opencv +MFC实现视频播放、暂停、视频标注、跟踪

       最近在做视频标注、跟踪这一块，参考了好多资料。

       简易功能已实现。

       先把代码和效果图贴出来。

环境：VS2013+opencv2.4.8 

注：vs2013工程师基于MFC，对话框的

代码如下：

#include "CvvImage.h"#include "opencv2/opencv.hpp"#include <iostream>#include <string>#include <vector>#include <fstream>CEvent start_event;int terminate_flag;#ifdef _DEBUG#define new DEBUG_NEW#endifusing namespace std;using namespace cv;// Global variablesbool is_drawing = false;vector<Rect> rectVec;vector<Rect> biaozhu_boxs;Rect drawing_box;Mat img_original, img_drawing;IplImage* pFrame;bool flag;Scalar blue = Scalar(255, 0, 0);Scalar red = Scalar(0, 0, 255);Scalar black = Scalar(0, 0, 0);Scalar white = Scalar(255, 255, 255);DWORD WINAPI PlayVideo(LPVOID lpParam);VideoCapture capture;char* trackBarName = "播放进度";    //trackbar控制条名称double totalFrame = 1.0;     //视频总帧数double currentFrame = 1.0;    //当前播放帧int trackbarValue = 1;    //trackbar控制量int trackbarMax = 255;   //trackbar控制条最大值double frameRate = 1.0;  //视频帧率double controlRate = 0.1;////控制条回调函数void TrackBarFunc(int, void(*)){controlRate = (double)trackbarValue / trackbarMax*totalFrame; //trackbar控制条对视频播放进度的控制capture.set(CV_CAP_PROP_POS_FRAMES, controlRate);//设置当前播放帧}//播放视频DWORD WINAPI PlayVideo(LPVOID lpParam){CVideoLableDemo3Dlg* pThis = (CVideoLableDemo3Dlg*)lpParam;//【1】读入视频  capture.open("HaiZeiWang.mp4");//【2】检测是否已经打开 if (!capture.isOpened()){return -1;}totalFrame = capture.get(CV_CAP_PROP_FRAME_COUNT);  //获取总帧数frameRate = capture.get(CV_CAP_PROP_FPS);   //获取帧率double pauseTime = 1000 / frameRate; // 由帧率计算两幅图像间隔时间//在图像窗口上创建控制条createTrackbar(trackBarName, "Video", &trackbarValue, trackbarMax, TrackBarFunc);TrackBarFunc(0, 0);while (1){capture >> img_original;if (img_original.empty()){break;}img_original.copyTo(img_drawing);//保证视频标注后跟随for (vector<Rect>::iterator it = biaozhu_boxs.begin(); it != biaozhu_boxs.end(); ++it){rectangle(img_drawing, (*it), Scalar(0, 255, 0));}WaitForSingleObject(start_event, INFINITE);start_event.SetEvent();if (terminate_flag == -1){terminate_flag = 0;_endthreadex(0);};if (flag){CvxText text("simhei.ttf");const char *msg = "在OpenCV中输出汉字！";float p = 1;text.setFont(NULL, NULL, NULL, &p);// 透明处理text.putText(&(IplImage)img_drawing, msg, cvPoint(100, 400), blue); } char c = cvWaitKey(33);imshow("Video", img_drawing);      //在窗口显示图像 }}//打开视频void CVideoLableDemo3Dlg::OnBnClickedOpenvideo(){HANDLE hThreadSend;//创建独立线程发送数据DWORD ThreadSendID;start_event.SetEvent();hThreadSend = CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE)PlayVideo, (LPVOID)this, 0, &ThreadSendID);CloseHandle(hThreadSend);}//暂停播放void CVideoLableDemo3Dlg::OnBnClickedSuspendvideo(){//f_capture_update = false;CString buttonText;m_StopButton.GetWindowText(buttonText);if (buttonText.Compare(_T("暂停播放")) == 0){start_event.ResetEvent();m_StopButton.SetWindowTextW(_T("继续"));}else{start_event.SetEvent();m_StopButton.SetWindowText(_T("暂停播放"));}}//视频标注void CVideoLableDemo3Dlg::OnBnClickedLable(){// TODO:  在此添加控件通知处理程序代码//start_event.ResetEvent();//m_StopButton.SetWindowTextW(_T("继续"));img_original.copyTo(img_drawing);setMouseCallback("Video", onMouse, 0);int frame_counter = 0;while (1){int c = waitKey(0);if ((c & 255) == 27){cout << "Exiting ...