::string _imgDir;
cv::VideoWriter *_vw = NULL;
bool _isShow = false;
int _imgCount = 0;
void CB(cv::Mat &frame, int num){
if (_vw == NULL) {
_vw = new cv::VideoWriter("out.avi", CV_FOURCC('M', 'J', 'P', 'G'), 25.0, cv::Size(frame.cols, frame.rows));
}
if (_rcMap.empty()) {
ReadRcFileTotal(_rcFile);
}
std::vector rcs;
std::map>::iterator it = _rcMap.find(num);
if (it != _rcMap.end()) {
rcs = it->second;
}
std::vector outRcs;
int64_t tm0 = gtm();
std::map map = _tt->UpdateAndGet(frame, rcs, num, outRcs);
int64_t tm1 = gtm();
Mat mm = frame.clone();
bool detect = (!rcs.empty());
DrawData(mm, frame, map, outRcs, detect);
printf("finish %d frame, updatecasttime:%ld\n", num, tm1-tm0);
//(*_vw) << frame;
if(_isShow){
std::string disp = "frame";
cv::resize(mm, mm, cv::Size(mm.cols/2, mm.rows/2));
cv::resize(frame, frame, cv::Size(frame.cols/2, frame.rows/2));
cv::imshow("mm", mm);
cv::imshow(disp, frame);
cv::waitKey(1);
}
}
void Go() {
std::string root = _imgDir;
for (int i = 1; i < _imgCount; i++) {
std::string path = root;
path += to6dStr(i);
path += ".jpg";
cv::Mat mat = cv::imread(path);
CB(mat, i);
}
}
int main(int argc, char **argv){
if (argc < 2) {
printf("usage:\n./tt showornot(0/1)\n");
return 0;
}
_isShow = toInt(argv[1]);
_tt = new NT();
if(!_tt->Init()){
return 0;
}
//_imgDir = "e:/code/deep_sort-master/MOT16/tt/xyz/img1/";
//_rcFile = "e:/code/deep_sort-master/MOT16/tt/xyz/det/det.txt";
_imgDir = "/home/xyz/code1/xyz/img1/";
_rcFile = "/home/xyz/code1/xyz/det/det.txt";
//_rcFile = "/home/xyz/code/test/pp/FaceNumGetter/out/102.txt";
//_imgDir = "/home/xyz/code1/GEP/FrameBuffer/imglog/img1/";
//_rcFile = "/home/xyz/code1/GEP/FrameBuffer/imglog/det/det.txt";
_imgCount = 650;// 2001;// 750;// 680;
Go();
return 0;
}
================================================
FILE: NT.cpp
================================================
#include "NT.h"
//#define UDL
#ifdef UDL
//#define UBC
#include "deepsort/FeatureGetter/FeatureGetter.h"
#endif
#include "./deepsort/tracker.h"
#include "StrCommon.h"
#include "fdsst/fdssttracker.hpp"
#include "fdsst/fhog.h"
#include
boost::shared_ptr NearestNeighborDistanceMetric::self_;
boost::shared_ptr KF::self_;
#define UHOG
void ExtractFeatureHog(const cv::Mat &in,
const std::vector &rcsin,
std::vector &fts){
cv::Mat frame;
cvtColor(in, frame, cv::COLOR_RGB2GRAY);
for(int i = 0; i < rcsin.size(); i++){
Mat nnn = frame(rcsin[i]);
resize(nnn, nnn, Size(32, 32));
int len = 0;
float *hog = HOGXYZ(nnn, len);
if(hog==NULL || len!=128){
printf("hog(%d) is null or len(%d)!=128,exit!\n", hog==NULL, len);
exit(0);
}
FEATURE ft;
for(int j = 0; j < len; j++){
ft(j) = hog[j];
}
delete []hog;
fts.push_back(ft);
}
}
#ifdef UDL
void ExtractFeature(const cv::Mat &in,
const std::vector &rcsin,
std::vector &fts) {
int maxw = 0;
int maxh = 0;
int count = rcsin.size();
#ifdef UBC
int BC = 1;
if(count < BC)count=BC;
#endif
std::vector faces;
cv::Rect lr;
for (int i = 0; i < count; i++) {
cv::Rect rc;
if(i < rcsin.size()){
rc = rcsin[i];
lr = rc;
}
