mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
Added tracking: numerating the detected objects on video
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@ -1,9 +1,10 @@
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#include <iostream>
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#include <iomanip>
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#include <string>
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#include <vector>
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#include <fstream>
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//#define OPENCV
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#define OPENCV
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#include "yolo_v2_class.hpp" // imported functions from DLL
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@ -13,21 +14,27 @@
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#pragma comment(lib, "opencv_core249.lib")
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#pragma comment(lib, "opencv_imgproc249.lib")
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#pragma comment(lib, "opencv_highgui249.lib")
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void draw_boxes(cv::Mat mat_img, std::vector<bbox_t> result_vec) {
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void draw_boxes(cv::Mat mat_img, std::vector<bbox_t> result_vec, std::vector<std::string> obj_names, unsigned int wait_msec = 0) {
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for (auto &i : result_vec) {
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cv::rectangle(mat_img, cv::Rect(i.x, i.y, i.w, i.h), cv::Scalar(50, 200, 50), 3);
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cv::Scalar color(60, 160, 260);
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cv::rectangle(mat_img, cv::Rect(i.x, i.y, i.w, i.h), color, 3);
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if(obj_names.size() > i.obj_id)
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putText(mat_img, obj_names[i.obj_id], cv::Point2f(i.x, i.y - 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 1, color);
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if(i.track_id > 0)
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putText(mat_img, std::to_string(i.track_id), cv::Point2f(i.x+5, i.y + 15), cv::FONT_HERSHEY_COMPLEX_SMALL, 1, color);
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}
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cv::imshow("window name", mat_img);
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cv::waitKey(0);
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cv::waitKey(wait_msec);
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}
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#endif // OPENCV
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void show_result(std::vector<bbox_t> const result_vec, std::vector<std::string> const obj_names) {
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for (auto &i : result_vec) {
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if (obj_names.size() > i.obj_id) std::cout << obj_names[i.obj_id] << " - ";
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std::cout << "obj_id = " << i.obj_id << " - x = " << i.x << ", y = " << i.y
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std::cout << "obj_id = " << i.obj_id << ", x = " << i.x << ", y = " << i.y
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<< ", w = " << i.w << ", h = " << i.h
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<< ", prob = " << i.prob << std::endl;
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<< std::setprecision(3) << ", prob = " << i.prob << std::endl;
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}
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}
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@ -50,23 +57,38 @@ int main()
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while (true)
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{
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std::string filename;
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std::cout << "input image filename: ";
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std::cout << "input image or video filename: ";
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std::cin >> filename;
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if (filename.size() == 0) break;
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try {
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#ifdef OPENCV
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std::string const file_ext = filename.substr(filename.find_last_of(".") + 1);
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if (file_ext == "avi" || file_ext == "mp4" || file_ext == "mjpg" || file_ext == "mov") { // video file
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cv::Mat frame;
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detector.nms = 0.02; // comment it - if track_id is not required
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for(cv::VideoCapture cap(filename); cap >> frame, cap.isOpened();) {
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std::vector<bbox_t> result_vec = detector.detect(frame, 0.2);
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result_vec = detector.tracking(result_vec); // comment it - if track_id is not required
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draw_boxes(frame, result_vec, obj_names, 3);
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show_result(result_vec, obj_names);
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}
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}
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else { // image file
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cv::Mat mat_img = cv::imread(filename);
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std::vector<bbox_t> result_vec = detector.detect(mat_img);
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draw_boxes(mat_img, result_vec);
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draw_boxes(mat_img, result_vec, obj_names);
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show_result(result_vec, obj_names);
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}
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#else
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//std::vector<bbox_t> result_vec = detector.detect(filename);
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auto img = detector.load_image(filename);
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std::vector<bbox_t> result_vec = detector.detect(img);
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detector.free_image(img);
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#endif
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show_result(result_vec, obj_names);
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#endif
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}
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catch (std::exception &e) { std::cerr << "exception: " << e.what() << "\n"; getchar(); }
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catch (...) { std::cerr << "unknown exception \n"; getchar(); }
