opencv_traincascade训练分类器，手势识别。

opencv_traincascade 训练方法，参考本人的博客：Here；

xml和video下载地址：Here。

测试代码：

#include <iostream>#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>#include <opencv2/opencv.hpp>using namespace std;using namespace cv;// Global variables// Copy this file from opencv/data/haarscascades to target folderstring face_cascade_name = "/Users/liupeng/Desktop/my/handDetection/handDetection/hand.xml";CascadeClassifier *face_cascade;string window_name = "Capture - Face detection";int filenumber; // Number of file to be savedstring filename;// Function Headersclass faceDetection{private:    std::vector<Rect> faces;public:    faceDetection();    ~faceDetection();    void detectAndDisplay(Mat frame);};faceDetection::faceDetection(){}faceDetection::~faceDetection(){}// Function detectAndDisplayvoid faceDetection::detectAndDisplay(Mat frame){    // 报错问题所在，。    // std::vector<Rect> faces;        Mat frame_gray;    Mat crop;    Mat res;    Mat gray;    string text;    stringstream sstm;        cvtColor(frame, frame_gray, COLOR_BGR2GRAY);    equalizeHist(frame_gray, frame_gray);        // Detect faces    face_cascade->detectMultiScale(frame_gray, faces, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));        // Set Region of Interest    cv::Rect roi_b;    cv::Rect roi_c;        size_t ic = 0; // ic is index of current element    int ac = 0; // ac is area of current element        size_t ib = 0; // ib is index of biggest element    int ab = 0; // ab is area of biggest element        for (ic = 0; ic < faces.size(); ic++) // Iterate through all current elements (detected faces)            {        roi_c.x = faces[ic].x;        roi_c.y = faces[ic].y;        roi_c.width = (faces[ic].width);        roi_c.height = (faces[ic].height);                ac = roi_c.width * roi_c.height; // Get the area of current element (detected face)                roi_b.x = faces[ib].x;        roi_b.y = faces[ib].y;        roi_b.width = (faces[ib].width);        roi_b.height = (faces[ib].height);                ab = roi_b.width * roi_b.height; // Get the area of biggest element, at beginning it is same as "current" element                if (ac > ab)        {            ib = ic;            roi_b.x = faces[ib].x;            roi_b.y = faces[ib].y;            roi_b.width = (faces[ib].width);            roi_b.height = (faces[ib].height);        }                crop = frame(roi_b);        resize(crop, res, Size(128, 128), 0, 0, INTER_LINEAR); // This will be needed later while saving images        cvtColor(crop, gray, CV_BGR2GRAY); // Convert cropped image to Grayscale                // Form a filename        filename = "";        stringstream ssfn;        ssfn << filenumber << ".png";        filename = ssfn.str();        filenumber++;                // imwrite(filename, gray);                Point pt1(faces[ic].x, faces[ic].y); // Display detected faces on main window - live stream from camera        Point pt2((faces[ic].x + faces[ic].height), (faces[ic].y + faces[ic].width));        rectangle(frame, pt1, pt2, Scalar(0, 255, 0), 2, 8, 0);    }        // Show image    sstm << "Crop area size: " << roi_b.width << "x" << roi_b.height << " Filename: " << filename;    text = sstm.str();        putText(frame, text, cvPoint(30, 30), FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0, 0, 255), 1, CV_AA);    imshow("original", frame);    // waitKey();        if (!crop.empty())    {        imshow("detected", crop);        // waitKey();    }    else        destroyWindow("detected");    }int main(int argc, char* argv[]){    faceDetection *face;    face = new faceDetection;    // Load the cascade    face_cascade = new CascadeClassifier;    if (!face_cascade->load(face_cascade_name)){        printf("--(!)Error loading\n");        return (-1);    }        cvNamedWindow("Camera" , CV_WINDOW_AUTOSIZE );        // 开启摄像头。    // CvCapture* capture = cvCreateCameraCapture(CV_CAP_ANY);    // 读取视频文件夹。    CvCapture* capture = cvCreateFileCapture("/Users/liupeng/Desktop/my/handDetection/handDetection/hand.mp4");        assert(capture != NULL);        IplImage *frame = 0;        while(1)    {        frame = cvQueryFrame(capture);        if(!frame) break;                face->detectAndDisplay((Mat)frame);                char c = cvWaitKey(15);        if(c == 27)  break;    }        cvReleaseCapture(&capture);    cvReleaseImage( &frame);            return (int)0;}