void CascadeClassifier::ApplyOriginalSizeForInputBoosting(const CString filename,int& pointer) const
{
IntImage procface;
IntImage image,square;
REAL sq,ex,value;
int result;
CRect rect;
REAL ratio;
procface.Load(filename);
if(procface.height <=0 || procface.width<=0) return;
ratio = 1.0;
REAL paddedsize = REAL(1)/REAL((sx+1)*(sy+1));
while((procface.height>sx+1) && (procface.width>sy+1))
{
procface.CalcSquareAndIntegral(square,image);
for(int i=0,size_x=image.height-sx; i<size_x; i+=bootstrap_increment[bootstrap_level])
for(int j=0,size_y=image.width-sy; j<size_y; j+=bootstrap_increment[bootstrap_level])
{
ex = image.data[i+sx][j+sy]+image.data[i][j]-image.data[i+sx][j]-image.data[i][j+sy];
if(ex<mean_min || ex>mean_max) continue;
sq = square.data[i+sx][j+sy]+square.data[i][j]-square.data[i+sx][j]-square.data[i][j+sy];
if(sq<sq_min) continue;
ex *= paddedsize;
ex = ex * ex;
sq *= paddedsize;
sq = sq - ex;
ASSERT(sq>=0);
if(sq>0) sq = sqrt(sq);
else sq = 1.0;
if(sq<var_min) continue;
result = 1;
for(int k=0; k<count; k++)
{
value = 0.0;
for(int t=0,size=ac[k].count; t<size; t++)
value += (ac[k].alphas[t]*ac[k].scs[t].Apply(ac[k].scs[t].GetOneFeatureTranslation(image.data+i,j)/sq));
if(value<ac[k].thresh)
{
result = 0;
break;
}
}
if(result==1)
{
for(int k=1; k<=sx; k++)
for(int t=1; t<=sy; t++)
trainset[pointer].data[k][t]=image.data[i+k][j+t]-image.data[i+k][j]-image.data[i][j+t]+image.data[i][j];
pointer++;
if(pointer==totalcount) return;
}
}
ratio = ratio * bootstrap_resizeratio[bootstrap_level];
procface.Resize(image,bootstrap_resizeratio[bootstrap_level]);
SwapIntImage(procface,image);
}
}
int main(int argc,char* argv[])
{
std::cout << "usage:" << std::endl;
std::cout << argv[0] << " <video_file>" << std::endl << std::endl;
std::cout << "keys:" << std::endl;
std::cout << "space : toggle using simple post-process (NMS, non-maximal suppression)" << std::endl;
std::cout << "0 : waits to process next frame until a key pressed" << std::endl;
std::cout << "1 : doesn't wait to process next frame" << std::endl;
std::cout << "2 : resize frames 1/2" << std::endl;
std::cout << "3 : don't resize frames" << std::endl;
std::cout << "4 : resize frames 1/4" << std::endl;
if (argc < 2)
return 0;
cv::Mat src;
cv::VideoCapture capture( argv[1] );
LoadCascade(scanner);
std::cout<<"Detectors loaded."<<std::endl;
int key = 0;
int wait_time = 1;
float fx = 1;
bool rect_organization = true;
IntImage<double> original;
while( key != 27 )
{
capture >> src;
if( src.empty() ) break;
if (fx < 1)
{
cv::resize(src, src, cv::Size(), fx, fx);
}
original.Load( src );
std::vector<CRect> results;
scanner.FastScan(original, results, 2);
if(rect_organization)
{
PostProcess(results,2);
PostProcess(results,0);
RemoveCoveredRectangles(results);
}
for(size_t i = 0; i < results.size(); i++)
{
cv::rectangle(src, cvPoint(results[i].left,results[i].top),cvPoint(results[i].right,results[i].bottom),cv::Scalar(0,255,0),2 );
}
cv::imshow("result",src);
key = cv::waitKey( wait_time );
if (key == 32)
rect_organization = !rect_organization;
if (key == 48)
wait_time = 0;
if (key == 49)
wait_time = 1;
if (key == 50)
fx = 0.5;
if (key == 51)
fx = 1;
if (key == 52)
fx = 0.25;
}
cv::waitKey();
return 0;
}
