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);
}
}
void CascadeClassifier::ApplyOriginalSize(IntImage& original,const CString filename)
{
IntImage procface;
IntImage image,square;
REAL sq,ex,value;
int result;
CRect rect;
REAL ratio;
vector<CRect> results;
procface.Copy(original);
ratio = 1.0;
results.clear();
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+=1)
for(int j=0,size_y=image.width-sy; j<size_y; j+=1)
{
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++)
{
REAL f1 = 0;
REAL** p = image.data + i;
SimpleClassifier& s = ac[k].scs[t];
switch(s.type)
{
case 0:
f1 = p[s.x1][j+s.y3] - p[s.x1][j+s.y1] + p[s.x3][j+s.y3] - p[s.x3][j+s.y1]
+ REAL(2)*(p[s.x2][j+s.y1] - p[s.x2][j+s.y3]);
break;
case 1:
f1 = p[s.x3][j+s.y1] + p[s.x3][j+s.y3] - p[s.x1][j+s.y1] - p[s.x1][j+s.y3]
+ REAL(2)*(p[s.x1][j+s.y2] - p[s.x3][j+s.y2]);
break;
case 2:
f1 = p[s.x1][j+s.y1] - p[s.x1][j+s.y3] + p[s.x4][j+s.y3] - p[s.x4][j+s.y1]
+ REAL(3)*(p[s.x2][j+s.y3] - p[s.x2][j+s.y1] + p[s.x3][j+s.y1] - p[s.x3][j+s.y3]);
break;
case 3:
f1 = p[s.x1][j+s.y1] - p[s.x1][j+s.y4] + p[s.x3][j+s.y4] - p[s.x3][j+s.y1]
+ REAL(3)*(p[s.x3][j+s.y2] - p[s.x3][j+s.y3] + p[s.x1][j+s.y3] - p[s.x1][j+s.y2]);
break;
case 4:
f1 = p[s.x1][j+s.y1] + p[s.x1][j+s.y3] + p[s.x3][j+s.y1] + p[s.x3][j+s.y3]
- REAL(2)*(p[s.x2][j+s.y1] + p[s.x2][j+s.y3] + p[s.x1][j+s.y2] + p[s.x3][j+s.y2])
+ REAL(4)*p[s.x2][j+s.y2];
break;
default:
#ifndef DEBUG
__assume(0);
#else
;
#endif
}
if(s.parity!=0)
if(f1<sq*s.thresh)
value += ac[k].alphas[t];
else ;
else if(f1>=sq*s.thresh)
value += ac[k].alphas[t];
else ;
}
if(value<ac[k].thresh)
{
result = 0;
break;
}
}
if(result!=0)
{
const REAL r = 1.0/ratio;
rect.left = (LONG)(j*r);
rect.top = (LONG)(i*r);
rect.right = (LONG)((j+sy)*r);
rect.bottom = (LONG)((i+sx)*r);
results.push_back(rect);
}
}
ratio = ratio * REAL(0.8);
procface.Resize(image,REAL(0.8));
SwapIntImage(procface,image);
}
total_fp += results.size();
PostProcess(results,2);
PostProcess(results,0);
DrawResults(original,results);
// original.Save(filename+"_result.JPG");
}
