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Fixed - use individual track_id for each class of object

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This commit is contained in:
AlexeyAB
2017-08-08 18:23:57 +03:00
parent b202eaee25
commit 4528f9b4b4
3 changed files with 19 additions and 10 deletions
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13
src/yolo_console_dll.cpp
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@ -31,9 +31,10 @@ void draw_boxes(cv::Mat mat_img, std::vector<bbox_t> result_vec, std::vector<std
std::string obj_name = obj_names[i.obj_id]; std::string obj_name = obj_names[i.obj_id];
if (i.track_id > 0) obj_name += " - " + std::to_string(i.track_id); if (i.track_id > 0) obj_name += " - " + std::to_string(i.track_id);
cv::Size const text_size = getTextSize(obj_name, cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, 2, 0); cv::Size const text_size = getTextSize(obj_name, cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, 2, 0);
size_t const max_width = (text_size.width > i.w + 2) ? text_size.width : (i.w + 2); int const max_width = (text_size.width > i.w + 2) ? text_size.width : (i.w + 2);
if(i.x > 3 && (i.x + max_width) < mat_img.cols && i.y > 30 && i.y < mat_img.rows) cv::rectangle(mat_img, cv::Point2f(std::max((int)i.x - 3, 0), std::max((int)i.y - 30, 0)),
cv::rectangle(mat_img, cv::Point2f(i.x - 3, i.y - 30), cv::Point2f(i.x + max_width, i.y), color, CV_FILLED, 8, 0); cv::Point2f(std::min((int)i.x + max_width, mat_img.cols-1), std::min((int)i.y, mat_img.rows-1)),
color, CV_FILLED, 8, 0);
putText(mat_img, obj_name, cv::Point2f(i.x, i.y - 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, cv::Scalar(0, 0, 0), 2); putText(mat_img, obj_name, cv::Point2f(i.x, i.y - 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, cv::Scalar(0, 0, 0), 2);
} }
} }
@ -79,7 +80,9 @@ int main()
#ifdef OPENCV #ifdef OPENCV
std::string const file_ext = filename.substr(filename.find_last_of(".") + 1); std::string const file_ext = filename.substr(filename.find_last_of(".") + 1);
std::string const protocol = filename.substr(0, 4); std::string const protocol = filename.substr(0, 4);
if (file_ext == "avi" || file_ext == "mp4" || file_ext == "mjpg" || file_ext == "mov" || protocol == "rtsp") { // video file if (file_ext == "avi" || file_ext == "mp4" || file_ext == "mjpg" || file_ext == "mov" || // video file
protocol == "rtsp" || protocol == "http") // video network stream
{
cv::Mat frame, prev_frame, det_frame; cv::Mat frame, prev_frame, det_frame;
std::vector<bbox_t> result_vec, thread_result_vec; std::vector<bbox_t> result_vec, thread_result_vec;
detector.nms = 0.02; // comment it - if track_id is not required detector.nms = 0.02; // comment it - if track_id is not required
@ -98,7 +101,7 @@ int main()
show_result(result_vec, obj_names); show_result(result_vec, obj_names);
} }
prev_frame = frame; prev_frame = frame;
//if(protocol == "rtsp") while (!ready_flag) cap.grab(); // use if cam-fps 2x or more than dnn-fps //if (protocol == "rtsp" || protocol == "http") do { cap.grab(); } while (!ready_flag); // use if cam-fps 2x or more than dnn-fps
ready_flag = false; ready_flag = false;
} }
} }