else{
rc = lr;
}
faces.push_back(in(rc).clone());
int w = rc.width;
int h = rc.height;
if (w > maxw) {
maxw = w;
}
if (h > maxh) {
maxh = h;
}
}
maxw += 10;
maxh += 10;
cv::Mat frame(maxh, maxw*count, CV_8UC3);
std::vector rcs;
for (int i = 0; i < count; i++) {
cv::Mat &face = faces[i];
cv::Rect rc = cv::Rect(i*maxw + 5, 5, face.cols, face.rows);
rcs.push_back(rc);
cv::Mat tmp = frame(rc);
face.copyTo(tmp);
}
std::vector newfts;
FeatureGetter::Instance()->Get(frame, rcs, newfts);
for(int i = 0; i < rcsin.size(); i++){
fts.push_back(newfts[i]);
}
}
#endif
NT::NT(){
tt_ = TTrackerP(new TTracker(0.7, 30, 1));
}
NT::~NT(){
}
bool NT::Init(){
#ifdef UDL
if(!FeatureGetter::Instance()->Init()){
return false;
}
#endif
if(0){// just a test
Mat frame = cv::imread("/home/xyz/code1/xyz/img1/000001.jpg");
Mat nnn;
cvtColor(frame, nnn, cv::COLOR_RGB2GRAY);
resize(nnn, nnn, Size(32, 32));
Mat a = fhog(nnn, 4, 9, 0.2f, false);
std::cout << "a:cols:" << a.cols << "a:rows:" << a.rows << "\njust a test, exit\n";
exit(0);
}
KF::Instance()->Init();
#ifdef UDL
#ifdef UBC
Mat frame = cv::imread("/home/xyz/code1/xyz/img1/000001.jpg");
std::vector dets;
std::vector fts;
std::vector rcs;
srand((unsigned)time(NULL));
int width = frame.cols;
int height = frame.rows;
//for(int i = 0; i < 30; i++){
int x = rand()%width;
int y = rand()%height;
int w = 100;
int h = 100;
//std::cout << x << "," << y << "," << w << "," << h << "\n";
if(x+w > width){
w = width - x;
}
if(y+h > height){
h = height - y;
}
cv::Rect rc(x, y, w, h);
rcs.push_back(rc);
//}
ExtractFeature(frame, rcs, fts);
#endif
#endif
NearestNeighborDistanceMetric::Instance()->Init(0.2, 100);
return true;
}
NewAndDelete NT::UpdateDS(const cv::Mat &frame, const std::vector &rcs, int num, const std::vector &oriPos){
int64_t tm1 = gtm();
std::vector dets;
std::vector fts;
if(rcs.size() > 0){
#ifdef UHOG
ExtractFeatureHog(frame, rcs, fts);
#else
ExtractFeature(frame, rcs, fts);
#endif
}
int64_t tm2 = gtm();
for (int i = 0; i < rcs.size(); i++){
DSBOX box;
cv::Rect rc = rcs[i];
box(0) = rc.x;
box(1) = rc.y;
box(2) = rc.width;
box(3) = rc.height;
Detection det(box, 1, fts[i]);
//printf("oriPos.size():%d\n", oriPos.size());
if(i < (int)oriPos.size()-1){
det.oriPos_ = oriPos[i];
}
dets.push_back(det);
}
NewAndDelete nad = tt_->update(dets);
int64_t tm3 = gtm();
std::string tail = "";
if(tm3-tm1 > 30000){
tail = "****";
}
std::cout << num << "----rcs.size():" << rcs.size() << "[tm1:" << tm1 << ",tm2:" << tm2 << "("<< (tm2 - tm1) << ")"<< ",tm3:"
<< tm3 << "(" << (tm3-tm1) << ")]" << tail.c_str() << "\n";
return nad;
}
struct RRS{
void Push(const cv::Rect &rc){
boost::mutex::scoped_lock lock(mutex_);
rcs_.push_back(rc);
}
void Get(std::vector &rcs){
rcs = rcs_;
}
private:
std::vector rcs_;
boost::mutex mutex_;
};
struct FFS{
public:
void Push(int id, const FDSSTTrackerP &ff){
boost::mutex::scoped_lock lock(mutex_);
ffs_.push_back(std::make_pair(id, ff));
}
void Get(std::vector > &ffs){
ffs = ffs_;
}
private:
std::vector > ffs_;
boost::mutex mutex_;
