up new v4

Scheaven

2021-06-03 168af40fe9a3cc81c6ee16b3e81f154780c36bdb

 main.cpp

@@ -1,14 +1,11 @@
//

// Created by Scheaven on 2019/11/18.

//

#include "lib/core/tracker_manager.h"

#include <opencv2/opencv.hpp>

#include "opencv2/core/core.hpp"

#include "opencv2/highgui/highgui.hpp"

#include "tensorflow/core/public/session.h"

#include "tensorflow/core/protobuf/meta_graph.pb.h"

#include "tensorflow/core/graph/default_device.h"

#include "tensorflow/core/platform/env.h"

#include "h_interface.h"

#include "std_target.h"

#include "time.h"





#ifdef OPENCV

#include <opencv2/opencv.hpp>         // C++

#pragma comment(lib, "opencv_core249.lib")

@@ -17,62 +14,80 @@


#endif   // OPENCV

using namespace std;

std::vector<cv::Rect> boxes; //存储box



using namespace cv;

void* handle;



int main(int argc, char *argv[])

{

    //视频流信息

//    //视频流信息

    VideoCapture cap;

    VideoCapture cap2;

    int cam_id = 1;

    int cam_id2 = 2;

    int cam_id = 0;

    int cam_id2 = 1;



    try {

        cap.open("../data/cs01.avi");

        cap2.open("../data/cs02.avi");

    }catch(exception){

        cout<<"输入视频"<<endl;

        return 0;

    }

    Mat frame, blob;

    Mat frame2, blob2;



    const char *conf = "../config.json";

    int *max_chan;

    int x = 5;

    max_chan=&x;

    handle = create(conf, max_chan);



    TrackerManager TM;

    TM.add_cam(cam_id);

    TM.add_cam(cam_id2);

    while (true) {

        std::vector<int> cam_ids;

        std::vector<cv::Mat> frame_vec;

        std::vector<FRAME_RESULT> results_vec;

        cam_ids.push_back(cam_id);

        cam_ids.push_back(cam_id2);

        //读取视频帧

    void *sr;

    void *sr2;

    TImage *img = new TImage();

    TImage *img2 = new TImage();

    int i = 0;

    cap = VideoCapture("/data/disk2/01_dataset/03_human/34983128.mp4");



    // string path="/data/disk1/workspace/07_CPP/build/re";

    // std::vector<string> video_path_vec;



    // globFile(path, video_path_vec, "jpg");



    // for (auto& file:video_path_vec)

    // {

    while(1){        /* code */

        // printf("----start--%s\n", file);

        // cout<<"----------------\n\n"<<file<<endl;

        // frame = imread(file);

        cap >> frame;

        cap2 >> frame2;

        frame_vec.push_back(frame);

        frame_vec.push_back(frame2);

        cout << "start--" << endl;

        if(!frame.empty()){

            FRAME_RESULT result;

            FRAME_RESULT result2;

            results_vec.push_back(result);

            results_vec.push_back(result2);

//            TM.single_detect_tracking(cam_id, frame, result);

            TM.mul_detect_tracking(cam_ids, frame_vec, results_vec);

//            cout<< "result: "<< result[0] << endl;

        // frame = imread("/data/disk1/project/data/04_human/error/4.png");

        clock_t t_strat2 = clock();

        if(!frame.empty())

        {

            img->width = frame.cols;

            img->height = frame.rows;

            img->channel = frame.channels();

            img->data = frame.data;

            sr = get_result(handle, img, 0);



            TResult * t_result = (TResult*) sr;



            cout << "=======t_result->count==" << t_result->count  << endl;

            for (int i=0; i<t_result->count; i++)

                cout << "====1111111111===confidence:" << t_result->targets[i].confidence << endl;



            // if (t_result->count>0)

            // {

            //    imwrite("/data/disk2/01_dataset/03_human/02_person/positive/"+file.substr(file.find_last_of("/")), frame);

            // }else

            // {

            //     imwrite("/data/disk2/01_dataset/03_human/02_person/negate/"+file.substr(file.find_last_of("/")), frame);

            // }





        }else{

            cout << "-----------------------over--" << endl;

            release(handle);

            release_result(sr);

            break;

        }

//        //计算效率

//        std::vector<double> layersTimes;

//        double freq = cv::getTickFrequency() / 1000;

//        double t = net.getPerfProfile(layersTimes) / freq;

//        std::string label = cv::format("Inference time for a frame : %.2f ms", t);

//        putText(frame, label, cv::Point(0, 15), cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 255));

//        waitKey(1);



        clock_t t_strat3 = clock();

        cout << "rps---"<< CLOCKS_PER_SEC/(t_strat3 - t_strat2)  <<endl;

    }

    return 0;

}