mirror/darknet
1
0
Fork 0
mirror of https://github.com/pjreddie/darknet.git synced 2023-08-10 21:13:14 +03:00
Code Issues Projects Releases Wiki Activity

Added object tracking using optical flow

Browse Source
This commit is contained in:
AlexeyAB
2017-12-26 02:56:13 +03:00
parent ee87f4b649
commit 7113d2cc7f
3 changed files with 260 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
src/detector.c
View File

@ -399,7 +399,7 @@ void validate_detector_recall(char *datacfg, char *cfgfile, char *weightfile)
int m = plist->size;
int i=0;
float thresh = .2;// .001;
float thresh = .001;// .001; // .2;
float iou_thresh = .5;
float nms = .4;

108
src/yolo_console_dll.cpp
View File

@ -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 @@ 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("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 @@ int main(int argc, char *argv[])
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 @@ int main(int argc, char *argv[])
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 @@ int main(int argc, char *argv[])
}
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;
{
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;
}
#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
// 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 @@ int main(int argc, char *argv[])
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 @@ 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);
}
//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();

166
src/yolo_v2_class.hpp
View File

@ -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 @@ struct image_t {
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 @@ public:
}
private:
static image_t ipl_to_image(IplImage* src)
{
unsigned char *data = (unsigned char *)src->imageData;
@ -142,8 +149,165 @@ private:
#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)