OpenCV视频入门操作，打开指定视频以及本地摄像头（C++）库函数图像识别追踪——VS2017-OpenCV4.0.1

OpenCV的安装与实现VS环境设置，VS2017与OpenCV4.1.0的文件选择

https://blog.csdn.net/cfl997/article/details/92829765

视频：

VideoCapture capture(0);

参数为0；默认打开本地摄像头；

换成地址即可。

用一个while函数取读取每一帧，再显示。也就是不断地显示很多张图片。

#include
using namespace cv;

int main() {
	VideoCapture capture(0);
	Mat edges;
	while (1) {
		Mat frame;
		capture >> frame;
		imshow("读取视频", frame);
		if (waitKey(30) >= 0)break;
	}
	return 0;
}

对于视频的处理。

既然都是每一帧图像，自然就是对图像的处理。

我们测试一个边缘化：

#include
using namespace cv;

int main() {
	VideoCapture capture(0);
	Mat edges;
	while (1) {
		Mat frame;
		capture >> frame;
		cvtColor(frame, edges, COLOR_BGR2GRAY);
		blur(edges, edges, Size(7, 7));
		Canny(edges, edges, 3,9,3);
		imshow("读取视频", edges);
		if (waitKey(30) >= 0)break;
	}
	return 0;
}

效果图：

边缘处理可以自然灰度处理，模糊等操作也是可以的。

 

这里库函数里有个写好的操作可以追踪选择的图像

在摄像头的视频中选取要识别的颜色范围。便可以跟踪图像：

代码如下：

#include 
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"

#include 
#include 

using namespace cv;
using namespace std;

Mat image;

bool backprojMode = false;
bool selectObject = false;
int trackObject = 0;
bool showHist = true;
Point origin;
Rect selection;
int vmin = 10, vmax = 256, smin = 30;

// User draws box around object to track. This triggers CAMShift to start tracking
static void onMouse( int event, int x, int y, int, void* )
{
    if( selectObject )
    {
        selection.x = MIN(x, origin.x);
        selection.y = MIN(y, origin.y);
        selection.width = std::abs(x - origin.x);
        selection.height = std::abs(y - origin.y);

        selection &= Rect(0, 0, image.cols, image.rows);
    }

    switch( event )
    {
    case EVENT_LBUTTONDOWN:
        origin = Point(x,y);
        selection = Rect(x,y,0,0);
        selectObject = true;
        break;
    case EVENT_LBUTTONUP:
        selectObject = false;
        if( selection.width > 0 && selection.height > 0 )
            trackObject = -1;   // Set up CAMShift properties in main() loop
        break;
    }
}

string hot_keys =
    "\n\nHot keys: \n"
    "\tESC - quit the program\n"
    "\tc - stop the tracking\n"
    "\tb - switch to/from backprojection view\n"
    "\th - show/hide object histogram\n"
    "\tp - pause video\n"
    "To initialize tracking, select the object with mouse\n";

static void help()
{
    cout << "\nThis is a demo that shows mean-shift based tracking\n"
            "You select a color objects such as your face and it tracks it.\n"
            "This reads from video camera (0 by default, or the camera number the user enters\n"
            "Usage: \n"
            "   ./camshiftdemo [camera number]\n";
    cout << hot_keys;
}

const char* keys =
{
    "{help h | | show help message}{@camera_number| 0 | camera number}"
};

int main( int argc, const char** argv )
{
    VideoCapture cap;
    Rect trackWindow;
    int hsize = 16;
    float hranges[] = {0,180};
    const float* phranges = hranges;
    CommandLineParser parser(argc, argv, keys);
    if (parser.has("help"))
    {
        help();
        return 0;
    }
    int camNum = parser.get(0);
    cap.open(camNum);

    if( !cap.isOpened() )
    {
        help();
        cout << "***Could not initialize capturing...***\n";
        cout << "Current parameter's value: \n";
        parser.printMessage();
        return -1;
    }
    cout << hot_keys;
    namedWindow( "Histogram", 0 );
    namedWindow( "CamShift Demo", 0 );
    setMouseCallback( "CamShift Demo", onMouse, 0 );
    createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );
    createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );
    createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );

    Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
    bool paused = false;

    for(;;)
    {
        if( !paused )
        {
            cap >> frame;
            if( frame.empty() )
                break;
        }

        frame.copyTo(image);

        if( !paused )
        {
            cvtColor(image, hsv, COLOR_BGR2HSV);

            if( trackObject )
            {
                int _vmin = vmin, _vmax = vmax;

                inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),
                        Scalar(180, 256, MAX(_vmin, _vmax)), mask);
                int ch[] = {0, 0};
                hue.create(hsv.size(), hsv.depth());
                mixChannels(&hsv, 1, &hue, 1, ch, 1);

                if( trackObject < 0 )
                {
                    // Object has been selected by user, set up CAMShift search properties once
                    Mat roi(hue, selection), maskroi(mask, selection);
                    calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
                    normalize(hist, hist, 0, 255, NORM_MINMAX);

                    trackWindow = selection;
                    trackObject = 1; // Don't set up again, unless user selects new ROI

                    histimg = Scalar::all(0);
                    int binW = histimg.cols / hsize;
                    Mat buf(1, hsize, CV_8UC3);
                    for( int i = 0; i < hsize; i++ )
                        buf.at(i) = Vec3b(saturate_cast(i*180./hsize), 255, 255);
                    cvtColor(buf, buf, COLOR_HSV2BGR);

                    for( int i = 0; i < hsize; i++ )
                    {
                        int val = saturate_cast(hist.at(i)*histimg.rows/255);
                        rectangle( histimg, Point(i*binW,histimg.rows),
                                   Point((i+1)*binW,histimg.rows - val),
                                   Scalar(buf.at(i)), -1, 8 );
                    }
                }

                // Perform CAMShift
                calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
                backproj &= mask;
                RotatedRect trackBox = CamShift(backproj, trackWindow,
                                    TermCriteria( TermCriteria::EPS | TermCriteria::COUNT, 10, 1 ));
                if( trackWindow.area() <= 1 )
                {
                    int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;
                    trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,
                                       trackWindow.x + r, trackWindow.y + r) &
                                  Rect(0, 0, cols, rows);
                }

                if( backprojMode )
                    cvtColor( backproj, image, COLOR_GRAY2BGR );
                ellipse( image, trackBox, Scalar(0,0,255), 3, LINE_AA );
            }
        }
        else if( trackObject < 0 )
            paused = false;

        if( selectObject && selection.width > 0 && selection.height > 0 )
        {
            Mat roi(image, selection);
            bitwise_not(roi, roi);
        }

        imshow( "CamShift Demo", image );
        imshow( "Histogram", histimg );

        char c = (char)waitKey(10);
        if( c == 27 )
            break;
        switch(c)
        {
        case 'b':
            backprojMode = !backprojMode;
            break;
        case 'c':
            trackObject = 0;
            histimg = Scalar::all(0);
            break;
        case 'h':
            showHist = !showHist;
            if( !showHist )
                destroyWindow( "Histogram" );
            else
                namedWindow( "Histogram", 1 );
            break;
        case 'p':
            paused = !paused;
            break;
        default:
            ;
        }
    }

    return 0;
}