\n";break;}switch ((char)c){case 'n'://read the next frame++frame_counter;capture >> img_original;if (img_original.empty()){cout << "\nVideo Finished!" << endl;}img_original.copyTo(img_drawing);//save all of the labeling rectsfor (vector<Rect>::iterator it = biaozhu_boxs.begin(); it != biaozhu_boxs.end(); ++it){rectangle(img_drawing, (*it), Scalar(0, 255, 0));}break;case 'z'://undo the latest labelingif (!biaozhu_boxs.empty()){vector<Rect>::iterator it_end = biaozhu_boxs.end();--it_end;biaozhu_boxs.erase(it_end);}img_original.copyTo(img_drawing);for (vector<Rect>::iterator it = biaozhu_boxs.begin(); it != biaozhu_boxs.end(); ++it){rectangle(img_drawing, (*it), Scalar(0, 255, 0));}break;case 'c'://clear all the rects on the imagebiaozhu_boxs.clear();img_original.copyTo(img_drawing);}imshow("Video", img_drawing);}}//这一块暂时还没用上void CVideoLableDemo3Dlg::ImageText(Mat& img, const char *text, Point left_top, Point right_bottom, Scalar fonts_color, int thickness, float row_spacing){CvxText fonts("..\\3rdparty\\script\\msyh.ttc");CvPoint point;point.x = left_top.x;point.y = left_top.y + thickness;//putText函数中的point是以左下角坐标为起始输入位置的，所以要转换坐标float p = 1; //字体透明度CvScalar type;type.val[0] = thickness;    // 字体大小type.val[1] = 0.5;   // 空白字符大小比例type.val[2] = 0.1;   // 间隔大小比例type.val[3] = 0;      // 旋转角度(不支持)fonts.setFont(NULL, &type, NULL, &p);}string readTxt(string file){string final;ifstream fin;fin.open(file);string str;while (!fin.eof()){getline(fin, str);final = final + str + "\n";}cout << final << endl;fin.close();return final;}//文字标注void CVideoLableDemo3Dlg::OnBnClickedVideotextlable(){  flag = true;}void CVideoLableDemo3Dlg::OnBnClickedSavepicture(){time_t t = time(NULL);  //获取当前系统的日历时间tm *local = localtime(&t);char time_name[30];int i = 0;const char* path;//保存的图片名，可以把保存路径写在filename中sprintf(time_name, "%d.%d.%d.%d.%d %s", \local->tm_year + 1900, local->tm_mon + 1, \local->tm_mday, local->tm_hour, local->tm_min, ".jpg");imwrite(time_name, img_drawing);//没有说明保存路径时，图片自动存放在vs当前工程的文件夹里；}//目标跟踪的鼠标移动void onMouseTargetTracking(int event, int x, int y, int, void*){if (selectObject)//只有当鼠标左键按下去时才有效，然后通过if里面代码就可以确定所选择的矩形区域selection了{selection.x = MIN(x, origin.x);//矩形左上角顶点坐标selection.y = MIN(y, origin.y);selection.width = std::abs(x - origin.x);//矩形宽selection.height = std::abs(y - origin.y);//矩形高selection &= Rect(0, 0, image.cols, image.rows);//用于确保所选的矩形区域在图片范围内}switch (event){case CV_EVENT_LBUTTONDOWN:origin = Point(x, y);selection = Rect(x, y, 0, 0);//鼠标刚按下去时初始化了一个矩形区域selectObject = true;break;case CV_EVENT_LBUTTONUP:selectObject = false;if (selection.width > 0 && selection.height > 0)trackObject = -1;break;}}//目标跟踪void CVideoLableDemo3Dlg::OnBnClickedObjecttracking(){VideoCapture cap; //定义一个摄像头捕捉的类对象Rect trackWindow;RotatedRect trackBox;//定义一个旋转的矩阵类对象int hsize = 16;float hranges[] = { 0, 180 };//hranges在后面的计算直方图函数中要用到const float* phranges = hranges;cap.open("out3.mp4");if (!cap.isOpened()){cout << "***Could not initialize capturing...***\n";cout << "Current parameter's value: \n";}namedWindow("Histogram", 0);namedWindow("CamShift Demo", 0);setMouseCallback("CamShift Demo", onMouseTargetTracking, 0);//消息响应机制Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;bool paused = false;//进入视频帧处理主循环  for (;;){if (!paused)//没有暂停{cap >> frame;//从视频中输出一帧图像到frame中if (frame.empty())break;}frame.copyTo(image);//复制一幅图像到imageif (!paused)//没有按暂停键{cvtColor(image, hsv, CV_BGR2HSV);//将rgb转化成hsv空间的if (trackObject)//trackObject初始化为0,或者按完键盘的'c'键后也为0，当鼠标单击松开后为-1{int _vmin = vmin, _vmax = vmax;//inRange函数的功能是检查输入数组每个元素大小是否在2个给定数值之间，可以有多通道,mask保存0通道的最小值，也就是h分量//这里利用了hsv的3个通道，比较h,0~180,s,smin~256,v,min(vmin,vmax),max(vmin,vmax)。