| src/detector.c | ●●●●● patch | view | raw | blame | history | |
| src/yolo_console_dll.cpp | ●●●●● patch | view | raw | blame | history | |
| src/yolo_v2_class.hpp | ●●●●● patch | view | raw | blame | history |
src/detector.c
@@ -399,7 +399,7 @@ int m = plist->size; int i=0; float thresh = .2;// .001; float thresh = .001;// .001; // .2; float iou_thresh = .5; float nms = .4;
@@ -2,6 +2,7 @@ #include <iomanip> #include <string> #include <vector> #include <queue> #include <fstream> #include <thread> #include <atomic> @@ -10,8 +11,10 @@ #ifdef _WIN32 #define OPENCV #include "windows.h" #endif #define TRACK_OPTFLOW #include "yolo_v2_class.hpp" // imported functions from DLL #ifdef OPENCV @@ -21,6 +24,11 @@ #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") #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") #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") @@ -85,11 +93,15 @@ std::string filename; if (argc > 1) filename = argv[1]; Detector detector("cfg/yolo-voc.cfg", "yolo-voc.weights"); //Detector detector("cfg/yolo-voc.cfg", "yolo-voc.weights"); Detector detector("tiny-yolo-voc_air.cfg", "backup/tiny-yolo-voc_air_5000.weights"); auto obj_names = objects_names_from_file("data/voc.names"); std::string out_videofile = "result.avi"; bool const save_output_videofile = false; #ifdef TRACK_OPTFLOW Tracker_optflow tracker_flow; #endif while (true) { @@ -105,6 +117,8 @@ protocol == "rtmp://" || protocol == "rtsp://" || protocol == "http://" || protocol == "https:/") // video network stream { cv::Mat cap_frame, cur_frame, det_frame, write_frame; std::queue<cv::Mat> track_optflow_queue; int passed_flow_frames = 0; std::shared_ptr<image_t> det_image; std::vector<bbox_t> result_vec, thread_result_vec; detector.nms = 0.02; // comment it - if track_id is not required @@ -126,7 +140,9 @@ 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()) { while (!cur_frame.empty()) { // always sync if (t_cap.joinable()) { t_cap.join(); ++fps_cap_counter; @@ -134,22 +150,79 @@ } t_cap = std::thread([&]() { cap >> cap_frame; }); // swap result and input-frame // swap result bouned-boxes and input-frame if(consumed) { { std::unique_lock<std::mutex> lock(mtx); det_image = detector.mat_to_image_resize(cur_frame); result_vec = thread_result_vec; result_vec = detector.tracking(result_vec); // comment it - if track_id is not required consumed = false; } // launch thread once #ifdef TRACK_OPTFLOW int y = 0, x = 0; cv::Mat show_flow = cur_frame.clone(); auto lambda = [&x, &y](cv::Mat draw_frame, cv::Mat src_frame, std::vector<bbox_t> result_vec) { //if (x > 10) return; if (result_vec.size() == 0) return; bbox_t i = result_vec[0]; //cv::Rect r(i.x, i.y, i.w, i.h); cv::Rect r(i.x + (i.w-31)/2, i.y + (i.h - 31)/2, 31, 31); cv::Rect img_rect(cv::Point2i(0, 0), src_frame.size()); cv::Rect rect_roi = r & img_rect; if (rect_roi.width < 1 || rect_roi.height < 1) return; cv::Mat roi = src_frame(rect_roi); cv::Mat dst; cv::resize(roi, dst, cv::Size(100, 100)); if (x > 10) x = 0, ++y; cv::Rect dst_rect_roi(cv::Point2i(x*100, y*100), dst.size()); cv::Mat dst_roi = draw_frame(dst_rect_roi); dst.copyTo(dst_roi); ++x; }; // track optical flow if (track_optflow_queue.size() > 0) { std::queue<cv::Mat> new_track_optflow_queue; std::cout << "\n !!!! all = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl; //draw_boxes(track_optflow_queue.front().clone(), result_vec, obj_names, 3, current_det_fps, current_cap_fps); //cv::waitKey(10); tracker_flow.update_tracking_flow(track_optflow_queue.front()); lambda(show_flow, track_optflow_queue.front(), result_vec); track_optflow_queue.pop(); while(track_optflow_queue.size() > 0) { //draw_boxes(track_optflow_queue.front().clone(), result_vec, obj_names, 