NICE_VisLearning/featureLearning/FeatureLearningClusterBased.h

/**
* @file FeatureLearningClusterBased.h
* @brief compute new histogram entries by clustering new features and take centers of clusters which are relevant and novel
* @author Alexander Freytag
* @date 16-04-2013 (dd-mm-yyyy)

*/
#ifndef _INCLUDEFEATURELEARNINGCLUSTERBASED
#define _INCLUDEFEATURELEARNINGCLUSTERBASED

#include "FeatureLearningGeneric.h"

#include <string>

#include <core/vector/Distance.h>
#include <core/vector/VVector.h>

#include <vislearning/cbaselib/MultiDataset.h>
#include <vislearning/features/localfeatures/GenericLocalFeatureSelection.h>
#include <vislearning/math/cluster/ClusterAlgorithm.h>

namespace OBJREC
{

  /** abstract interface for feature learning algorithms */
  class FeatureLearningClusterBased : public FeatureLearningGeneric
  {

    protected:
           
      bool showTrainingImages;
      
      //! define the initial number of clusters our codebook shall contain
      int initialNumberOfClusters;       
      //! define the number of clusters we want to compute for an unseen image
      int numberOfClustersForNewImage;      
  
      OBJREC::ClusterAlgorithm * clusterAlgo;
      NICE::VectorDistance<double> * distFunction;

      LocalFeatureRepresentation * featureExtractor;
      
      NICE::VVector prototypes;     
      
      bool showResults;
      std::string resultdir;
      
      int newImageCounter;
      //just needed for visualisation
      double oldMaxDist;
      //TODO stupid!!!
      double maxValForVisualization;
            
      /************************
       * 
       *   protected methods
       * 
       **************************/
      
      void setClusterAlgo( const std::string & _clusterAlgoString, const bool & _setForInitialTraining);
      
      void extractFeaturesFromTrainingImages(  const OBJREC::MultiDataset *_md,  NICE::VVector & examplesTraining  );
      
      void train ( const OBJREC::MultiDataset *_md ); 
      
      virtual bool loadInitialCodebook ( );
      virtual bool writeInitialCodebook ( );
      
      


    public:

      /** constructor
        *  @param conf needs a configfile
        *  @param md and a MultiDataset (contains images and other things)
        */
      FeatureLearningClusterBased ( const NICE::Config *_conf, const OBJREC::MultiDataset *_md , const std::string & _section = "featureLearning");

      /** simple destructor */
      virtual ~FeatureLearningClusterBased();
      
      /** this function has to be overloaded by all subclasses
          @param imgWithNovelContent 
      */
      virtual void learnNewFeatures ( const std::string & filename ) ;
      
      virtual NICE::FloatImage evaluateCurrentCodebook ( const std::string & filename , const bool & beforeComputingNewFeatures = true );
      

  };


} // namespace

#endif