如果3个通道都在对应的范围内，则//mask对应的那个点的值全为1(0xff)，否则为0(0x00).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());//hue初始化为与hsv大小深度一样的矩阵，色调的度量是用角度表示的，红绿蓝之间相差120度，反色相差180度mixChannels(&hsv, 1, &hue, 1, ch, 1);//将hsv第一个通道(也就是色调)的数复制到hue中，0索引数组if (trackObject < 0)//鼠标选择区域松开后，该函数内部又将其赋值1{//此处的构造函数roi用的是Mat hue的矩阵头，且roi的数据指针指向hue，即共用相同的数据，select为其感兴趣的区域Mat roi(hue, selection), maskroi(mask, selection);//mask保存的hsv的最小值//calcHist()函数第一个参数为输入矩阵序列，第2个参数表示输入的矩阵数目，第3个参数表示将被计算直方图维数通道的列表，第4个参数表示可选的掩码函数//第5个参数表示输出直方图，第6个参数表示直方图的维数，第7个参数为每一维直方图数组的大小，第8个参数为每一维直方图bin的边界calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);//将roi的0通道计算直方图并通过mask放入hist中，hsize为每一维直方图的大小normalize(hist, hist, 0, 255, CV_MINMAX);//将hist矩阵进行数组范围归一化，都归一化到0~255trackWindow = selection;trackObject = 1;//只要鼠标选完区域松开后，且没有按键盘清0键'c'，则trackObject一直保持为1，因此该if函数只能执行一次，除非重新选择跟踪区域histimg = Scalar::all(0);//与按下'c'键是一样的，这里的all(0)表示的是标量全部清0int binW = histimg.cols / hsize;  //histing是一个200*300的矩阵，hsize应该是每一个bin的宽度，也就是histing矩阵能分出几个bin出来Mat buf(1, hsize, CV_8UC3);//定义一个缓冲单bin矩阵for (int i = 0; i < hsize; i++)//saturate_case函数为从一个初始类型准确变换到另一个初始类型buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180. / hsize), 255, 255);//Vec3b为3个char值的向量cvtColor(buf, buf, CV_HSV2BGR);//将hsv又转换成bgrfor (int i = 0; i < hsize; i++){int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows / 255);//at函数为返回一个指定数组元素的参考值rectangle(histimg, Point(i*binW, histimg.rows),    //在一幅输入图像上画一个简单抽的矩形，指定左上角和右下角，并定义颜色，大小，线型等Point((i + 1)*binW, histimg.rows - val),Scalar(buf.at<Vec3b>(i)), -1, 8);}}calcBackProject(&hue, 1, 0, hist, backproj, &phranges);//计算直方图的反向投影，计算hue图像0通道直方图hist的反向投影，并让入backproj中backproj &= mask;//opencv2.0以后的版本函数命名前没有cv两字了，并且如果函数名是由2个意思的单词片段组成的话，且前面那个片段不够成单词，则第一个字母要//大写，比如Camshift，如果第一个字母是个单词，则小写，比如meanShift，但是第二个字母一定要大写RotatedRect trackBox = CamShift(backproj, trackWindow,               //trackWindow为鼠标选择的区域，TermCriteria为确定迭代终止的准则TermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1));//CV_TERMCRIT_EPS是通过forest_accuracy,CV_TERMCRIT_ITERif (trackWindow.area() <= 1)                                                  //是通过max_num_of_trees_in_the_forest  {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);//Rect函数为矩阵的偏移和大小，即第一二个参数为矩阵的左上角点坐标，第三四个参数为矩阵的宽和高}if (backprojMode)cvtColor(backproj, image, CV_GRAY2BGR);//因此投影模式下显示的也是rgb图？ellipse(image, trackBox, Scalar(0, 0, 255), 3, CV_AA);//跟踪的时候以椭圆为代表目标}}//后面的代码是不管pause为真还是为假都要执行的else if (trackObject < 0)//同时也是在按了暂停字母以后paused = false;if (selectObject && selection.width > 0 && selection.height > 0){Mat roi(image, selection);bitwise_not(roi, roi);//bitwise_not为将每一个bit位取反}imshow("CamShift Demo", image);imshow("Histogram", histimg);char c = (char)waitKey(10);if (c == 27)              //退出键break;switch (c){case 'b':             //反向投影模型交替backprojMode = !backprojMode;break;case 'c':            //清零跟踪目标对象trackObject = 0;histimg = Scalar::all(0);break;case 'h':          //显示直方图交替showHist = !showHist;if (!showHist)destroyWindow("Histogram");elsenamedWindow("Histogram", 1);break;case 'p':       //暂停跟踪交替paused = !paused;break;default:}}}