};
// for framebuffer
void NT::UpdateFDSST(const Mat &frame, std::vector &rcs){
std::map::iterator it;
std::vector lostIds;
RRS rrs;
std::vector ffs;
for(it = fdssts_.begin(); it != fdssts_.end(); ++it){
FDSSTTrackerP fdsst = it->second;
ffs.push_back(fdsst);
}
#pragma omp parallel for
for(int i = 0; i < ffs.size(); i++){
cv::Rect rc = ffs[i]->update(frame);
rrs.Push(rc);
}
//
std::vector rrcs;
rrs.Get(rrcs);
for(int i = 0; i < rrcs.size(); i++){
cv::Rect rc = rrcs[i];
int ww = frame.cols;
int hh = frame.rows;
int min = 8;
if(rc.x<0 || rc.y<0 ||
(rc.x+rc.width)>ww ||
(rc.y+rc.height)>hh ||
rc.width<=min || rc.height<=min){
lostIds.push_back(it->first);
continue;
}
rcs.push_back(ToOriRect(rc));
}
// remove
for(int id:lostIds){
fdssts_.erase(id);
}
}
std::map NT::UpdateAndGet(const cv::Mat &frame,
const std::vector &rcsin,
int num,
std::vector &outRcs,
const std::vector &oriPos){
std::vector rcs = rcsin;
//{
Mat ffMat;
cvtColor(frame, ffMat, cv::COLOR_RGB2GRAY);
resize(ffMat, ffMat, Size(ffMat.cols*scale_, ffMat.rows*scale_));
std::cout << "NT::UpdateAndGet1\n";
//}
if(!rcsin.empty()){
fdssts_.clear();
}
else{
UpdateFDSST(ffMat, rcs);
}
std::cout << "NT::UpdateAndGet1.5\n";
outRcs = rcs;
NewAndDelete nad = UpdateDS(frame, rcs, num, oriPos);
std::map map;
std::vector &kalmanTrackers =
tt_->kalmanTrackers_;
std::cout << "NT::UpdateAndGet2\n";
std::vector > idrcs;
for (const auto& track : kalmanTrackers){
int id = (int)track->track_id;
printf("trackid:%d, is_confirmed:%d, time_since_update:%d\n", id, track->is_confirmed(), track->time_since_update_);
//if (!track->is_confirmed() || track->time_since_update_ > 0) {
// continue;
//}
if(track->time_since_update_ > 0){
continue;
}
DSBOX box = track->to_tlwh();
cv::Rect rc;
rc.x = box(0);
rc.y = box(1);
rc.width = box(2);
rc.height = box(3);
int oriPos= track->oriPos_;
DSResult tr;
tr.rc_ = rc;
tr.oriPos_ = oriPos;
if(!rcsin.empty()){
idrcs.push_back(std::make_pair(id, rc));
printf("id:%d, rc:(%d, %d, %d, %d), oriPos:%d, rcsin.size():%d, rcs.size():%d\n",
id, rc.x, rc.y, rc.width, rc.height,
oriPos, rcsin.size(), rcs.size());
}
if (!track->is_confirmed() || track->time_since_update_ > 0) {
continue;
}
map.insert(std::make_pair(id, tr));
}
std::cout << "NT::UpdateAndGet3\n";
FFS ffs;
#pragma omp parallel for
for(int i = 0; i < idrcs.size(); i++){
std::pair pa = idrcs[i];
int id = pa.first;
cv::Rect rc = pa.second;
printf("id:%d, rc:(%d, %d, %d, %d)\n",
id, rc.x, rc.y, rc.width, rc.height);
FDSSTTrackerP fdsst(new FDSSTTracker());
fdsst->init(ToScaleRect(rc), ffMat);
ffs.Push(id, fdsst);
}
std::cout << "NT::UpdateAndGet4\n";
std::vector > pps;
ffs.Get(pps);
for(int i = 0; i < pps.size(); i++){
std::pair pa = pps[i];
fdssts_.insert(pa);
}
return map;
}
================================================
FILE: NT.h
================================================
#ifndef _NTH_
#define _NTH_
#include
#include
#include "NTN.h"
using namespace cv;
struct DSResult{
cv::Rect rc_;
int oriPos_;
DSResult(){
rc_ = cv::Rect(0, 0, 0, 0);
