void HOGTrainer::train() {
vector<Mat> fullPosLst;
vector<Mat> fullNegLst;
vector<Mat> negLst;
vector<Mat> posLst;
vector<Mat> gradientLst;
vector<int> labels;
loadImages(posDir, pos, fullPosLst);
samplePos(fullPosLst, posLst, size);
labels.assign(posLst.size(), +1);
const unsigned int old = (unsigned int) labels.size();
loadImages(negDir, neg, fullNegLst);
sampleNeg(fullNegLst, negLst, size);
labels.insert(labels.end(), negLst.size(), -1);
cout << old << " " << labels.size();
CV_Assert(old < labels.size());
computeHog(posLst, gradientLst, size);
computeHog(negLst, gradientLst, size);
trainSvm(gradientLst, labels);
}
esvmHog *computeHogWrapper(const char *filename,const int cellWidth,const bool enablePadding,const int padding,const int userTasks)
{
esvmImage *img = readImage(filename);
int numRows = img->numRows;
int numCols = img->numCols;
int numChannels = img->numChannels;
assert(numChannels == 3);
int *im = img->im;
esvmHog *soln;
soln = computeHog(im,numRows,numCols,numChannels,cellWidth,enablePadding,padding,userTasks);
free(img->im); //frees int *im as well.
free(img);
return soln;
}
esvmHogPyr *computeHogScale(cv::Mat img,const int cellWidth,
const int maxLevels,const int minDimension,const int interval,
const float minScale,const bool enablePadding,const int padding,const int userTasks,
const bool useMexResize)
{
int numRows = img.rows;
int numCols = img.cols;
int numChannels = 3;
float sc = pow(2,1.0/interval);
esvmHog **pyr = (esvmHog **)esvmCalloc(maxLevels,sizeof(esvmHog *));
float *scaleArr = (float *)esvmCalloc(maxLevels,sizeof(float));
//do the first level outside the loop. So that you don't have to make a call to resize
//OpenCV resize does some weird stuff on resize factor 1.0
int *tmpim = RgbtoIm(img,numRows,numCols,numChannels);
scaleArr[0]=1.0f;
pyr[0] = computeHog(tmpim, numRows, numCols, numChannels, cellWidth,
enablePadding, padding, userTasks);
free(tmpim);
int counter = 1;
float *flIm;
cv::Mat dst;
if(useMexResize==true) {
flIm = RgbtoImFlTranspose(img,numRows,numCols,numChannels);
}
for(int i=2;i<=maxLevels;i++) {
float scale = 1.0 / pow(sc,i-1);
scaleArr[i-1] = scale;
int nr = round((float)numRows * scale);
int nc = round((float)numCols * scale);
if(scale < minScale) {
break;
}
if(min(nr,nc)<=minDimension) {
break;
}
int *im;
if(useMexResize==false) {
dst.create((int)nc,(int)nr,img.type());
cv::resize(img,dst,dst.size(), 0, 0, ESVM_INTERP);
im = RgbtoIm(dst,(int)nr,(int)nc,numChannels);
}
else {
//im = mexResize(flIm,numRows,numCols,numChannels,numRows*scale,numCols*scale);
im = mexResize(flIm,numRows,numCols,numChannels,nr,nc);
}
pyr[i-1] = computeHog(im, nr, nc, numChannels, cellWidth,
enablePadding, padding, userTasks);
if(__unlikely(pyr[i-1]==NULL))
break;
counter++;
//if(useMexResize==false)
// cvReleaseImage(&dst);
free(im);
if(__likely(enablePadding==true)) {
if( max(pyr[i-1]->rows-(padding<<1),pyr[i-1]->cols-(padding<<1)) <= minDimension) {
break;
}
}
else {
if(max(pyr[i-1]->rows,pyr[i-1]->cols) <= minDimension) {
break;
}
}
}
scaleArr = (float *)realloc((void *)scaleArr,counter*sizeof(float));
esvmHogPyr *hogpyr = (esvmHogPyr *)esvmMalloc(sizeof(esvmHogPyr));
hogpyr->num = counter;
hogpyr->hogs = pyr;
hogpyr->scale = scaleArr;
//FIXME:: We can shrink pyr from maxLevels to counter, using realloc.
//It is not a serious problem since pyr actually contains maxLevels*sizeof(esvmHog *) bytes
//cvReleaseImage(&img);
if(useMexResize==true)
free(flIm);
return hogpyr;
}
