NICE_VisLearning/features/localfeatures/LFReadCache.tcc

/** 
* @file LFReadCache.tcc
* @author Erik Rodner
* @date 02/14/2008

*/
#include "core/vector/VectorT.h"
#include "core/vector/MatrixT.h"
#include "core/image/ImageT.h"

#include <iostream>
#include <fstream>

#include "vislearning/features/localfeatures/LFReadCache.h"

#include "vislearning/baselib/Globals.h"
#include "core/basics/StringTools.h"
#include "core/basics/FileMgt.h"
#include "core/vector/VVector.h"

namespace OBJREC {

template <class ImageClass>
int LFReadCache::extractFeaturesTemplate ( const ImageClass & img, 
		  NICE::VVector & features, 
		  NICE::VVector & positions) const
{
    std::string filename = Globals::getCacheFilename ( cachedir, cachemode );
    std::string filename_desc = filename + ".desc";
    std::string filename_pos = filename + ".key";

    int ret = 0;

    if ( ! NICE::FileMgt::fileExists ( filename_desc ) ||
	 ! NICE::FileMgt::fileExists ( filename_pos ) )
    {
		fprintf (stderr, "LFReadCache::extractFeatures: recovering data (%s,%s not found)\n", filename_desc.c_str(),
			filename_pos.c_str());
		if ( lfrep == NULL )
			fthrow(Exception, "LocalFeatureRepresentation not available, recovering is impossible!");

		lfrep->extractFeatures ( img, features, positions );

		features.save ( filename_desc, descFormat );
		positions.save ( filename_pos, NICE::VVector::FILEFORMAT_LINE );
    } else {
		if ( (descFormat == NICE::VVector::FILEFORMAT_BINARY_DOUBLE) || (descFormat == NICE::VVector::FILEFORMAT_BINARY_CHAR) )
		{
			if ( lfrep == NULL ) {
				fthrow(Exception, "Raw binary format needs a LocalFeatureRepresentation as prototype");
			} else {
				features.setBufSize(lfrep->getDescSize());
			}
		}

		features.read( filename_desc, descFormat );
		positions.read ( filename_pos, NICE::VVector::FILEFORMAT_LINE );

		if ( positions.size() != features.size() )
		{
			std::cerr << "LFReadCache::extractFeatures: format error ! positions.size=" << positions.size() <<
			" features.size()=" << features.size() << std::endl;
			std::cerr << "features: " << filename_desc << std::endl;
			std::cerr << "positions: " << filename_pos << std::endl;
			exit(-1);
		}

		if ( (numFeatures >= 0) && (features.size() > (size_t)numFeatures) ) {
			size_t n = features.size() - numFeatures; // >= 1
			fprintf (stderr, "LFReadCache: number of local features is restricted: localfeature_count %d, real %d\n",
			numFeatures, (int)features.size() );

			if ( n > (size_t)numFeatures ) {
				NICE::VVector nf;
				NICE::VVector np;
				for ( size_t l = 0 ; l < (size_t)numFeatures ; l++ )
				{
					size_t i = rand() % features.size();
					nf.push_back ( features[i] );
					np.push_back ( positions[i] );
					features.erase ( features.begin() + i );
					positions.erase ( positions.begin() + i );
				}
				positions = np;
				features = nf;
			} else {
				for ( size_t l = 0 ; l < n ; l++ )
				{
					size_t i = rand() % features.size();
					features.erase ( features.begin() + i );
					positions.erase ( positions.begin() + i );
				}
			}
		}
    }


    return ret;
}

}