NICE_VisLearning/features/localfeatures/LocalFeatureRGBSift.cpp

#include "objrec/features/localfeatures/LocalFeatureRGBSift.h"

using namespace OBJREC;
using namespace std;
using namespace NICE;


LocalFeatureRGBSift::LocalFeatureRGBSift (const Config *conf) : LocalFeatureSift (conf)
{
  deletemode = false;
}

LocalFeatureRGBSift::~LocalFeatureRGBSift()
{

}

int 
LocalFeatureRGBSift::getDescriptors (const NICE::ColorImage & img, VVector & positions, VVector & descriptors) const
{
	sortPositions (positions);
	descriptors.clear();
	for (int i = 0; i < (int) positions.size(); i++) 
	{
		NICE::Vector v;
		descriptors.push_back (v);
	}

	vector<VVector> desc (3);

#ifdef NICE_USELIB_OPENMP
	// check whether siftGPU should be used
	int numberOfCPU = omp_get_num_procs();
	int numberOfThreads = 0;
	if (isGpuUsed()) 
	{ 
		// in case of siftGPU it is possible to use one device
		numberOfThreads = 1;
		clog << "[log] LocalFeatureRGBSift: no multithreading" << endl;
	}
	else 
	{
		// in case of siftpp it is possible to use all given cores
		numberOfThreads = numberOfCPU;
		clog << "[log] LocalFeatureRGBSift: multithreading with (max) " << numberOfCPU << " threads" << endl;
	}
#endif

#pragma omp parallel for num_threads(numberOfThreads)
  for (int i = 0; i < 3; i++) {
    NICE::Image tmp (img.width(), img.height());

    for (int y = 0; y < img.height(); y++) {
      for (int x = 0; x < img.width(); x++) {
        tmp.setPixel (x, y, img.getPixel (x, y, i));
      }
    }
    VVector pos = positions;
    computeDesc (tmp, pos, desc[i]);
  }

  for (int i = 0; i < 3; i++) {
    assert (desc[i].size() == descriptors.size());

    if (i == 0) {
#pragma omp parallel for num_threads( numberOfCPU )
      for (int j = 0; j < (int) desc[i].size(); j++) {
        descriptors[j] = desc[i][j];
      }
    }
    else {
#pragma omp parallel for num_threads( numberOfCPU )
      for (int j = 0; j < (int) desc[i].size(); j++) {
        descriptors[j].append (desc[i][j]);
      }
    }
  }

  return positions.size();
}