oriPos_ = -1;
}
};
class TTracker;
typedef boost::shared_ptr TTrackerP;
class FDSSTTracker;
typedef boost::shared_ptr FDSSTTrackerP;
class NT{
public:
NT();
~NT();
bool Init();
// for framebuffer
std::map UpdateAndGet(const cv::Mat &frame,
const std::vector &rcs,
int num,
std::vector &outRcs,
const std::vector &oriPos=std::vector(0));
private:
void UpdateFDSST(const Mat &frame, std::vector &rcs);
NewAndDelete UpdateDS(const cv::Mat &frame,
const std::vector &rcs,
int num,
const std::vector &oriPos);
private:
cv::Rect ToOriRect(const cv::Rect &rc){
cv::Rect re;
float x = ((float)rc.x)/scale_;
float y = ((float)rc.y)/scale_;
float w = ((float)rc.width)/scale_;
float h = ((float)rc.height)/scale_;
re.x = x;
re.y = y;
re.width = w;
re.height = h;
return re;
}
cv::Rect ToScaleRect(const cv::Rect &rc){
cv::Rect re;
float x = ((float)rc.x)*scale_;
float y = ((float)rc.y)*scale_;
float w = ((float)rc.width)*scale_;
float h = ((float)rc.height)*scale_;
re.x = x;
re.y = y;
re.width = w;
re.height = h;
return re;
}
private:
TTrackerP tt_;
std::map fdssts_;
float scale_ = 0.25;
};
#endif
================================================
FILE: NTN.h
================================================
#ifndef _NTNH_
#define _NTNH_
struct NewAndDelete{
std::map news_;// id, pos
std::vector deletes_;
};
#endif
================================================
FILE: README.md
================================================
**DS**(~~deepsort cpp version~~)
C++ implementation of Simple Online Realtime Tracking with a Deep Association Metric
# 1. dependencies
component|version
-|-
eigen|3.3
opencv|-
boost|-
tensorflow|1.4
# 2. build
./make.sh
# 3. prepare data
change the var values at [lines160-162 in Main.cpp](https://github.com/oylz/DS/blob/master/Main.cpp#L160TL162):
```
_imgDir = "/home/xyz/code1/xyz/img1/"; // MOT format
_rcFile = "/home/xyz/code1/xyz/det/det.txt"; // MOT format
_imgCount = 680; // frames count
```
# 4. run
./r.sh
# 5.tips
tensorflow build:
```
(1) ./configure
(2) bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=cuda tensorflow:libtensorflow_cc.so
```
================================================
FILE: StrCommon.h
================================================
#ifndef _STRCOMMONH_
#define _STRCOMMONH_
#include
#include
#ifdef WIN32
#include
#include
#include
static int gettimeofday(struct timeval *tp, void *tzp)
{
time_t clock;
struct tm tm;
SYSTEMTIME wtm;
GetLocalTime(&wtm);
tm.tm_year = wtm.wYear - 1900;
tm.tm_mon = wtm.wMonth - 1;
tm.tm_mday = wtm.wDay;
tm.tm_hour = wtm.wHour;
tm.tm_min = wtm.wMinute;
tm.tm_sec = wtm.wSecond;
tm.tm_isdst = -1;
clock = mktime(&tm);
tp->tv_sec = clock;
tp->tv_usec = wtm.wMilliseconds * 1000;
return (0);
}
static void usleep(int64_t us) {
int64_t s = us / 1000;
Sleep(s);
}
#else
#include
#endif
using namespace cv;
static int64_t gtm() {
struct timeval tm;
gettimeofday(&tm, 0);
int64_t re = ((int64_t)tm.tv_sec) * 1000 * 1000 + tm.tv_usec;
return re;
}
static void splitStr(const std::string& inputStr, const std::string &key, std::vector& outStrVec) {
