| | |
| | | #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 |
| | |
| | | float prob; // confidence - probability that the object was found correctly |
| | | unsigned int obj_id; // class of object - from range [0, classes-1] |
| | | unsigned int track_id; // tracking id for video (0 - untracked, 1 - inf - tracked object) |
| | | unsigned int frames_counter;// counter of frames on which the object was detected |
| | | }; |
| | | |
| | | struct image_t { |
| | |
| | | class Detector { |
| | | std::shared_ptr<void> detector_gpu_ptr; |
| | | std::deque<std::vector<bbox_t>> prev_bbox_vec_deque; |
| | | const int cur_gpu_id; |
| | | public: |
| | | float nms = .4; |
| | | bool wait_stream; |
| | | |
| | | YOLODLL_API Detector(std::string cfg_filename, std::string weight_filename, int gpu_id = 0); |
| | | YOLODLL_API ~Detector(); |
| | |
| | | YOLODLL_API int get_net_width() const; |
| | | YOLODLL_API int get_net_height() const; |
| | | |
| | | YOLODLL_API std::vector<bbox_t> tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story = 6); |
| | | YOLODLL_API std::vector<bbox_t> tracking_id(std::vector<bbox_t> cur_bbox_vec, bool const change_history = true, |
| | | int const frames_story = 6, int const max_dist = 150); |
| | | |
| | | #ifdef OPENCV |
| | | std::vector<bbox_t> detect(cv::Mat mat, float thresh = 0.2, bool use_mean = false) |
| | |
| | | return mat_to_image(det_mat); |
| | | } |
| | | |
| | | static std::shared_ptr<image_t> mat_to_image(cv::Mat img) |
| | | static std::shared_ptr<image_t> mat_to_image(cv::Mat img_src) |
| | | { |
| | | cv::Mat img; |
| | | cv::cvtColor(img_src, img, cv::COLOR_RGB2BGR); |
| | | std::shared_ptr<image_t> image_ptr(new image_t, [](image_t *img) { free_image(*img); delete img; }); |
| | | std::shared_ptr<IplImage> ipl_small = std::make_shared<IplImage>(img); |
| | | *image_ptr = ipl_to_image(ipl_small.get()); |
| | | rgbgr_image(*image_ptr); |
| | | return image_ptr; |
| | | } |
| | | |
| | |
| | | int c = src->nChannels; |
| | | int step = src->widthStep; |
| | | image_t out = make_image_custom(w, h, c); |
| | | int i, j, k, count = 0;; |
| | | int count = 0; |
| | | |
| | | for (k = 0; k < c; ++k) { |
| | | for (i = 0; i < h; ++i) { |
| | | for (j = 0; j < w; ++j) { |
| | | out.data[count++] = data[i*step + j*c + k] / 255.; |
| | | for (int k = 0; k < c; ++k) { |
| | | for (int i = 0; i < h; ++i) { |
| | | int i_step = i*step; |
| | | for (int j = 0; j < w; ++j) { |
| | | out.data[count++] = data[i_step + j*c + k] / 255.; |
| | | } |
| | | } |
| | | } |
| | | |
| | | return out; |
| | | } |
| | | |
| | |
| | | return out; |
| | | } |
| | | |
| | | static void rgbgr_image(image_t im) |
| | | { |
| | | int i; |
| | | for (i = 0; i < im.w*im.h; ++i) { |
| | | float swap = im.data[i]; |
| | | im.data[i] = im.data[i + im.w*im.h * 2]; |
| | | im.data[i + im.w*im.h * 2] = swap; |
| | | } |
| | | } |
| | | |
| | | #endif // OPENCV |
| | | |
| | | }; |
| | |
| | | |
| | | #if defined(TRACK_OPTFLOW) && defined(OPENCV) |
| | | |
| | | #include <opencv2/cudaoptflow.hpp> |
| | | #include <opencv2/cudaimgproc.hpp> |
| | | #include <opencv2/cudaarithm.hpp> |
| | | #include <opencv2/core/cuda.hpp> |
| | | |
| | | class Tracker_optflow { |
| | | public: |
| | | const int gpu_count; |
| | | const int gpu_id; |
| | | |
| | | |
| | | Tracker_optflow(int _gpu_id = 0) : gpu_count(cv::cuda::getCudaEnabledDeviceCount()), gpu_id(std::min(_gpu_id, gpu_count-1)) |
| | | { |
| | | int const old_gpu_id = cv::cuda::getDevice(); |
| | | cv::cuda::setDevice(gpu_id); |
| | | |
| | | stream = cv::cuda::Stream(); |
| | | |
| | | sync_PyrLKOpticalFlow_gpu = cv::cuda::SparsePyrLKOpticalFlow::create(); |
| | | sync_PyrLKOpticalFlow_gpu->setWinSize(cv::Size(9, 9)); // 15, 21, 31 |
| | | sync_PyrLKOpticalFlow_gpu->setMaxLevel(3); // +- 3 pt |
| | | sync_PyrLKOpticalFlow_gpu->setNumIters(2000); // def: 30 |
| | | |
| | | cv::cuda::setDevice(old_gpu_id); |
| | | } |
| | | |
| | | // just to avoid extra allocations |
| | | cv::cuda::GpuMat src_mat_gpu; |
| | | cv::cuda::GpuMat dst_mat_gpu, dst_grey_gpu; |
| | |
| | | |
| | | cv::cuda::GpuMat src_grey_gpu; // used in both functions |
| | | cv::Ptr<cv::cuda::SparsePyrLKOpticalFlow> sync_PyrLKOpticalFlow_gpu; |
| | | cv::cuda::Stream stream; |
| | | |
| | | void update_tracking_flow(cv::Mat src_mat, int gpu_id = 0) |
| | | void update_tracking_flow(cv::Mat src_mat) |
| | | { |
| | | int const old_gpu_id = cv::cuda::getDevice(); |
| | | static const int gpu_count = cv::cuda::getCudaEnabledDeviceCount(); |
| | | if (gpu_count > gpu_id) |
| | | if (old_gpu_id != 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_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); |
| | | if (old_gpu_id != gpu_id) |
| | | 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) |
| | | std::vector<bbox_t> tracking_flow(cv::Mat dst_mat, std::vector<bbox_t> cur_bbox_vec, bool check_error = false) |
| | | { |
| | | if (sync_PyrLKOpticalFlow_gpu.empty()) { |
| | | std::cout << "sync_PyrLKOpticalFlow_gpu isn't initialized \n"; |
| | |
| | | } |
| | | |
| | | int const old_gpu_id = cv::cuda::getDevice(); |
| | | static const int gpu_count = cv::cuda::getCudaEnabledDeviceCount(); |
| | | if (gpu_count > gpu_id) |
| | | if(old_gpu_id != 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) { |
| | |
| | | |
| | | 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.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); |
| | | |
| | |
| | | |
| | | 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) |
| | | if (!check_error || (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; |
| | |
| | | } |
| | | } |
| | | |
| | | cv::cuda::setDevice(old_gpu_id); |
| | | if (old_gpu_id != gpu_id) |
| | | cv::cuda::setDevice(old_gpu_id); |
| | | |
| | | return result_bbox_vec; |
| | | } |