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@ -154,7 +154,7 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh)
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cudaSetDevice(net.gpu_index);
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//std::cout << "net.gpu_index = " << net.gpu_index << std::endl;
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float nms = .4;
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//float nms = .4;
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image im;
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im.c = img.c;
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@ -189,6 +189,7 @@ YOLODLL_API std::vector<bbox_t> Detector::detect(image_t img, float thresh)
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bbox.h = b.h*im.h;
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bbox.obj_id = obj_id;
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bbox.prob = prob;
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bbox.track_id = 0;
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bbox_vec.push_back(bbox);
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}
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@ -1,6 +1,8 @@
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#pragma once
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#include <memory>
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#include <vector>
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#include <deque>
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#include <algorithm>
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#ifdef OPENCV
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#include <opencv2/opencv.hpp> // C++
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@ -18,6 +20,7 @@ struct bbox_t {
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unsigned int x, y, w, h; // (x,y) - top-left corner, (w, h) - width & height of bounded box
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float prob; // confidence - probability that the object was found correctly
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unsigned int obj_id; // class of object - from range [0, classes-1]
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unsigned int track_id; // tracking id for video (0 - untracked, 1 - inf - tracked object)
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};
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struct image_t {
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@ -31,6 +34,7 @@ struct image_t {
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class Detector {
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std::shared_ptr<void> detector_gpu_ptr;
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public:
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float nms = .4;
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YOLODLL_API Detector(std::string cfg_filename, std::string weight_filename, int gpu_id = 0);
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YOLODLL_API ~Detector();
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@ -107,6 +111,59 @@ private:
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}
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#endif // OPENCV
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std::deque<std::vector<bbox_t>> prev_bbox_vec_deque;
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public:
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std::vector<bbox_t> tracking(std::vector<bbox_t> cur_bbox_vec, int const frames_story = 4)
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{
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bool prev_track_id_present = false;
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for (auto &i : prev_bbox_vec_deque)
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if (i.size() > 0) prev_track_id_present = true;
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static unsigned int track_id = 1;
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if(!prev_track_id_present) {
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//track_id = 1;
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for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
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cur_bbox_vec[i].track_id = track_id++;
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prev_bbox_vec_deque.push_front(cur_bbox_vec);
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if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back();
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return cur_bbox_vec;
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}
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std::vector<unsigned int> dist_vec(cur_bbox_vec.size(), std::numeric_limits<unsigned int>::max());
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for (auto &prev_bbox_vec : prev_bbox_vec_deque) {
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for (auto &i : prev_bbox_vec) {
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int cur_index = -1;
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for (size_t m = 0; m < cur_bbox_vec.size(); ++m) {
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bbox_t const& k = cur_bbox_vec[m];
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if (i.obj_id == k.obj_id) {
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unsigned int cur_dist = sqrt(((float)i.x - k.x)*((float)i.x - k.x) + ((float)i.y - k.y)*((float)i.y - k.y));
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if (cur_dist < 100 && (k.track_id == 0 || dist_vec[m] > cur_dist)) {
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dist_vec[m] = cur_dist;
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cur_index = m;
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}
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}
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}
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bool track_id_absent = !std::any_of(cur_bbox_vec.begin(), cur_bbox_vec.end(), [&](bbox_t const& b) { return b.track_id == i.track_id; });
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if (cur_index >= 0 && track_id_absent)
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cur_bbox_vec[cur_index].track_id = i.track_id;
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}
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}
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for (size_t i = 0; i < cur_bbox_vec.size(); ++i)
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if (cur_bbox_vec[i].track_id == 0)
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cur_bbox_vec[i].track_id = track_id++;
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prev_bbox_vec_deque.push_front(cur_bbox_vec);
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if (prev_bbox_vec_deque.size() > frames_story) prev_bbox_vec_deque.pop_back();
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return cur_bbox_vec;
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}
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};
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