联合多个手势分类器做的猜拳游戏

经过多天的努力，做出几个分类器然后利用下面代码进行组合调用，虽然效果不是很好，但是已经算是进步了。

#define _CRT_SECURE_NO_WARNINGS
//手势检测器测试代码
#include"iostream"
#include"highgui.h"
#include"cv.h"
using namespace std;
//定义全局变量cascase指针(彩色)
CvHaarClassifierCascade* cascade2 = NULL;
CvHaarClassifierCascade* cascade5 = NULL;
CvHaarClassifierCascade* cascade10 = NULL;
//（灰度检测器）
CvHaarClassifierCascade* graycascade2 = NULL;
CvHaarClassifierCascade* graycascade5 = NULL;
CvHaarClassifierCascade* graycascade10 = NULL;

IplImage* fit = cvLoadImage("F:\Opencv\Project\Codes\SampleMake\BetFitGame\fit.bmp");
IplImage* hand = cvLoadImage("F:\Opencv\Project\Codes\SampleMake\BetFitGame\hand.bmp");
IplImage* sci = cvLoadImage("F:\Opencv\Project\Codes\SampleMake\BetFitGame\scisor.bmp");
IplImage* jpg = cvLoadImage("F:\Opencv\Project\Codes\SampleMake\BetFitGame\none.bmp");
//要加载的分类器全路径（有色）
char str5[] = "F:\Opencv\detector\color\colorhand5cascade.xml";
char str2[] = "F:\Opencv\detector\color\colorhand2\name.xml";
char str10[] = "F:\Opencv\detector\color\colorhand10cascade.xml";
//(灰度检测器)
char graystr2[] = "F:\Opencv\detector\gray\grayhand2\name.xml";
char graystr5[] = "F:\Opencv\detector\gray\grayhand5cascade.xml";
char graystr10[] = "F:\Opencv\detector\gray\grayhand10cascade.xml";

CvCapture* capture = NULL;
//设置三个内存，检测的时候使用
CvMemStorage* storage2 = cvCreateMemStorage(0);
CvMemStorage* storage5 = cvCreateMemStorage(0);
CvMemStorage* storage10 = cvCreateMemStorage(0);
//灰度
CvMemStorage* graystorage2 = cvCreateMemStorage(0);
CvMemStorage* graystorage5 = cvCreateMemStorage(0);
CvMemStorage* graystorage10 = cvCreateMemStorage(0);
//定义三个全局变量的序列，储存获得的轮廓
CvSeq* seq2 = 0;
CvSeq* seq5 = 0;
CvSeq* seq10 = 0;
//灰度
CvSeq* grayseq2 = 0;
CvSeq* grayseq5 = 0;
CvSeq* grayseq10 = 0;
//定义三个指针类型的矩形变量
CvRect* rect2 = NULL;
CvRect* rect5 = NULL;
CvRect* rect10 = NULL;
//灰度
CvRect* grayrect2 = NULL;
CvRect* grayrect5 = NULL;
CvRect* grayrect10 = NULL;

