AlexeyAB
2017-12-25 7113d2cc7fceb0fb599326aec65771c33f5f4386
Added object tracking using optical flow
3 files modified
276 ■■■■■ changed files
src/detector.c 2 ●●● patch | view | raw | blame | history
src/yolo_console_dll.cpp 108 ●●●● patch | view | raw | blame | history
src/yolo_v2_class.hpp 166 ●●●●● 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;
src/yolo_console_dll.cpp
@@ -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;
                        {
                            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 @@
                            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)