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https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
Changed example of DLL/SO usage to work faster
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@ -76,18 +76,19 @@ int main()
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cv::Mat frame, prev_frame;
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std::vector<bbox_t> result_vec, thread_result_vec;
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detector.nms = 0.02; // comment it - if track_id is not required
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std::thread td([]() {});
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for (cv::VideoCapture cap(filename); cap >> frame, cap.isOpened();) {
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auto image_ptr = detector.mat_to_image(frame);
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std::thread td([&]() { thread_result_vec = detector.detect(*image_ptr, 0.2); });
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td.join();
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result_vec = thread_result_vec;
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cv::Mat det_frame = frame;
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td = std::thread([&]() { thread_result_vec = detector.detect(det_frame, 0.2); });
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if (!prev_frame.empty()) {
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result_vec = detector.tracking(result_vec); // comment it - if track_id is not required
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draw_boxes(prev_frame, result_vec, obj_names, 3);
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show_result(result_vec, obj_names);
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}
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td.join();
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prev_frame = frame;
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result_vec = thread_result_vec;
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}
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}
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else { // image file
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@ -102,6 +102,15 @@ YOLODLL_API Detector::~Detector()
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#endif
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}
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YOLODLL_API int Detector::get_net_width() {
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detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
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return detector_gpu.net.w;
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}
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YOLODLL_API int Detector::get_net_height() {
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detector_gpu_t &detector_gpu = *reinterpret_cast<detector_gpu_t *>(detector_gpu_ptr.get());
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return detector_gpu.net.h;
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}
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YOLODLL_API std::vector<bbox_t> Detector::detect(std::string image_filename, float thresh)
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{
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@ -51,6 +51,8 @@ public:
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YOLODLL_API std::vector<bbox_t> detect(image_t img, float thresh = 0.2);
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static YOLODLL_API image_t load_image(std::string image_filename);
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static YOLODLL_API void free_image(image_t m);
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YOLODLL_API int get_net_width();
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YOLODLL_API int get_net_height();
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YOLODLL_API std::vector<bbox_t> tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story = 4);
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@ -59,8 +61,13 @@ public:
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{
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if(mat.data == NULL)
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throw std::runtime_error("file not found");
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auto image_ptr = mat_to_image(mat);
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return detect(*image_ptr, thresh);
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cv::Mat det_mat;
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cv::resize(mat, det_mat, cv::Size(get_net_width(), get_net_height()));
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auto image_ptr = mat_to_image(det_mat);
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auto detection_boxes = detect(*image_ptr, thresh);
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float wk = (float)mat.cols / det_mat.cols, hk = (float)mat.rows / det_mat.rows;
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for (auto &i : detection_boxes) i.x*=wk, i.w*= wk, i.y*=hk, i.h*=hk;
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return detection_boxes;
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}
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static std::shared_ptr<image_t> mat_to_image(cv::Mat img)
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