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我正在尝试使用 opencv 级联实现人脸检测 viola jones 分类器。这是我正在使用的代码：

int main( ){
SYSTEMTIME tm;

GetLocalTime(&tm);
printf("Date: %02d.%02d.%d, %02d:%02d:%02d:%02d\n", tm.wDay, tm.wMonth, tm.wYear, tm.wHour, tm.wMinute, tm.wSecond, tm.wMilliseconds);
//CString t = CTime::GetCurrentTime().Format("%H:%M:%S:%MS");
Mat image;
Mat frame_gray;

image = imread("test.jpg", CV_LOAD_IMAGE_COLOR); 
namedWindow( "window1", 1 );   imshow( "window1", image );


// Load Face cascade (.xml file)
CascadeClassifier face_cascade;
face_cascade.load( "cascades.xml" );



cvtColor( image, frame_gray, CV_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );


GetLocalTime(&tm);
printf("Date: %02d.%02d.%d, %02d:%02d:%02d:%02d\n", tm.wDay, tm.wMonth, tm.wYear, tm.wHour, tm.wMinute, tm.wSecond, tm.wMilliseconds);
float pyramidScale = 1.5f;
// Detect faces
std::vector<Rect> faces;
face_cascade.detectMultiScale( frame_gray, faces, pyramidScale, 3, 0, Size(20, 20), Size(50, 50));

GetLocalTime(&tm);
printf("Date: %02d.%02d.%d, %02d:%02d:%02d:%02d\n", tm.wDay, tm.wMonth, tm.wYear, tm.wHour, tm.wMinute, tm.wSecond, tm.wMilliseconds);

// Draw circles on the detected faces
for( int i = 0; i < faces.size(); i++ )
{
    Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
    ellipse( image, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 255, 255 ), 4, 8, 0 );
}

imshow( "Detected Face", image );


SYSTEMTIME tm1;
GetLocalTime(&tm);
printf("Date: %02d.%02d.%d, %02d:%02d:%02d:%02d\n", tm.wDay, tm.wMonth, tm.wYear, tm.wHour, tm.wMinute, tm.wSecond, tm.wMilliseconds);
//cout<< "Time : "<<tm.wHour<<":"<<tm.wMinute << ":"<< tm.wSecond << ":" << tm.wMilliseconds << "\n";
waitKey(0);                  
return 0;
}

问题是它说这是 opencv 中的 viola jones 实现，通常需要 30fps 才能运行（来自作者方面），但它需要 6 秒才能运行正常的高清图像以进行 1920x1080 左右的人脸检测。我想问一下实施是否正确，或者我实施该方法的方式有什么问题，有什么办法可以让它更快吗？cascade.xml 是我使用示例图像训练的文件。谢谢你。

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