//设定缩放比例
double scale = 3;
//定义三张小图片，供转换后检测使用
IplImage* simg2 = NULL;
IplImage* simg5 = NULL;
IplImage* simg10 = NULL;
//灰度
IplImage* graysimg2 = NULL;
IplImage* graysimg5 = NULL;
IplImage* graysimg10 = NULL;
void LoadDetector()//加载分类器
{
    //加载分类器(彩色)
    try{ cascade2 = (CvHaarClassifierCascade*)cvLoad(str2); }
    catch (cv::Exception){ cout << "加载分类器" << str2 << "出现错误" << endl; exit(0); }
    try{ cascade10 = (CvHaarClassifierCascade*)cvLoad(str10); }
    catch (cv::Exception){ cout << "加载分类器" << str10 << "出现错误" << endl; exit(0); }
    try{ cascade5 = (CvHaarClassifierCascade*)cvLoad(str5); }
    catch (cv::Exception){ cout << "加载分类器" << str5 << "出现错误" << endl; exit(0); }
    //灰度
    try{ graycascade2 = (CvHaarClassifierCascade*)cvLoad(graystr2); }
    catch (cv::Exception){ cout << "加载分类器" << graystr2 << "出现错误" << endl; exit(0); }
    try{ graycascade5 = (CvHaarClassifierCascade*)cvLoad(graystr5); }
    catch (cv::Exception){ cout << "加载分类器" << graystr5 << "出现错误" << endl; exit(0); }
    try{ graycascade10 = (CvHaarClassifierCascade*)cvLoad(graystr10); }
    catch (cv::Exception){ cout << "加载分类器" << graystr10 << "出现错误" << endl; exit(0); }
}
void InitialSmallPicture(IplImage* img)
{
    //获取原图像大小
    CvSize size = cvGetSize(img);
    //缩放后的图像
    CvSize smallsize = cvSize(1.0*size.width / scale, 1.0*size.height / scale);
    //根据原图像和新尺寸创建新的图片，用来检测，可以提高检测速度
    simg2 = cvCreateImage(smallsize, img->depth, img->nChannels);
    simg5 = cvCreateImage(smallsize, img->depth, img->nChannels);
    simg10 = cvCreateImage(smallsize, img->depth, img->nChannels);
    graysimg2 = cvCreateImage(smallsize, 8, 1);
    graysimg5 = cvCreateImage(smallsize, 8, 1);
    graysimg10 = cvCreateImage(smallsize, 8, 1);
}
void DetectObject(IplImage* img)
{
    //将所有的照片按比例缩小
    cvResize(img, simg2);
    cvResize(img, simg5);
    cvResize(img, simg10);
    //转化给灰度一些
    cvCvtColor(simg2, graysimg2, CV_BGR2GRAY);
    cvCvtColor(simg5, graysimg5, CV_BGR2GRAY);
    cvCvtColor(simg10, graysimg10, CV_BGR2GRAY);
    //初始化所有的矩阵变量
    rect2 = NULL;
    rect5 = NULL;
    rect10 = NULL;
    grayrect2 = NULL;
    grayrect5 = NULL;
    grayrect10 = NULL;

    if (storage2){ cvClearMemStorage(storage2); }
    if (storage5){ cvClearMemStorage(storage5); }
    if (storage10){ cvClearMemStorage(storage10); }
    if (graystorage2){ cvClearMemStorage(graystorage2); }
    if (graystorage5){ cvClearMemStorage(graystorage5); }
    if (graystorage10){ cvClearMemStorage(graystorage10); }
    //检测函数

    //color2
    seq2 = cvHaarDetectObjects(simg2, cascade2, storage2, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT);
    if (seq2&&seq2->total > 0)
    {
        rect2 = (CvRect*)cvGetSeqElem(seq2, 0);
        return;
    }
    //gray2
    grayseq2 = cvHaarDetectObjects(graysimg2, graycascade2, graystorage2, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT);
    if (grayseq2&&grayseq2->total > 0)
    {
        grayrect2 = (CvRect*)cvGetSeqElem(grayseq2, 0);
        //if (rect2)
        return;
    }

    //color5
    seq5 = cvHaarDetectObjects(simg5, cascade5, storage5, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT, cvSize(6, 10), cvSize(140, 200));
    if (seq5&&seq5->total > 0)
    {
        rect5 = (CvRect*)cvGetSeqElem(seq5, 0);
        //rect2 = NULL;
        //grayrect2 = NULL;
        //return;
    }
    //gray5
    grayseq5 = cvHaarDetectObjects(graysimg5, graycascade5, graystorage5, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT, cvSize(6, 10), cvSize(140, 200));
    if (rect5&&grayseq5->total > 0)
    {
        grayrect5 = (CvRect*)cvGetSeqElem(grayseq5, 0);

