#include #include #include #include #include #include #include #include #include // std::mutex, std::unique_lock #include // std::condition_variable #ifdef _WIN32 #define OPENCV #define GPU #endif // To use tracking - uncomment the following line. Tracking is supported only by OpenCV 3.x //#define TRACK_OPTFLOW #include "yolo_v2_class.hpp" // imported functions from DLL #ifdef OPENCV #include // C++ #include "opencv2/core/version.hpp" #ifndef CV_VERSION_EPOCH #include "opencv2/videoio/videoio.hpp" #define OPENCV_VERSION CVAUX_STR(CV_VERSION_MAJOR)""CVAUX_STR(CV_VERSION_MINOR)""CVAUX_STR(CV_VERSION_REVISION) #pragma comment(lib, "opencv_world" OPENCV_VERSION ".lib") #ifdef TRACK_OPTFLOW #pragma comment(lib, "opencv_cudaoptflow" OPENCV_VERSION ".lib") #pragma comment(lib, "opencv_cudaimgproc" OPENCV_VERSION ".lib") #pragma comment(lib, "opencv_core" OPENCV_VERSION ".lib") #pragma comment(lib, "opencv_imgproc" OPENCV_VERSION ".lib") #pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib") #endif // TRACK_OPTFLOW #else #define OPENCV_VERSION CVAUX_STR(CV_VERSION_EPOCH)""CVAUX_STR(CV_VERSION_MAJOR)""CVAUX_STR(CV_VERSION_MINOR) #pragma comment(lib, "opencv_core" OPENCV_VERSION ".lib") #pragma comment(lib, "opencv_imgproc" OPENCV_VERSION ".lib") #pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib") #endif // CV_VERSION_EPOCH class track_kalman { public: cv::KalmanFilter kf; int state_size, meas_size, contr_size; track_kalman(int _state_size = 10, int _meas_size = 10, int _contr_size = 0) : state_size(_state_size), meas_size(_meas_size), contr_size(_contr_size) { kf.init(state_size, meas_size, contr_size, CV_32F); cv::setIdentity(kf.measurementMatrix); cv::setIdentity(kf.measurementNoiseCov, cv::Scalar::all(1e-1)); cv::setIdentity(kf.processNoiseCov, cv::Scalar::all(1e-5)); cv::setIdentity(kf.errorCovPost, cv::Scalar::all(1e-2)); cv::setIdentity(kf.transitionMatrix); } void set(std::vector result_vec) { for (size_t i = 0; i < result_vec.size() && i < state_size*2; ++i) { kf.statePost.at(i * 2 + 0) = result_vec[i].x; kf.statePost.at(i * 2 + 1) = result_vec[i].y; } } // Kalman.correct() calculates: statePost = statePre + gain * (z(k)-measurementMatrix*statePre); // corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) std::vector correct(std::vector result_vec) { cv::Mat measurement(meas_size, 1, CV_32F); for (size_t i = 0; i < result_vec.size() && i < meas_size * 2; ++i) { measurement.at(i * 2 + 0) = result_vec[i].x; measurement.at(i * 2 + 1) = result_vec[i].y; } cv::Mat estimated = kf.correct(measurement); for (size_t i = 0; i < result_vec.size() && i < meas_size * 2; ++i) { result_vec[i].x = estimated.at(i * 2 + 0); result_vec[i].y = estimated.at(i * 2 + 1); } return result_vec; } // Kalman.predict() calculates: statePre = TransitionMatrix * statePost; // predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k) std::vector predict() { std::vector result_vec; cv::Mat control; cv::Mat prediction = kf.predict(control); for (size_t i = 0; i < prediction.rows && i < state_size * 2; ++i) { result_vec[i].x = prediction.at(i * 2 + 0); result_vec[i].y = prediction.at(i * 2 + 1); } return result_vec; } }; class extrapolate_coords_t { public: std::vector old_result_vec; std::vector dx_vec, dy_vec, time_vec; std::vector old_dx_vec, old_dy_vec; void new_result(std::vector new_result_vec, float new_time) { old_dx_vec = dx_vec; old_dy_vec = dy_vec; if (old_dx_vec.size() != old_result_vec.size()) std::cout << "old_dx != old_res \n"; dx_vec = std::vector(new_result_vec.size(), 0); dy_vec = std::vector(new_result_vec.size(), 0); update_result(new_result_vec, new_time, false); old_result_vec = new_result_vec; time_vec = std::vector(new_result_vec.size(), new_time); } void update_result(std::vector new_result_vec, float new_time, bool update = true) { for (size_t i = 0; i < new_result_vec.size(); ++i) { for (size_t k = 0; k < old_result_vec.size(); ++k) { if (old_result_vec[k].track_id == new_result_vec[i].track_id && old_result_vec[k].obj_id == new_result_vec[i].obj_id) { float const delta_time = new_time - time_vec[k]; if (abs(delta_time) < 1) break; size_t index = (update) ? k : i; float dx = ((float)new_result_vec[i].x - (float)old_result_vec[k].x) / delta_time; float dy = ((float)new_result_vec[i].y - (float)old_result_vec[k].y) / delta_time; float old_dx = dx, old_dy = dy; // if it's shaking if (update) { if (dx * dx_vec[i] < 0) dx = dx / 2; if (dy * dy_vec[i] < 0) dy = dy / 2; } else { if (dx * old_dx_vec[k] < 0) dx = dx / 2; if (dy * old_dy_vec[k] < 0) dy = dy / 2; } dx_vec[index] = dx; dy_vec[index] = dy; //if (old_dx == dx && old_dy == dy) std::cout << "not shakin \n"; //else std::cout << "shakin \n"; if (dx_vec[index] > 1000 || dy_vec[index] > 1000) { //std::cout << "!!! bad dx or dy, dx = " << dx_vec[index] << ", dy = " << dy_vec[index] << // ", delta_time = " << delta_time << ", update = " << update << std::endl; dx_vec[index] = 0; dy_vec[index] = 0; } old_result_vec[k].x = new_result_vec[i].x; old_result_vec[k].y = new_result_vec[i].y; time_vec[k] = new_time; break; } } } } std::vector predict(float cur_time) { std::vector result_vec = old_result_vec; for (size_t i = 0; i < old_result_vec.size(); ++i) { float const delta_time = cur_time - time_vec[i]; auto &bbox = result_vec[i]; float new_x = (float) bbox.x + dx_vec[i] * delta_time; float new_y = (float) bbox.y + dy_vec[i] * delta_time; if (new_x > 0) bbox.x = new_x; else bbox.x = 0; if (new_y > 0) bbox.y = new_y; else bbox.y = 0; } return result_vec; } }; void draw_boxes(cv::Mat mat_img, std::vector result_vec, std::vector obj_names, int current_det_fps = -1, int current_cap_fps = -1) { int const colors[6][3] = { { 1,0,1 },{ 0,0,1 },{ 0,1,1 },{ 0,1,0 },{ 1,1,0 },{ 1,0,0 } }; for (auto &i : result_vec) { cv::Scalar color = obj_id_to_color(i.obj_id); cv::rectangle(mat_img, cv::Rect(i.x, i.y, i.w, i.h), color, 2); if (obj_names.size() > 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); cv::Size const text_size = getTextSize(obj_name, cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, 2, 0); int const max_width = (text_size.width > i.w + 2) ? text_size.width : (i.w + 2); cv::rectangle(mat_img, cv::Point2f(std::max((int)i.x - 1, 0), std::max((int)i.y - 30, 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); } } if (current_det_fps >= 0 && current_cap_fps >= 0) { std::string fps_str = "FPS detection: " + std::to_string(current_det_fps) + " FPS capture: " + std::to_string(current_cap_fps); putText(mat_img, fps_str, cv::Point2f(10, 20), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, cv::Scalar(50, 255, 0), 2); } } #endif // OPENCV void show_console_result(std::vector const result_vec, std::vector const obj_names) { for (auto &i : result_vec) { if (obj_names.size() > i.obj_id) std::cout << obj_names[i.obj_id] << " - "; std::cout << "obj_id = " << i.obj_id << ", x = " << i.x << ", y = " << i.y << ", w = " << i.w << ", h = " << i.h << std::setprecision(3) << ", prob = " << i.prob << std::endl; } } std::vector objects_names_from_file(std::string const filename) { std::ifstream file(filename); std::vector file_lines; if (!file.is_open()) return file_lines; for(std::string line; getline(file, line);) file_lines.push_back(line); std::cout << "object names loaded \n"; return file_lines; } int main(int argc, char *argv[]) { std::string names_file = "data/voc.names"; std::string cfg_file = "cfg/yolo-voc.cfg"; std::string weights_file = "yolo-voc.weights"; std::string filename; if (argc > 4) { //voc.names yolo-voc.cfg yolo-voc.weights test.mp4 names_file = argv[1]; cfg_file = argv[2]; weights_file = argv[3]; filename = argv[4]; } else if (argc > 1) filename = argv[1]; float const thresh = (argc > 5) ? std::stof(argv[5]) : 0.20; Detector detector(cfg_file, weights_file); auto