3, current_det_fps, current_cap_fps); //cv::waitKey(10); result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), result_vec); if (track_optflow_queue.size() <= passed_flow_frames && new_track_optflow_queue.size() == 0) new_track_optflow_queue = track_optflow_queue; lambda(show_flow, track_optflow_queue.front(), result_vec); track_optflow_queue.pop(); } track_optflow_queue = new_track_optflow_queue; new_track_optflow_queue.swap(std::queue<cv::Mat>()); passed_flow_frames = 0; std::cout << "\n !!!! now = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl; cv::imshow("flow", show_flow); cv::waitKey(3); } #endif } // 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, 0.24, true); auto result = detector.detect_resized(*current_image, frame_size, 0.24, false); // true Sleep(500); ++fps_det_counter; std::unique_lock<std::mutex> lock(mtx); thread_result_vec = result; @@ -169,6 +242,13 @@ fps_det_counter = 0; fps_cap_counter = 0; } #ifdef TRACK_OPTFLOW ++passed_flow_frames; track_optflow_queue.push(cur_frame.clone()); result_vec = tracker_flow.tracking_flow(cur_frame, result_vec); // track optical flow #endif draw_boxes(cur_frame, result_vec, obj_names, 3, current_det_fps, current_cap_fps); //show_console_result(result_vec, obj_names); @@ -183,10 +263,10 @@ } // wait detection result for video-file only (not for net-cam) if (protocol != "rtsp://" && protocol != "http://" && protocol != "https:/") { std::unique_lock<std::mutex> lock(mtx); while (!consumed) cv.wait(lock); } //if (protocol != "rtsp://" && protocol != "http://" && protocol != "https:/") { // std::unique_lock<std::mutex> lock(mtx); // while (!consumed) cv.wait(lock); //} } if (t_cap.joinable()) t_cap.join(); if (t_detect.joinable()) t_detect.join(); src/yolo_v2_class.hpp
@@ -8,6 +8,11 @@ #include <opencv2/opencv.hpp> // C++ #include "opencv2/highgui/highgui_c.h" // C #include "opencv2/imgproc/imgproc_c.h" // C #include <opencv2/cudaoptflow.hpp> #include <opencv2/cudaimgproc.hpp> #include <opencv2/cudaarithm.hpp> #include "opencv2/core/cuda.hpp" #endif // OPENCV #ifdef YOLODLL_EXPORTS @@ -41,6 +46,7 @@ class Detector { std::shared_ptr<void> detector_gpu_ptr; std::deque<std::vector<bbox_t>> prev_bbox_vec_deque; public: float nms = .4; @@ -93,6 +99,7 @@ } private: static image_t ipl_to_image(IplImage* src) { unsigned char *data = (unsigned char *)src->imageData; @@ -142,8 +149,165 @@ #endif // OPENCV std::deque<std::vector<bbox_t>> prev_bbox_vec_deque; }; #if defined(TRACK_OPTFLOW) && defined(OPENCV) class Tracker_optflow { public: // just to avoid extra allocations cv::cuda::GpuMat src_mat_gpu; cv::cuda::GpuMat dst_mat_gpu, dst_grey_gpu; cv::cuda::GpuMat tmp_grey_gpu; cv::cuda::GpuMat prev_pts_flow_gpu, cur_pts_flow_gpu; cv::cuda::GpuMat status_gpu, err_gpu; cv::cuda::GpuMat src_grey_gpu; // used in both functions cv::Ptr<cv::cuda::SparsePyrLKOpticalFlow> sync_PyrLKOpticalFlow_gpu; void update_tracking_flow(cv::Mat src_mat, int gpu_id = 0) { int const old_gpu_id = cv::cuda::getDevice(); static const int gpu_count = cv::cuda::getCudaEnabledDeviceCount(); if (gpu_count > gpu_id) cv::cuda::setDevice(gpu_id); cv::cuda::Stream stream; if (sync_PyrLKOpticalFlow_gpu.empty()) { sync_PyrLKOpticalFlow_gpu = cv::cuda::SparsePyrLKOpticalFlow::create(); //sync_PyrLKOpticalFlow_gpu->setWinSize(cv::Size(31, 31)); //sync_PyrLKOpticalFlow_gpu.winSize = cv::Size(31, 31); //sync_PyrLKOpticalFlow_gpu->setWinSize(cv::Size(15, 15)); //sync_PyrLKOpticalFlow_gpu.winSize = cv::Size(15, 15); sync_PyrLKOpticalFlow_gpu->setWinSize(cv::Size(21, 21)); sync_PyrLKOpticalFlow_gpu->setMaxLevel(3); //sync_PyrLKOpticalFlow_gpu.maxLevel = 8; // +-32 points // def: 3 sync_PyrLKOpticalFlow_gpu->setNumIters(6000); //sync_PyrLKOpticalFlow_gpu.iters = 8000; // def: 30 //??? //sync_PyrLKOpticalFlow_gpu.getMinEigenVals = true; //std::cout << "sync_PyrLKOpticalFlow_gpu.maxLevel: " << sync_PyrLKOpticalFlow_gpu.maxLevel << std::endl; //std::cout << "sync_PyrLKOpticalFlow_gpu.iters: " << sync_PyrLKOpticalFlow_gpu.iters << std::endl; //std::cout << "sync_PyrLKOpticalFlow_gpu.winSize: " << sync_PyrLKOpticalFlow_gpu.winSize << std::endl; } if (src_mat.channels() == 3) { if (src_mat_gpu.cols == 0) { src_mat_gpu = cv::cuda::GpuMat(src_mat.size(), src_mat.type()); src_grey_gpu = cv::cuda::GpuMat(src_mat.size(), CV_8UC1); } src_mat_gpu.upload(src_mat, stream); cv::cuda::cvtColor(src_mat_gpu, src_grey_gpu, CV_BGR2GRAY, 0, stream); //std::cout << " \n\n OK !!! \n\n"; } cv::cuda::setDevice(old_gpu_id); } std::vector<bbox_t> tracking_flow(cv::Mat dst_mat, std::vector<bbox_t> cur_bbox_vec, int gpu_id = 0) { if (sync_PyrLKOpticalFlow_gpu.empty()) { std::cout << "sync_PyrLKOpticalFlow_gpu isn't initialized \n"; return cur_bbox_vec; } int const old_gpu_id = cv::cuda::getDevice(); static const int gpu_count = cv::cuda::getCudaEnabledDeviceCount(); if (gpu_count > gpu_id) cv::cuda::setDevice(gpu_id); cv::cuda::Stream stream; if (dst_mat_gpu.cols == 0) { dst_mat_gpu = cv::cuda::GpuMat(dst_mat.size(), dst_mat.type()); dst_grey_gpu = cv::cuda::GpuMat(dst_mat.size(), CV_8UC1); tmp_grey_gpu = cv::cuda::GpuMat(dst_mat.size(), CV_8UC1); } dst_mat_gpu.upload(dst_mat, stream); cv::cuda::cvtColor(dst_mat_gpu, dst_grey_gpu, CV_BGR2GRAY, 0, stream); if (src_grey_gpu.rows != dst_grey_gpu.rows || src_grey_gpu.cols != dst_grey_gpu.cols) { stream.waitForCompletion(); src_grey_gpu = dst_grey_gpu.clone(); cv::cuda::setDevice(old_gpu_id); return cur_bbox_vec; } cv::Mat prev_pts, prev_pts_flow_cpu, cur_pts_flow_cpu; for (auto &i : cur_bbox_vec) { float x_center = (i.x + i.w / 2); float y_center = (i.y + i.h / 2); prev_pts.push_back(cv::Point2f(x_center, y_center)); } if (prev_pts.rows == 0) prev_pts_flow_cpu = cv::Mat(); else cv::transpose(prev_pts, prev_pts_flow_cpu); if (prev_pts_flow_gpu.cols < prev_pts_flow_cpu.cols) { prev_pts_flow_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), prev_pts_flow_cpu.type()); cur_pts_flow_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), prev_pts_flow_cpu.type()); status_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), CV_8UC1); err_gpu = cv::cuda::GpuMat(prev_pts_flow_cpu.size(), CV_32FC1); } prev_pts_flow_gpu.upload(cv::Mat(prev_pts_flow_cpu), stream); dst_grey_gpu.copyTo(tmp_grey_gpu, stream); //sync_PyrLKOpticalFlow_gpu.sparse(src_grey_gpu, dst_grey_gpu, prev_pts_flow_gpu, cur_pts_flow_gpu, status_gpu, &err_gpu); // OpenCV 2.4.x sync_PyrLKOpticalFlow_gpu->calc(src_grey_gpu, dst_grey_gpu, prev_pts_flow_gpu, cur_pts_flow_gpu, status_gpu, err_gpu, stream); // OpenCV 3.x //std::cout << "\n 1-e \n"; cur_pts_flow_gpu.download(cur_pts_flow_cpu, stream); tmp_grey_gpu.copyTo(src_grey_gpu, stream); cv::Mat err_cpu, status_cpu; err_gpu.download(err_cpu, stream); status_gpu.download(status_cpu, stream); stream.waitForCompletion(); std::vector<bbox_t> result_bbox_vec; for (size_t i = 0; i < cur_bbox_vec.size(); ++i) { cv::Point2f cur_key_pt = cur_pts_flow_cpu.at<cv::Point2f>(0, i); cv::Point2f prev_key_pt = prev_pts_flow_cpu.at<cv::Point2f>(0, i); float moved_x = cur_key_pt.x - prev_key_pt.x; float moved_y = cur_key_pt.y - prev_key_pt.y; if (err_cpu.cols > i && status_cpu.cols > i) if (abs(moved_x) < 100 && abs(moved_y) < 100) //if (err_cpu.at<float>(0, i) < 60 && status_cpu.at<unsigned char>(0, i) != 0) { cur_bbox_vec[i].x += moved_x + 0.5; cur_bbox_vec[i].y += moved_y + 0.5; result_bbox_vec.push_back(cur_bbox_vec[i]); } } cv::cuda::setDevice(old_gpu_id); return result_bbox_vec; } }; #else class Tracker_optflow {}; #endif // defined(TRACK_OPTFLOW) && defined(OPENCV)
