//
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// Created by Scheaven on 2019/11/18.
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//
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#include "lib/core/tracker_manager.h"
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#include <opencv2/opencv.hpp>
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#include "opencv2/core/core.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include "tensorflow/core/public/session.h"
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#include "tensorflow/core/protobuf/meta_graph.pb.h"
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#include "tensorflow/core/graph/default_device.h"
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#include "tensorflow/core/platform/env.h"
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#ifdef OPENCV
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#include <opencv2/opencv.hpp> // C++
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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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#endif // OPENCV
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using namespace std;
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std::vector<cv::Rect> boxes; //存储box
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int main(int argc, char *argv[])
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{
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//视频流信息
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VideoCapture cap;
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VideoCapture cap2;
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int cam_id = 1;
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int cam_id2 = 2;
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try {
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cap.open("../data/cs01.avi");
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cap2.open("../data/cs02.avi");
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}catch(exception){
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cout<<"输入视频"<<endl;
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return 0;
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}
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Mat frame, blob;
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Mat frame2, blob2;
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TrackerManager TM;
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TM.add_cam(cam_id);
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TM.add_cam(cam_id2);
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while (true) {
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std::vector<int> cam_ids;
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std::vector<cv::Mat> frame_vec;
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std::vector<FRAME_RESULT> results_vec;
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cam_ids.push_back(cam_id);
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cam_ids.push_back(cam_id2);
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//读取视频帧
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cap >> frame;
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cap2 >> frame2;
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frame_vec.push_back(frame);
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frame_vec.push_back(frame2);
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cout << "start--" << endl;
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if(!frame.empty()){
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FRAME_RESULT result;
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FRAME_RESULT result2;
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results_vec.push_back(result);
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results_vec.push_back(result2);
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// TM.single_detect_tracking(cam_id, frame, result);
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TM.mul_detect_tracking(cam_ids, frame_vec, results_vec);
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// cout<< "result: "<< result[0] << endl;
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}else{
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cout << "-----------------------over--" << endl;
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break;
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}
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// //计算效率
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// std::vector<double> layersTimes;
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// double freq = cv::getTickFrequency() / 1000;
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// double t = net.getPerfProfile(layersTimes) / freq;
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// std::string label = cv::format("Inference time for a frame : %.2f ms", t);
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// putText(frame, label, cv::Point(0, 15), cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 255));
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// waitKey(1);
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}
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return 0;
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}
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