obj_names = objects_names_from_file(names_file); std::string out_videofile = "result.avi"; bool const save_output_videofile = true; #ifdef TRACK_OPTFLOW Tracker_optflow tracker_flow; detector.wait_stream = true; #endif while (true) { std::cout << "input image or video filename: "; if(filename.size() == 0) std::cin >> filename; if (filename.size() == 0) break; try { #ifdef OPENCV extrapolate_coords_t extrapolate_coords; bool extrapolate_flag = false; float cur_time_extrapolate = 0, old_time_extrapolate = 0; preview_boxes_t large_preview(100, 150, false), small_preview(50, 50, true); bool show_small_boxes = false; std::string const file_ext = filename.substr(filename.find_last_of(".") + 1); std::string const protocol = filename.substr(0, 7); if (file_ext == "avi" || file_ext == "mp4" || file_ext == "mjpg" || file_ext == "mov" || // video file protocol == "rtmp://" || protocol == "rtsp://" || protocol == "http://" || protocol == "https:/") // video network stream { cv::Mat cap_frame, cur_frame, det_frame, write_frame; std::queue track_optflow_queue; int passed_flow_frames = 0; std::shared_ptr det_image; std::vector result_vec, thread_result_vec; detector.nms = 0.02; // comment it - if track_id is not required std::atomic consumed, videowrite_ready; consumed = true; videowrite_ready = true; std::atomic fps_det_counter, fps_cap_counter; fps_det_counter = 0; fps_cap_counter = 0; int current_det_fps = 0, current_cap_fps = 0; std::thread t_detect, t_cap, t_videowrite; std::mutex mtx; std::condition_variable cv_detected, cv_pre_tracked; std::chrono::steady_clock::time_point steady_start, steady_end; cv::VideoCapture cap(filename); cap >> cur_frame; int const video_fps = cap.get(CV_CAP_PROP_FPS); cv::Size const frame_size = cur_frame.size(); cv::VideoWriter output_video; if (save_output_videofile) output_video.open(out_videofile, CV_FOURCC('D', 'I', 'V', 'X'), std::max(35, video_fps), frame_size, true); while (!cur_frame.empty()) { // always sync if (t_cap.joinable()) { t_cap.join(); ++fps_cap_counter; cur_frame = cap_frame.clone(); } t_cap = std::thread([&]() { cap >> cap_frame; }); ++cur_time_extrapolate; // swap result bouned-boxes and input-frame if(consumed) { std::unique_lock lock(mtx); det_image = detector.mat_to_image_resize(cur_frame); auto old_result_vec = detector.tracking_id(result_vec); auto detected_result_vec = thread_result_vec; result_vec = detected_result_vec; #ifdef TRACK_OPTFLOW // track optical flow if (track_optflow_queue.size() > 0) { //std::cout << "\n !!!! all = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl; cv::Mat first_frame = track_optflow_queue.front(); tracker_flow.update_tracking_flow(track_optflow_queue.front(), result_vec); while (track_optflow_queue.size() > 1) { track_optflow_queue.pop(); result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), true); } track_optflow_queue.pop(); passed_flow_frames = 0; result_vec = detector.tracking_id(result_vec); auto tmp_result_vec = detector.tracking_id(detected_result_vec, false); small_preview.set(first_frame, tmp_result_vec); extrapolate_coords.new_result(tmp_result_vec, old_time_extrapolate); old_time_extrapolate = cur_time_extrapolate; extrapolate_coords.update_result(result_vec, cur_time_extrapolate - 1); } #else result_vec = detector.tracking_id(result_vec); // comment it - if track_id is not required extrapolate_coords.new_result(result_vec, cur_time_extrapolate - 1); #endif // add old tracked objects for (auto &i : old_result_vec) { auto it = std::find_if(result_vec.begin(), result_vec.end(), [&i](bbox_t const& b) { return b.track_id == i.track_id && b.obj_id == i.obj_id; }); bool track_id_absent = (it == result_vec.end()); if (track_id_absent) { if (i.frames_counter-- > 1) result_vec.push_back(i); } else { it->frames_counter = std::min((unsigned)3, i.frames_counter + 1); } } #ifdef TRACK_OPTFLOW