| build/darknet/yolo_console_dll.vcxproj | ●●●●● patch | view | raw | blame | history | |
| build/darknet/yolo_cpp_dll.vcxproj | ●●●●● patch | view | raw | blame | history | |
| src/cuda.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 |
build/darknet/yolo_console_dll.vcxproj
@@ -118,6 +118,7 @@ <AdditionalIncludeDirectories>C:\opencv_source\opencv\bin\install\include</AdditionalIncludeDirectories> <PreprocessorDefinitions>_CRT_SECURE_NO_WARNINGS;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions> <ExceptionHandling>Async</ExceptionHandling> <OpenMPSupport>true</OpenMPSupport> </ClCompile> <Link> <EnableCOMDATFolding>true</EnableCOMDATFolding> build/darknet/yolo_cpp_dll.vcxproj
@@ -134,7 +134,7 @@ <IntrinsicFunctions>true</IntrinsicFunctions> <SDLCheck>true</SDLCheck> <AdditionalIncludeDirectories>..\..\3rdparty\include;%(AdditionalIncludeDirectories);$(CudaToolkitIncludeDir);$(cudnn)\include</AdditionalIncludeDirectories> <PreprocessorDefinitions>YOLODLL_EXPORTS;_TIMESPEC_DEFINED;_CRT_SECURE_NO_WARNINGS;GPU;WIN32;NDEBUG;_CONSOLE;_LIB;%(PreprocessorDefinitions)</PreprocessorDefinitions> <PreprocessorDefinitions>CUDNN;YOLODLL_EXPORTS;_TIMESPEC_DEFINED;_CRT_SECURE_NO_WARNINGS;GPU;WIN32;NDEBUG;_CONSOLE;_LIB;%(PreprocessorDefinitions)</PreprocessorDefinitions> <CLanguageStandard>c11</CLanguageStandard> <CppLanguageStandard>c++1y</CppLanguageStandard> <PrecompiledHeaderCompileAs>CompileAsCpp</PrecompiledHeaderCompileAs> src/cuda.c
@@ -96,6 +96,7 @@ int i = cuda_get_device(); if(!init[i]) { cublasCreate(&handle[i]); cublasStatus_t status = cublasSetStream(handle[i], get_cuda_stream()); init[i] = 1; } return handle[i]; src/yolo_console_dll.cpp
@@ -15,6 +15,7 @@ #endif #define TRACK_OPTFLOW #include "yolo_v2_class.hpp" // imported functions from DLL #ifdef OPENCV @@ -93,8 +94,8 @@ std::string filename; if (argc > 1) filename = argv[1]; Detector detector("cfg/yolo-voc.cfg", "yolo-voc.weights"); //Detector detector("tiny-yolo-voc_air.cfg", "backup/tiny-yolo-voc_air_5000.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"; @@ -131,7 +132,7 @@ int current_det_fps = 0, current_cap_fps = 0; std::thread t_detect, t_cap, t_videowrite; std::mutex mtx; std::condition_variable cv; 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); @@ -153,35 +154,31 @@ // 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; 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 #ifdef TRACK_OPTFLOW // 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; tracker_flow.update_tracking_flow(track_optflow_queue.front()); // 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; tracker_flow.update_tracking_flow(track_optflow_queue.front()); while (track_optflow_queue.size() > 1) { track_optflow_queue.pop(); while (track_optflow_queue.size() > 0) { 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; track_optflow_queue.pop(); } track_optflow_queue = new_track_optflow_queue; new_track_optflow_queue.swap(std::queue<cv::Mat>()); passed_flow_frames = 0; 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; } track_optflow_queue = new_track_optflow_queue; new_track_optflow_queue.swap(std::queue<cv::Mat>()); passed_flow_frames = 0; } #endif consumed = false; cv_pre_tracked.notify_all(); } // launch thread once - Detection if (!t_detect.joinable()) { @@ -189,6 +186,7 @@ auto current_image = det_image; consumed = true; while (current_image.use_count() > 0) { //std::vector<bbox_t> result; auto result = detector.detect_resized(*current_image, frame_size, 0.24, false); // true //Sleep(200); Sleep(50); @@ -197,7 +195,8 @@ thread_result_vec = result; current_image = det_image; consumed = true; cv.notify_all(); cv_detected.notify_all(); while (consumed) cv_pre_tracked.wait(lock); } }); } @@ -234,7 +233,7 @@ // 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); // while (!consumed) cv_detected.wait(lock); //} } if (t_cap.joinable()) t_cap.join(); src/yolo_v2_class.hpp
@@ -89,12 +89,15 @@ 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::cout << "\n img_rgb: " << img_rgb.size() << ", " << img_rgb.type() << ", " << img_rgb.channels() << std::endl; //std::cout << "\n img: " << img.size() << ", " << img.type() << ", " << img.channels() << std::endl; 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; } @@ -108,15 +111,23 @@ 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.; //std::vector<unsigned char> tmp(w*h*c); 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.; //tmp[count++] = data[i_step + j*c + k]; } } } //cv::Mat wrapped_8bit(cv::Size(w, h), CV_8UC3, tmp.data()); //cv::Mat wrapped_32float(cv::Size(w, h), CV_32FC3, out.data); //wrapped_8bit.convertTo(wrapped_32float, CV_32FC3, 1 / 255.); return out; } @@ -137,16 +148,6 @@ 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 }; @@ -156,22 +157,23 @@ class Tracker_optflow { public: int gpu_id; const int gpu_count; const int gpu_id; Tracker_optflow(int _gpu_id = 0) : gpu_id(_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(); static const int gpu_count = cv::cuda::getCudaEnabledDeviceCount(); if (gpu_count > gpu_id) cv::cuda::setDevice(gpu_id); cv::cuda::setDevice(gpu_id); stream = cv::cuda::Stream(); 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)); // 15, 21, 31 sync_PyrLKOpticalFlow_gpu->setMaxLevel(5); // +- 50 ptx sync_PyrLKOpticalFlow_gpu->setNumIters(2000); // def: 30 sync_PyrLKOpticalFlow_gpu->setWinSize(cv::Size(21, 21)); sync_PyrLKOpticalFlow_gpu->setMaxLevel(50); //sync_PyrLKOpticalFlow_gpu.maxLevel = 8; // +-32 points // def: 3 sync_PyrLKOpticalFlow_gpu->setNumIters(6000); //sync_PyrLKOpticalFlow_gpu.iters = 8000; // def: 30 cv::cuda::setDevice(old_gpu_id); } // just to avoid extra allocations @@ -183,15 +185,14 @@ 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 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::setDevice(gpu_id); cv::cuda::Stream stream; //cv::cuda::Stream stream; if (src_mat.channels() == 3) { if (src_mat_gpu.cols == 0) { @@ -214,11 +215,9 @@ } 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::setDevice(gpu_id); cv::cuda::Stream stream; //cv::cuda::Stream stream; if (dst_mat_gpu.cols == 0) { dst_mat_gpu = cv::cuda::GpuMat(dst_mat.size(), dst_mat.type());
