OpenCV2.4版本的camshiftdemo.cpp的详细注释

来源：互联网发布：程序员客栈专职编辑：程序博客网时间：2024/05/22 13:25
要我怎么感谢这位仁兄。。。
#include "opencv2/video/tracking.hpp"#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/highgui/highgui.hpp"#include <iostream>#include <ctype.h>using namespace cv;using namespace std;Mat image;bool backprojMode = false;bool selectObject = false;//用来判断是否选中，当鼠标左键按下时为true，左键松开时为falseint trackObject = 0;bool showHist = true;Point origin;//选中的起点Rect selection;//选中的区域int vmin = 10, vmax = 256, smin = 30;//图像掩膜需要的边界常数//鼠标事件响应函数，这个函数从按下左键时开始响应直到左键释放static void onMouse( int event, int x, int y, int, void* ){    if( selectObject )    {//选择区域的x坐标选起点与当前点的最小值，保证鼠标不管向右下角还是左上角拉动都正确选择        selection.x = MIN(x, origin.x);        selection.y = MIN(y, origin.y);//获得选择区域的宽和高        selection.width = std::abs(x - origin.x);        selection.height = std::abs(y - origin.y);//这条语句多余，注释掉不影响结果    //  selection &= Rect(0, 0, image.cols, image.rows);    }    switch( event )    {    case CV_EVENT_LBUTTONDOWN://按下鼠标时，捕获点origin        origin = Point(x,y);        selection = Rect(x,y,0,0);        selectObject = true;//这时switch前面的if语句条件为true，执行该语句        break;    case CV_EVENT_LBUTTONUP://松开鼠标时，捕获width和height        selectObject = false;        if( selection.width > 0 && selection.height > 0 )            trackObject = -1;//重新计算直方图        break;    }}static void help()//打印控制按键说明{    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 << "\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";}const char* keys ={    "{1|  | 0 | camera number}"};int main( int argc, const char** argv ){    help();    VideoCapture cap;    Rect trackWindow;//要跟踪的窗口    int hsize = 16;//创建直方图时要用的常量    float hranges[] = {0,180};    const float* phranges = hranges;    CommandLineParser parser(argc, argv, keys);    int camNum = parser.get<int>("1");//现在camNum = 0    cap.open(camNum);    //摄像头画面捕捉不成功则退出程序    if( !cap.isOpened() )    {        help();        cout << "***Could not initialize capturing...***\n";        cout << "Current parameter's value: \n";        parser.printParams();//打印出cmd参数信息        return -1;    }    //关于显示窗口的一些设置    namedWindow( "Histogram", 0 );    namedWindow( "CamShift Demo", 0 );    //设置鼠标事件，把鼠标响应与onMouse函数关联起来    setMouseCallback( "CamShift Demo", onMouse, 0 );    //创建三个滑块条，特定条件用滑块条选择不同参数能获得较好的跟踪效果    createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );    createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );    createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );    //创建Mat变量，frame, hsv, hue, mask, hist, histimg, backproj;其中histimg初始化为200*300的零矩阵    Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;    bool paused = false;    //主循环    for(;;)    {        if( !paused )        {            cap >> frame;//从摄像头输入frame            if( frame.empty() )//为空，跳出主循环                break;        }        frame.copyTo(image);//frame存入image        if( !paused )        {            cvtColor(image, hsv, CV_BGR2HSV);//将BGR转换成HSV格式，存入hsv中，hsv是3通道            if( trackObject )//松开鼠标左键时，trackObject为-1，执行核心部分            {                int _vmin = vmin, _vmax = vmax;                //inRange用来检查元素的取值范围是否在另两个矩阵的元素取值之间，返回验证矩阵mask（0-1矩阵）                //这里用于制作掩膜板，只处理像素值为H:0~180，S:smin~256, V:vmin~vmax之间的部分。mask是要求的，单通道                inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),                        Scalar(180, 256, MAX(_vmin, _vmax)), mask);                int ch[] = {0, 0};//type包含通道信息，例如CV_8UC3，而深度信息depth不包含通道信息，例如CV_8U.                hue.create(hsv.size(), hsv.depth());//hue是单通道                mixChannels(&hsv, 1, &hue, 1, ch, 1);//将H分量拷贝到hue中，其他分量不拷贝。                if( trackObject < 0 )                {                    //roi为选中区域的矩阵，maskroi为0-1矩阵                    Mat roi(hue, selection), maskroi(mask, selection);                    //绘制色调直方图hist，仅限于用户选定的目标矩形区域                    calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);                    normalize(hist, hist, 0, 255, CV_MINMAX);//必须是单通道，hist是单通道。归一化，范围为0-255                    trackWindow = selection;                    trackObject = 1;//trackObject置1，接下来就不需要再执行这个if块了                    histimg = Scalar::all(0);//用于显示直方图                    //计算每个直方的宽度                    int binW = histimg.cols / hsize;//hsize为16，共显示16个                    Mat buf(1, hsize, CV_8UC3);//                    for( int i = 0; i < hsize; i++ )//直方图每一项的颜色是根据项数变化的                        buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);                    cvtColor(buf, buf, CV_HSV2BGR);                    //量化等级一共有16个等级，故循环16次，画16个直方块                    for( int i = 0; i < hsize; i++ )                    {                        int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);//获取直方图每一项的高                        //画直方图。opencv中左上角为坐标原点                        rectangle( histimg, Point(i*binW,histimg.rows),                                   Point((i+1)*binW,histimg.rows - val),                                   Scalar(buf.at<Vec3b>(i)), -1, 8 );                    }                }                //根据直方图hist计算整幅图像的反向投影图backproj,backproj与hue相同大小                calcBackProject(&hue, 1, 0, hist, backproj, &phranges);                //计算两个矩阵backproj、mask的每个元素的按位与，返回backproj                backproj &= mask;                //调用最核心的camshift函数//TermCriteria是算法完成的条件                RotatedRect trackBox = CamShift(backproj, trackWindow,                                    TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 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 )//转换显示方式，将backproj显示出来                    cvtColor( backproj, image, CV_GRAY2BGR );//画出椭圆，第二个参数是一个矩形，画该矩形的内接圆                ellipse( image, trackBox, Scalar(0,0,255), 3, CV_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 );        //每轮都要等待用户的按键控制        char c = (char)waitKey(10);        if( c == 27 )//"Esc"键，直接退出            break;        switch(c)        {        case 'b'://转换显示方式            backprojMode = !backprojMode;            break;        case 'c'://停止追踪            trackObject = 0;            histimg = Scalar::all(0);            break;        case 'h'://隐藏或显示直方图            showHist = !showHist;            if( !showHist )                destroyWindow( "Histogram" );            else                namedWindow( "Histogram", 1 );            break;        case 'p'://暂停            paused = !paused;//frame停止从摄像头获取图像，只显示旧的图像            break;        default:            ;        }    }    return 0;}
0 0