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Code Issues Releases Wiki Activity

Tracking and Streaming fixed.

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pull/355/head
AlexeyAB 7 years ago
parent e205c1e7ae
commit 0419c54042
5 changed files with 63 additions and 63 deletions
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  1. 1
      build/darknet/yolo_console_dll.vcxproj
  2. 2
      build/darknet/yolo_cpp_dll.vcxproj
  3. 1
      src/cuda.c
  4. 53
      src/yolo_console_dll.cpp
  5. 69
      src/yolo_v2_class.hpp

1
build/darknet/yolo_console_dll.vcxproj
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@ -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>

2
build/darknet/yolo_cpp_dll.vcxproj
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@ -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>

1
src/cuda.c
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@ -96,6 +96,7 @@ cublasHandle_t blas_handle()
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];

53
src/yolo_console_dll.cpp
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@ -15,6 +15,7 @@
#endif
#define TRACK_OPTFLOW
#include "yolo_v2_class.hpp" // imported functions from DLL
#ifdef OPENCV
@ -93,8 +94,8 @@ int main(int argc, char *argv[])
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 main(int argc, char *argv[])
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 @@ int main(int argc, char *argv[])
// 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 @@ int main(int argc, char *argv[])
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 @@ int main(int argc, char *argv[])
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 @@ int main(int argc, char *argv[])
// 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();

69
src/yolo_v2_class.hpp
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@ -89,12 +89,15 @@ public:
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 @@ private:
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 @@ private:
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 @@ private:
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 @@ public:
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 @@ public:
}
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());

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