#include <stdio.h>
#include <opencv2/opencv.hpp>
#include <opencv2/dnn.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <opencv2/core/ocl.hpp>
#include <iostream>
using namespace cv;
using namespace std;
const size_t width = 500;
const size_t height = 120;
size_t det_index;
const float scaleFector = 0.007843f;
const float meanVal = 127.5;
dnn::Net net;
const char* class_video_Names[] = { "background",
"yiwu"};
Mat detect_from_video(Mat &src,float &x1,float &y1,float &x2,float &y2,size_t &det_index)
{
Mat blobimg = dnn::blobFromImage(src, scaleFector, Size(width, height), Scalar(127.5, 127.5, 127.5));
net.setInput(blobimg, "data");
Mat detection = net.forward("detection_out");
//cout << detection.size[2]<<" "<< detection.size[3] << endl;
Mat detectionMat(detection.size[2], detection.size[3], CV_32F, detection.ptr<float>());
const float confidence_threshold = 0.75;
for(int i=0; i<detectionMat.rows; i++){
float detect_confidence = detectionMat.at<float>(i, 2);
if(detect_confidence > confidence_threshold){
det_index = (size_t)detectionMat.at<float>(i, 1);
x1 = detectionMat.at<float>(i, 3)*src.cols;
y1 = detectionMat.at<float>(i, 4)*src.rows;
x2 = detectionMat.at<float>(i, 5)*src.cols;
y2 = detectionMat.at<float>(i, 6)*src.rows;
}
}
return src;
}
Mat changeImgLeft(Mat img1,Mat dst)
{
Mat roi;
cout<<img1.rows<<img1.cols<<endl;
roi = Mat::zeros(img1.size(),CV_8U);
imshow("roi", roi);
vector<vector<Point>> contour_left;
vector<Point> pts_left;
pts_left.push_back(Point(640, 281));
pts_left.push_back(Point(246, 257));
pts_left.push_back(Point(244, 247));
pts_left.push_back(Point(97, 237));
pts_left.push_back(Point(83, 168));
pts_left.push_back(Point(640, 160));
contour_left.push_back(pts_left);
drawContours(roi,contour_left,0,Scalar::all(255),-1);
imshow("roi_d", roi);
img1.copyTo(dst,roi);
imshow("dst", dst);
return dst;
}
int main(int argc,char ** argv)
{
float f,x1=0.0,y1=0.0,x2=0.0,y2=0.0;
float FPS[16];
int i, Fcnt=0;
int count =0;
VideoWriter vw1;
Size dsize = Size(300, 300);
Mat img2 = Mat(dsize, CV_32S);
Mat frame,CloseimgROI,CloseImgLeft;
chrono::steady_clock::time_point Tbegin, Tend;
net = dnn::readNetFromTorch("csv_retinanet_5.pt");
if (net.empty()){
cout << "init the model net error";
exit(-1);
}
VideoCapture capture;
frame= capture.open("./2021-01-06-14-22-02-L.mp4");
if(!capture.isOpened())
{
printf("can not open ...\n");
return -1;
}
vw1.open("save.mp4", VideoWriter::fourcc('m', 'p', '4', 'v'), 16, Size(640, 480));
if (!vw1.isOpened())
{
cout << "open vw1 faild" << endl;
return -1;
}
//cout << "Switched to " << (cv::ocl::useOpenCL() ? "OpenCL enabled" : "CPU") << endl;
//net.setPreferableTarget(DNN_TARGET_OPENCL);
cout << "Start grabbing, press ESC on Live window to terminate" << endl;
while(capture.read(frame)){
//frame=imread("2.jpg"); //need to refresh frame before dnn class detection
CloseimgROI = changeImgLeft(frame, CloseimgROI);
CloseImgLeft = CloseimgROI(Range(168, 289), cv::Range(83, 640));//将核心区域裁剪为矩形
count++;
Tbegin = chrono::steady_clock::now();
detect_from_video(CloseImgLeft,x1,y1,x2,y2,det_index);
Tend = chrono::steady_clock::now();
//calculate CloseImgLeft rate
f = chrono::duration_cast <chrono::milliseconds> (Tend - Tbegin).count();
if(f>0.0) FPS[((Fcnt++)&0x0F)]=1000.0/f;
for(f=0.0, i=0;i<16;i++){ f+=FPS[i]; }
putText(frame, format("FPS %0.2f", f/16),Point(10,20),FONT_HERSHEY_SIMPLEX,0.6, Scalar(0, 0, 255));
//show output
imshow("CloseImgLeft", CloseImgLeft);
Rect rec((int)x1+112, (int)y1+205, (int)(x2 - x1), (int)(y2 - y1));
rectangle(frame,rec, Scalar(0, 0, 255), 2, 8, 0);
putText(frame, format("%s", class_video_Names[det_index]), Point(x1+112, y1-5+205) ,FONT_HERSHEY_SIMPLEX,1.0, Scalar(0, 0, 255), 2, 8, 0);
resize(CloseImgLeft, img2, dsize);
imshow("frame", frame);
if(count==1550 )
{
//vw1 << frame;
cv::imwrite("save.jpg", frame);
}
x1=0.0;
y1=0.0;
x2=0.0;
y2=0.0;
det_index = 0.0;
char esc = waitKey(5);
if(esc == 27) break;
}
vw1.release();
cout << "Closing the camera" << endl;
destroyAllWindows();
cout << "Bye!" << endl;
return 0;
}
