samples/cpp/camshiftdemo.cpp

一个使用均值漂移跟踪算法的示例

#include "opencv2/core/utility.hpp"
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
 
#include <iostream>
#include <ctype.h>
 
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;
 
// 用户在要跟踪的对象周围绘制方框。这将触发 CAMShift 开始跟踪
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; // 在 main() 循环中设置 CAMShift 属性
        break;
    }
}
 
string hot_keys =
    "\n\n快捷键：\n"
    "\tESC - 退出程序\n"
    "\tc - 停止跟踪\n"
    "\tb - 切换到/从反向投影视图\n"
    "\th - 显示/隐藏目标直方图\n"
    "\tp - 暂停视频\n"
    "要初始化跟踪，请使用鼠标选择对象\n";
 
static void help(const char** argv)
{
cout << "\n这是一个演示，展示了基于均值漂移的跟踪\n"
            "您可以选择一个彩色物体，例如您的脸部，然后程序会跟踪它。\n"
            "程序读取视频摄像头（默认情况下为 0，或者用户输入的摄像头编号）\n"
            "用法：\n\t";
cout << argv[0] << " [摄像头编号]\n";
cout << hot_keys;
}
 
const char* keys =
{
    "{help h | | 显示帮助信息}{@camera_number| 0 | 摄像头编号}"
};
 
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(argv);
        return 0; 0;
    }
    int camNum = parser.get<int>(0);
cap.open(camNum);
 
    if( !cap.isOpened() )
    {
help(argv);
cout << "***无法初始化捕获…***\n";
cout << "当前参数值：\n";
parser.printMessage();
        return 0; -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 )
                {
                    // 用户已选择对象，只需设置一次 CAMShift 搜索属性
                    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; // 除非用户选择新的 ROI，否则不再设置
 
histimg = Scalar::all(0);
                    int binW = histimg.cols / hsize;
                    Mat buf(1, hsize, CV_8UC3);
                    for( int i = 0; i < hsize; i++ )
buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);
                    cvtColor(buf, buf, COLOR_HSV2BGR);
 
                    for( int i = 0; i < hsize; i++ )
                    {
                        int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);
                        rectangle( histimg, Point(i*binW,histimg.rows),
                                   Point((i+1)*binW,histimg.rows - val),
                                   Scalar(buf.at<Vec3b>(i)), -1, 8 );
                    }
                }
 
                // 执行 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 演示", image );
        imshow( "直方图", 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( "直方图" );
            else
                namedWindow( "直方图", 1 );
            break;
        case 'p'
paused = !paused;
            break;
        default:
            ;
        }
    }
 
    return 0; 0;
}