14
src/yolo_v2_class.cpp
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@ -30,6 +30,7 @@ struct detector_gpu_t{
float *avg; float *avg;
float *predictions[FRAMES]; float *predictions[FRAMES];
int demo_index; int demo_index;
unsigned int *track_id;
}; };
@ -71,6 +72,9 @@ YOLODLL_API Detector::Detector(std::string cfg_filename, std::string weight_file
detector_gpu.probs = (float **)calloc(l.w*l.h*l.n, sizeof(float *)); detector_gpu.probs = (float **)calloc(l.w*l.h*l.n, sizeof(float *));
for (j = 0; j < l.w*l.h*l.n; ++j) detector_gpu.probs[j] = (float *)calloc(l.classes, sizeof(float)); for (j = 0; j < l.w*l.h*l.n; ++j) detector_gpu.probs[j] = (float *)calloc(l.classes, sizeof(float));
detector_gpu.track_id = (unsigned int *)calloc(l.classes, sizeof(unsigned int));
for (j = 0; j < l.classes; ++j) detector_gpu.track_id[j] = 1;
#ifdef GPU #ifdef GPU
cudaSetDevice(old_gpu_index); cudaSetDevice(old_gpu_index);
#endif #endif
@ -82,6 +86,8 @@ YOLODLL_API Detector::~Detector()
detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get()); detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
layer l = detector_gpu.net.layers[detector_gpu.net.n - 1]; layer l = detector_gpu.net.layers[detector_gpu.net.n - 1];
free(detector_gpu.track_id);
free(detector_gpu.avg); free(detector_gpu.avg);
for (int j = 0; j < FRAMES; ++j) free(detector_gpu.predictions[j]); for (int j = 0; j < FRAMES; ++j) free(detector_gpu.predictions[j]);
for (int j = 0; j < FRAMES; ++j) if(detector_gpu.images[j].data) free(detector_gpu.images[j].data); for (int j = 0; j < FRAMES; ++j) if(detector_gpu.images[j].data) free(detector_gpu.images[j].data);
@ -244,16 +250,16 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh, bool
YOLODLL_API std::vector<bbox_t> Detector::tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story) YOLODLL_API std::vector<bbox_t> Detector::tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story)
{ {
detector_gpu_t &det_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
bool prev_track_id_present = false; bool prev_track_id_present = false;
for (auto &i : prev_bbox_vec_deque) for (auto &i : prev_bbox_vec_deque)
if (i.size() > 0) prev_track_id_present = true; if (i.size() > 0) prev_track_id_present = true;
static unsigned int track_id = 1;
if (!prev_track_id_present) { if (!prev_track_id_present) {
//track_id = 1; //track_id = 1;
for (size_t i = 0; i < cur_bbox_vec.size(); ++i) for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
cur_bbox_vec[i].track_id = track_id++; cur_bbox_vec[i].track_id = det_gpu.track_id[cur_bbox_vec[i].obj_id]++;
prev_bbox_vec_deque.push_front(cur_bbox_vec); prev_bbox_vec_deque.push_front(cur_bbox_vec);
if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back(); if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back();
return cur_bbox_vec; return cur_bbox_vec;
@ -287,7 +293,7 @@ YOLODLL_API std::vector<bbox_t> Detector::tracking(std::vector<bbox_t> cur_bbox_
for (size_t i = 0; i < cur_bbox_vec.size(); ++i) for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
if (cur_bbox_vec[i].track_id == 0) if (cur_bbox_vec[i].track_id == 0)
cur_bbox_vec[i].track_id = track_id++; cur_bbox_vec[i].track_id = det_gpu.track_id[cur_bbox_vec[i].obj_id]++;
prev_bbox_vec_deque.push_front(cur_bbox_vec); prev_bbox_vec_deque.push_front(cur_bbox_vec);
if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back(); if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back();

2
src/yolo_v2_class.hpp
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@ -54,7 +54,7 @@ public:
YOLODLL_API int get_net_width(); YOLODLL_API int get_net_width();
YOLODLL_API int get_net_height(); YOLODLL_API int get_net_height();
YOLODLL_API std::vector<bbox_t> tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story = 4); YOLODLL_API std::vector<bbox_t> tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story = 6);
#ifdef OPENCV #ifdef OPENCV
std::vector<bbox_t> detect(cv::Mat mat, float thresh = 0.2, bool use_mean = false) std::vector<bbox_t> detect(cv::Mat mat, float thresh = 0.2, bool use_mean = false)