#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;}
