#include <stdio.h>#include <string>#include <opencv2/imgproc/imgproc.hpp>#include <opencv2/core/core.hpp>
 
#include <opencv2/highgui/highgui.hpp>int main(){    // Open the video file    cv::VideoCapture capture("../stomp.avi");    // check if video successfully opened    if (!capture.isOpened())        return 1;    // Get the frame rate    double rate = capture.get(CV_CAP_PROP_FPS);    bool stop(false);    cv::Mat frame;  // current video frame
 
    cv::namedWindow("Extracted Frame");    // Delay between each frame in ms    // corresponds to video frame rate    int delay = 1000 / rate;    // for all frames in video    while (!stop){        // read next frame if any        if (!capture.read(frame))            break;        cv::imshow("Extracted Frame", frame);        // introduce a delay
 
        // or press key to stop        if (cv::waitKey(delay) >= 0)            stop = true;    }    // Close the video file    // Not required since called by destructor    capture.release();}

#include <iostream>#include <iomanip>#include <sstream>#include <string>#include <vector>#include <dbg.h>#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>using namespace cv;using namespace std;int main(){    VideoCapture cap;    cap.open(0);    namedWindow("MyVideo", 1);    double dWidth = cap.get(CV_CAP_PROP_FRAME_WIDTH);    double dHeight = cap.get(CV_CAP_PROP_FRAME_HEIGHT);    Size frameSize(static_cast<int>(dWidth), static_cast<int>(dHeight));    VideoWriter oVideoWriter("MyVideo.avi", CV_FOURCC('P','I','M','1'), 20, frameSize, true);	// initialize the VideoWriter objetct    while (1) {        Mat frame;        bool bSuccess = cap.read(frame);        if (!bSuccess){ // if not success, break loop            cout << "ERROR: cannot read a frame from video file" << endl;            break;        }        oVideoWriter.write(frame);        imshow("MyVideo", frame); // show the frame in "MyVideo" window        if(waitKey(10) == 27) {// wait for ESC key            cout << "ESC key is pressed by user" << endl;            break;        }    }    return 0;}

int cv::meanShift(InputArray probImage, Rect& window, TermCriteria criteria)

// Computes the 1D Hue histogram with a mask.// BGR source image is converted to HSVcv::MatND getHueHistogram(const cv::Mat &image,                             int minSaturation = 0) {    cv::MatND hist;    // Convert to HSV color space    cv::Mat hsv;    cv::cvtColor(image, hsv, CV_BGR2HSV);       // Mask to be used (or not)       cv::Mat mask;       if (minSaturation > 0) {           // Spliting the 3 channels into 3 images           std::vector<cv::Mat> v;           cv::split(hsv, v);           // Mask out the low saturated pixels           cv::threshold(v[1], mask, minSaturation,                         255, cv::THRESH_BINARY);       }    // Prepare arguments for a 1D hue histogram    hranges[0]= 0.0;    hranges[1]= 180.0;    channels[0]= 0; // the hue channel       // Compute histogram    cv::calcHist(&hsv,         1,			// histogram of 1 image only        channels,	// the channel used        mask,	// no mask is used        hist,		// the resulting histogram        1,			// it is a 1D histogram        histSize,	// number of bins        ranges		// pixel value range    );    return hist;}

int main(){    // Read reference image    cv::Mat image= cv::imread("../baboon1.jpg");    if (!image.data)        return 0;     // Define ROI    cv::Mat imageROI= image(cv::Rect(110,260,35,40));    cv::rectangle(image, cv::Rect(110,260,35,40), cv::Scalar(0,0,255));    // Display image    cv::namedWindow("Image 1");    cv::imshow("Image 1",image);    // Get the Hue histogram    int minSat=65;    ColorHistogram hc;    cv::MatND colorhist= hc.getHueHistogram(imageROI, minSat);    ObjectFinder finder;    finder.setHistogram(colorhist);    finder.setThreshold(0.2f);    // Second image    image= cv::imread("../baboon3.jpg"); 	// Display image    cv::namedWindow("Image 2");    cv::imshow("Image 2",image);    // Convert to HSV space    cv::Mat hsv;    cv::cvtColor(image, hsv, CV_BGR2HSV);    // Split the image    vector<cv::Mat> v;    cv::split(hsv,v);    // Eliminate pixels with low saturation    cv::threshold(v[1],v[1],minSat,255,cv::THRESH_BINARY);    cv::namedWindow("Saturation");    cv::imshow("Saturation",v[1]);    // Get back-projection of hue histogram    int ch[1]={0};    cv::Mat result= finder.find(hsv,0.0f,180.0f,ch,1);    cv::namedWindow("Result Hue");    cv::imshow("Result Hue",result);    // Eliminate low stauration pixels    cv::bitwise_and(result,v[1],result);    cv::namedWindow("Result Hue and raw");    cv::imshow("Result Hue and raw",result);    cv::Rect rect(110,260,35,40);    cv::rectangle(image, rect, cv::Scalar(0,0,255));    cv::TermCriteria criteria(cv::TermCriteria::MAX_ITER,10,0.01);    cout << "meanshift= " << cv::meanShift(result,rect,criteria) << endl;    cv::rectangle(image, rect, cv::Scalar(0,255,0));    // Display image    cv::namedWindow("Image 2 result");    cv::imshow("Image 2 result",image);    cv::waitKey();    return 0;}

RotatedRect CamShift(InputArray probImage, Rect& window, TermCriteria criteria)

void cornerHarris(InputArray src,	// input                OutputArray dst,	// output                int blockSize,	// neighborhood size                int ksize,		// aperture size                double k,			// Harris parameter                int borderType=BORDER_DEFAULT )

// Detect Harris Cornerscv::Mat cornerStrength;cv::cornerHarris(image,cornerStrength,                3,	// neighborhood size                3,	// aperture size                0.01); // Harris parameter// threshold the corner strengthscv::Mat harrisCorners;double threshold= 0.0001;cv::threshold(cornerStrength,harrisCorners,            threshold,255,cv::THRESH_BINARY_INV);