mini6410成功移植OPENCV(2)

保存图像代码
    unsigned char * pBuffer =video_dev.buffer;
    fp=fopen("./photo.jpg","w");
    fwrite(pBuffer,12000,1,fp);
    fclose(fp);
在利用IplImage把图片读到内存中。接着就是对他进行人脸检测处理。
void photo::detect_and_draw(IplImage *img)
{
    static CvScalar colors[] =
    {
        {{0,0,255}},
        {{0,128,255}},
        {{0,255,255}},
        {{0,255,0}},
        {{255,128,0}},
        {{255,255,0}},
        {{0,255,0}},
        {{255,0,255}}
    };

double scale = 2;
    //建立一个空的灰度图
    IplImage* gray = cvCreateImage( cvSize(img->width,img->height), 8, 1 );
    //建立一个空圆形的灰度图
    IplImage* small_img = cvCreateImage( cvSize( cvRound (img->width/scale),
                         cvRound (img->height/scale)),
                     8, 1 );
    int i;
    //图像转换RGB模式转为灰度图
    cvCvtColor( img, gray, CV_BGR2GRAY );

cvResize( gray, small_img, CV_INTER_LINEAR );
    cvEqualizeHist( small_img, small_img );
    cvClearMemStorage( storage );

if( cascade )
    {
        double t = (double)cvGetTickCount();
        CvSeq* faces = cvHaarDetectObjects( small_img, cascade, storage,
                                            1.1, 2, 0/*CV_HAAR_DO_CANNY_PRUNING*/,
                                            cvSize(30, 30) );
        t = (double)cvGetTickCount() - t;
        printf( "detection time = %gms\n", t/((double)cvGetTickFrequency()*1000.) );

for( i = 0; i < (faces ? faces->total : 0); i++ )
        {
            CvRect* r = (CvRect*)cvGetSeqElem( faces, i );
            CvPoint center;
            int radius;
            center.x = cvRound((r->x + r->width*0.5)*scale);
            center.y = cvRound((r->y + r->height*0.5)*scale);
            radius = cvRound((r->width + r->height)*0.25*scale);
            //cvCircle( img, center, radius, colors[i%8], 3, 8, 0 );
            cvRectangle(img,cvPoint(center.x-radius,center.y-radius),cvPoint(center.x+radius,center.y+radius),colors[i%8],3,8,0);
            //cvRect(center.x-radius,center.y-radius,center.x+radius,center.y+radius);

}
    }
}