Patchwork::Patchwork(const HOGPyramid & pyramid) : padx_(pyramid.padx()), pady_(pyramid.pady()),
interval_(pyramid.interval())
{
// Remove the padding from the bottom/right sides since convolutions with Fourier wrap around
const int nbLevels = pyramid.levels().size();
rectangles_.resize(nbLevels);
for (int i = 0; i < nbLevels; ++i) {
rectangles_[i].first.setWidth(pyramid.levels()[i].cols() - padx_);
rectangles_[i].first.setHeight(pyramid.levels()[i].rows() - pady_);
}
// Build the patchwork planes
const int nbPlanes = BLF(rectangles_);
// Constructs an empty patchwork in case of error
if (nbPlanes <= 0)
return;
planes_.resize(nbPlanes);
for (int i = 0; i < nbPlanes; ++i) {
planes_[i] = Plane::Constant(MaxRows_, HalfCols_, Cell::Zero());
Map<HOGPyramid::Level, Aligned>
plane(reinterpret_cast<HOGPyramid::Cell *>(planes_[i].data()), MaxRows_, HalfCols_ * 2);
// Set the last feature to 1
for (int y = 0; y < MaxRows_; ++y)
for (int x = 0; x < MaxCols_; ++x)
plane(y, x)(HOGPyramid::NbFeatures - 1) = 1.0f;
}
// Recopy the pyramid levels into the planes
for (int i = 0; i < nbLevels; ++i) {
Map<HOGPyramid::Level, Aligned>
plane(reinterpret_cast<HOGPyramid::Cell *>(planes_[rectangles_[i].second].data()),
MaxRows_, HalfCols_ * 2);
plane.block(rectangles_[i].first.y(), rectangles_[i].first.x(),
rectangles_[i].first.height(), rectangles_[i].first.width()) =
pyramid.levels()[i].topLeftCorner(rectangles_[i].first.height(),
rectangles_[i].first.width());
}
// Transform the planes
int i;
#pragma omp parallel for private(i)
for (i = 0; i < nbPlanes; ++i)
#ifndef FFLD_HOGPYRAMID_DOUBLE
fftwf_execute_dft_r2c(Forwards_, reinterpret_cast<float *>(planes_[i].data()->data()),
reinterpret_cast<fftwf_complex *>(planes_[i].data()->data()));
#else
fftw_execute_dft_r2c(Forwards_, reinterpret_cast<double *>(planes_[i].data()->data()),
reinterpret_cast<fftw_complex *>(planes_[i].data()->data()));
#endif
}
void Mixture::convolve(const HOGPyramid & pyramid, vector<HOGPyramid::Matrix> & scores,
vector<Indices> & argmaxes,
vector<vector<vector<Model::Positions> > > * positions) const
{
if(empty() || pyramid.empty()) {
scores.clear();
argmaxes.clear();
if(positions)
positions->clear();
return;
}
const int nbModels = models_.size();
const int nbLevels = pyramid.levels().size();
// Convolve with all the models
vector<vector<HOGPyramid::Matrix> > tmp(nbModels);
convolve(pyramid, tmp, positions);
// In case of error
if(tmp.empty()) {
scores.clear();
argmaxes.clear();
if(positions)
positions->clear();
return;
}
// Resize the scores and argmaxes
scores.resize(nbLevels);
argmaxes.resize(nbLevels);
int i;
#pragma omp parallel for private(i)
for(i = 0; i < nbLevels; ++i) {
scores[i].resize(pyramid.levels()[i].rows() - maxSize().first + 1,
pyramid.levels()[i].cols() - maxSize().second + 1);
argmaxes[i].resize(scores[i].rows(), scores[i].cols());
for(int y = 0; y < scores[i].rows(); ++y) {
for(int x = 0; x < scores[i].cols(); ++x) {
int argmax = 0;
for(int j = 1; j < nbModels; ++j)
if(tmp[j][i](y, x) > tmp[argmax][i](y, x))
argmax = j;
scores[i](y, x) = tmp[argmax][i](y, x);
argmaxes[i](y, x) = argmax;
}
}
}
}
void printHogSizes(HOGPyramid pyramid){
int nlevels = pyramid.levels().size();
for(int level = 0; level < nlevels; level++){
//const float* raw_hog = pyramid.levels()[level].data()->data();
int width = pyramid.levels()[level].cols();
int height = pyramid.levels()[level].rows();
int depth = pyramid.NbFeatures;
printf("level %d: width=%d, height=%d, depth=%d \n", level, width, height, depth);
}
}
// nRows = 32
// nCols = width*height
void writePyraToCsv(HOGPyramid pyramid){
int nlevels = pyramid.levels().size();
for(int level = 0; level < nlevels; level++){
//printf("writing to CSV: level %d \n", level);
const float* raw_hog = pyramid.levels()[level].data()->data(); int width = pyramid.levels()[level].cols();
int height = pyramid.levels()[level].rows();
int depth = pyramid.NbFeatures;
ostringstream fname;
fname << "../piggyHOG_results/level" << level << ".csv"; //TODO: get orig img name into the CSV name.
int nCols = depth; //one descriptor per row
int nRows = width*height;
//TODO: also write (depth, width, height) -- in some order -- to the top of the CSV file.
writeCsv_2dFloat(raw_hog, nRows, nCols, fname.str());
}
}