        rect2 = NULL;
        grayrect2 = NULL;
        if (1.0*rect5->height / grayrect5->width > 1.5)
        {
            return;
        }
        else
        {
            grayrect5 = NULL;
            rect5 = NULL;
        }
    }
    //color10
    seq10 = cvHaarDetectObjects(simg10, cascade10, storage10, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT,cvSize(1,1));
    if (seq10&&seq10->total > 0)
    {
        rect10 = (CvRect*)cvGetSeqElem(seq10, 0);
        return;
    }
    //gray10
    grayseq10 = cvHaarDetectObjects(graysimg10, graycascade10, graystorage10, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT, cvSize(5, 5));
    if (grayseq10&&grayseq10->total>0)
    {
        grayrect10 = (CvRect*)cvGetSeqElem(grayseq10, 0);
        return;
    }
}
int index2 = 0;
int index5 = 0;
int index10 = 0;
void drawrectangele(IplImage* image)
{
    if (rect2 || grayrect2)
    {
        index2++;
        if (index5 >= 1)index5--;
        else index5 = 0;
        if (index10 >= 1)index10--;
        else index10 = 0;
        if (index2 >= 1){
            index5 = 0;
            index10 = 0;
            index2--;
            if (!rect2)rect2 = grayrect2;
            cvRectangle(image, cvPoint(rect2->x*scale, scale*rect2->y), cvPoint((rect2->x + rect2->width)*scale, (rect2->y + rect2->height)*scale), cvScalarAll(0), 2);
            cvPutText(image, "find scissor inside picture!", cvPoint(30, 80), &cvFont(2, 1), cvScalarAll(0));
            cvShowImage("BetGame", fit);
            return;
        }
    }
    if (rect10 || grayrect10)
    {
        index10++;
        if (index5 >= 1)index5--;
        else index5 = 0;
        if (index2 >= 1)index2--;
        else index2 = 0;
        if (index10 >= 7){
            index2 = 0;
            index5 = 0;
            index10--;
            if (!rect10)rect10 = grayrect10;
            cvRectangle(image, cvPoint(rect10->x*scale, scale*rect10->y), cvPoint((rect10->x + rect10->width)*scale, (rect10->y + rect10->height)*scale), cvScalarAll(0), 2);
            cvPutText(image, "Find fit inside picture!", cvPoint(30, 80), &cvFont(2, 1), cvScalarAll(0));
            cvShowImage("BetGame", hand);
            return;
        }
    }
    if (rect5||grayrect5)
    {
        index5++;
        if (index10 >= 1)index10--;
        else index10 = 0;
        if (index2 >= 1)index2--;
        else index2 = 0;
        if (index5 >=2){
            index10 = 0;
            index2 = 0;
            index5--;
            if (!rect5)rect5 = grayrect5;
            cvRectangle(image, cvPoint(rect5->x*scale, scale*rect5->y), cvPoint((rect5->x + rect5->width)*scale, (rect5->y + rect5->height)*scale), cvScalarAll(0), 2);
            cvPutText(image, "Find hand inside picture!", cvPoint(30, 80), &cvFont(2, 1), cvScalarAll(0));
            cvShowImage("BetGame", sci);
            return;
        }
    }
    
    cvPutText(image, "Not find anything inside picture!", cvPoint(30, 80), &cvFont(2, 1), cvScalarAll(0));
    cvShowImage("BetGame", jpg);
}
int main()
{
    LoadDetector();
    //打开摄像头
    try{ capture = cvCreateCameraCapture(0); }
    catch (cv::Exception){ cout << "打开摄像头出错" << endl; exit(0); }
    //定义新图片，并用capture初始化
    IplImage* image = cvQueryFrame(capture);
    InitialSmallPicture(image);
    //命名窗口
    cvNamedWindow("Detector Runing");
    cvNamedWindow("BetGame");

    while (true)
    {
        //循环获取图片
        image = cvQueryFrame(capture);
        //检测器运行
        if (image)
        {
            DetectObject(image);
            drawrectangele(image);
        }
        cvShowImage("Detector Runing", image);
        //如果按下ESC键就退出循环(ESC键值是27)
        if (cvWaitKey(20) == 27)break;
    }
    cvReleaseCapture(&capture);
    cvDestroyAllWindows();
    return 0;
}

说明：对摄像头伸出拳头，则反馈手掌；伸出双指（剪刀）,反馈拳头；伸出手掌，反馈剪刀。