程式碼如下

#include <iostream>
#include <opencv2/opencv.hpp>
#include <string>
using namespace std;
using namespace cv;

CascadeClassifier car_classifier;
string cascade_name = "car.xml";
void detect_and_display(Mat car,string video_windows_name);//////檢測和顯示函式

int main()
{
    VideoCapture cap;
    cap.open("car.avi"
 
);
    if(!cap.isOpened())
    {
        cout<<"the video is not opened......."<<endl;
        return -1;
    }
    if(!car_classifier.load(cascade_name.c_str()))
    {
        cout<<"分類器匯入失敗"<<endl;
        return -1;
    }
    while(1)
    {
        Mat frame;
        cap>>frame;
        //imshow("frame",frame);
 

        //waitKey(33);
        if(frame.data)
            detect_and_display(frame,"detect_and_display");
    }
    return 0;
}

void detect_and_display(Mat car,string video_windows_name)
{

    std::vector<Rect> cars;
    Mat car_gray, small_img;
    double scale = 1.3;
    Point pt11, pt22;
    cvtColor(car, car_gray, CV_BGR2GRAY);  //rgb型別轉換為灰度型別  
 

    resize(car_gray, small_img, Size(cvRound(car_gray.cols / scale), cvRound(car_gray.rows / scale)), 0, 0, CV_INTER_LINEAR);
    equalizeHist(small_img, small_img);   //直方圖均衡化  
    car_classifier.detectMultiScale(small_img,
        cars,
        1.1,
        3,
        CV_HAAR_DO_CANNY_PRUNING,
        Size(20, 20));
    for (int i = 0; i < cars.size(); i++)
    {
        Point pt11,pt22;
        pt11.x = cars[i].x*scale;
        pt22.x = (cars[i].x + cars[i].width)*scale;
        pt11.y = cars[i].y*scale;
        pt22.y = (cars[i].y + cars[i].height)*scale;
        rectangle(car, pt11, pt22, CV_RGB(255, 255, 0), 2, 8, 0);
    }
    imshow(video_windows_name,car);
    waitKey(33);
}