if (inputStr == "") {
return;
}
int pos = inputStr.find(key);
int oldpos = 0;
if (pos > 0) {
std::string tmp = inputStr.substr(0, pos);
outStrVec.push_back(tmp);
}
while (1) {
if (pos < 0) {
break;
}
oldpos = pos;
int newpos = inputStr.find(key, pos + key.length());
std::string tmp = inputStr.substr(pos + key.length(), newpos - pos - key.length());
outStrVec.push_back(tmp);
pos = newpos;
}
int tmplen = 0;
if (outStrVec.size() > 0) {
tmplen = outStrVec.at(outStrVec.size() - 1).length();
}
if (oldpos + tmplen < inputStr.length() - 1) {
std::string tmp = inputStr.substr(oldpos + key.length());
outStrVec.push_back(tmp);
}
}
static std::string trim(std::string &s) {
if (s.empty()) {
return s;
}
s.erase(0, s.find_first_not_of(" "));
s.erase(s.find_last_not_of(" ") + 1);
return s;
}
static int toInt(const std::string &in){
int re = 0;
sscanf(in.c_str(), "%d", &re);
return re;
}
static float toFloat(const std::string &in) {
float re = 0;
sscanf(in.c_str(), "%f", &re);
return re;
}
static std::string toStr(float in) {
char chr[20] = { 0 };
sprintf(chr, "%f", in);
std::string re(chr);
return re;
}
static std::string toStr(int in){
char chr[20] = {0};
sprintf(chr, "%d", in);
std::string re(chr);
return re;
}
static std::string to4dStr(int in){
char chr[20] = {0};
sprintf(chr, "%04d", in);
std::string re(chr);
return re;
}
static std::string to5dStr(int in){
char chr[20] = {0};
sprintf(chr, "%05d", in);
std::string re(chr);
return re;
}
static std::string to6dStr(int in){
char chr[20] = {0};
sprintf(chr, "%06d", in);
std::string re(chr);
return re;
}
#endif
================================================
FILE: data/tt1.pb
================================================
[File too large to display: 10.7 MB]
================================================
FILE: deepsort/Detection.h
================================================
#ifndef _DETECTIONH_
#define _DETECTIONH_
#include
#include
typedef Eigen::Matrix DSBOX;
typedef Eigen::Matrix DSBOXS;
typedef Eigen::Matrix FEATURE;
typedef Eigen::Matrix FEATURESS;
typedef std::vector IDS;
typedef Eigen::Matrix PT2;
typedef Eigen::Matrix DYNAMICM;
typedef Eigen::Matrix MEAN;
typedef Eigen::Matrix VAR;
typedef Eigen::Matrix NMEAN;
typedef Eigen::Matrix NVAR;
struct Detection {
DSBOX tlwh_;
float confidence_;
FEATURE feature_;
int oriPos_ = -1;
Detection(const DSBOX &tlwh, float confidence, const FEATURE &feature) {
tlwh_ = tlwh;
confidence_ = confidence;
//std::cout << feature;
feature_ = feature;
}
DSBOX to_tlbr() const{
DSBOX ret = tlwh_;
ret(0, 2) += ret(0, 0);
ret(0, 3) += ret(0, 1);
return ret;
}
DSBOX to_xyah() const{
DSBOX ret = tlwh_;
ret(0, 0) += ret(0, 2) / 2;
ret(0, 1) += ret(0, 3) / 2;
ret(0, 2) /= ret(0, 3);
return ret;
}
};
#endif
================================================
FILE: deepsort/FeatureGetter/CaffeShuffeNetFeatureGetter.cpp
================================================
#include "FeatureGetter.h"
#include
#include
#include
#include
#include
#include