tracker_flow.update_cur_bbox_vec(result_vec); result_vec = tracker_flow.tracking_flow(cur_frame, true); // track optical flow #endif consumed = false; cv_pre_tracked.notify_all(); } // launch thread once - Detection if (!t_detect.joinable()) { t_detect = std::thread([&]() { auto current_image = det_image; consumed = true; while (current_image.use_count() > 0) { auto result = detector.detect_resized(*current_image, frame_size.width, frame_size.height, thresh, false); // true ++fps_det_counter; std::unique_lock lock(mtx); thread_result_vec = result; consumed = true; cv_detected.notify_all(); if (detector.wait_stream) { while (consumed) cv_pre_tracked.wait(lock); } current_image = det_image; } }); } //while (!consumed); // sync detection if (!cur_frame.empty()) { steady_end = std::chrono::steady_clock::now(); if (std::chrono::duration(steady_end - steady_start).count() >= 1) { current_det_fps = fps_det_counter; current_cap_fps = fps_cap_counter; steady_start = steady_end; fps_det_counter = 0; fps_cap_counter = 0; } large_preview.set(cur_frame, result_vec); #ifdef TRACK_OPTFLOW ++passed_flow_frames; track_optflow_queue.push(cur_frame.clone()); result_vec = tracker_flow.tracking_flow(cur_frame); // track optical flow extrapolate_coords.update_result(result_vec, cur_time_extrapolate); small_preview.draw(cur_frame, show_small_boxes); #endif auto result_vec_draw = result_vec; if (extrapolate_flag) { result_vec_draw = extrapolate_coords.predict(cur_time_extrapolate); cv::putText(cur_frame, "extrapolate", cv::Point2f(10, 40), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.0, cv::Scalar(50, 50, 0), 2); } draw_boxes(cur_frame, result_vec_draw, obj_names, current_det_fps, current_cap_fps); //show_console_result(result_vec, obj_names); large_preview.draw(cur_frame); cv::imshow("window name", cur_frame); int key = cv::waitKey(3); // 3 or 16ms if (key == 'f') show_small_boxes = !show_small_boxes; if (key == 'p') while (true) if(cv::waitKey(100) == 'p') break; if (key == 'e') extrapolate_flag = !extrapolate_flag; if (output_video.isOpened() && videowrite_ready) { if (t_videowrite.joinable()) t_videowrite.join(); write_frame = cur_frame.clone(); videowrite_ready = false; t_videowrite = std::thread([&]() { output_video << write_frame; videowrite_ready = true; }); } } #ifndef TRACK_OPTFLOW // wait detection result for video-file only (not for net-cam) if (protocol != "rtsp://" && protocol != "http://" && protocol != "https:/") { std::unique_lock lock(mtx); while (!consumed) cv_detected.wait(lock); } #endif } if (t_cap.joinable()) t_cap.join(); if (t_detect.joinable()) t_detect.join(); if (t_videowrite.joinable()) t_videowrite.join(); std::cout << "Video ended \n"; } else if (file_ext == "txt") { // list of image files std::ifstream file(filename); if (!file.is_open()) std::cout << "File not found! \n"; else for (std::string line; file >> line;) { std::cout << line << std::endl; cv::Mat mat_img = cv::imread(line); std::vector result_vec = detector.detect(mat_img); show_console_result(result_vec, obj_names); //draw_boxes(mat_img, result_vec, obj_names); //cv::imwrite("res_" + line, mat_img); } } else { // image file cv::Mat mat_img = cv::imread(filename); std::vector result_vec = detector.detect(mat_img); result_vec = detector.tracking_id(result_vec); // comment it - if track_id is not required draw_boxes(mat_img, result_vec, obj_names); cv::imshow("window name", mat_img); cv::waitKey(3); // 3 or 16ms show_console_result(result_vec, obj_names); } #else //std::vector result_vec = detector.detect(filename); auto img = detector.load_image(filename); std::vector result_vec = detector.detect(img); detector.free_image(img); show_console_result(result_vec, obj_names); #endif } catch (std::exception &e) { std::cerr << "exception: " << e.what() << "\n"; getchar(); } catch (...) { std::cerr << "unknown exception \n"; getchar(); } filename.clear(); } return 0; }