xavier
110 lines
3.2 KiB
C++
110 lines
3.2 KiB
C++
#include <iostream>
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#include <signal.h>
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#include <stdlib.h> /* srand, rand */
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#include <unistd.h>
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#include <mutex>
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#include "utils.h"
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#include <opencv2/core/core.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <opencv2/videoio.hpp>
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#include <opencv2/imgproc/imgproc.hpp>
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#include "Yolo3Detection.h"
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bool gRun;
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bool SAVE_RESULT = false;
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void sig_handler(int signo) {
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std::cout<<"request gateway stop\n";
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gRun = false;
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}
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int main(int argc, char *argv[]) {
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std::cout<<"detection\n";
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signal(SIGINT, sig_handler);
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char *net = "yolo3_berkeley.rt";
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if(argc > 1)
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net = argv[1];
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char *input = "../demo/yolo_test.mp4";
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if(argc > 2)
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input = argv[2];
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tk::dnn::Yolo3Detection yolo;
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yolo.init(net);
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gRun = true;
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cv::VideoCapture cap(input);
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if(!cap.isOpened())
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gRun = false;
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else
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std::cout<<"camera started\n";
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cv::VideoWriter resultVideo;
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if(SAVE_RESULT) {
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int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
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int h = cap.get(cv::CAP_PROP_FRAME_HEIGHT);
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resultVideo.open("result.mp4", cv::VideoWriter::fourcc('M','P','4','V'), 30, cv::Size(w, h));
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}
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cv::Mat frame;
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cv::Mat dnn_input;
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cv::namedWindow("detection", cv::WINDOW_NORMAL);
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while(gRun) {
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cap >> frame;
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if(!frame.data) {
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break;
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}
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// this will be resized to the net format
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dnn_input = frame.clone();
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// TODO: async infer
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yolo.update(dnn_input);
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// draw dets
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for(int i=0; i<yolo.detected.size(); i++) {
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tk::dnn::box b = yolo.detected[i];
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int x0 = b.x;
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int x1 = b.x + b.w;
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int y0 = b.y;
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int y1 = b.y + b.h;
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std::string det_class = yolo.getYoloLayer()->classesNames[b.cl];
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float prob = b.prob;
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std::cout<<det_class<<" ("<<prob<<"): "<<x0<<" "<<y0<<" "<<x1<<" "<<y1<<"\n";
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// draw rectangle
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cv::rectangle(frame, cv::Point(x0, y0), cv::Point(x1, y1), yolo.colors[b.cl], 2);
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// draw label
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int baseline = 0;
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float fontScale = 0.5;
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int thickness = 2;
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cv::Size textSize = getTextSize(det_class, cv::FONT_HERSHEY_SIMPLEX, fontScale, thickness, &baseline);
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cv::rectangle(frame, cv::Point(x0, y0), cv::Point((x0 + textSize.width - 2), (y0 - textSize.height - 2)), yolo.colors[b.cl], -1);
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cv::putText(frame, det_class, cv::Point(x0, (y0 - (baseline / 2))), cv::FONT_HERSHEY_SIMPLEX, fontScale, cv::Scalar(255, 255, 255), thickness);
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}
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cv::imshow("detection", frame);
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cv::waitKey(1);
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if(SAVE_RESULT)
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resultVideo << frame;
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}
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std::cout<<"detection end\n";
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std::cout<<COL_GREENB<<"\n\nTime stats:\n";
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std::cout<<"Min: "<<*std::min_element(yolo.stats.begin(), yolo.stats.end())<<" ms\n";
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std::cout<<"Max: "<<*std::max_element(yolo.stats.begin(), yolo.stats.end())<<" ms\n";
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double mean = 0; for(int i=0; i<yolo.stats.size(); i++) mean += yolo.stats[i]; mean /= yolo.stats.size();
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std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;
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return 0;
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}
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