HmaxFL.H

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/*!@file HMAX/HmaxFL.H Modified from T. Serre's HMAX model with feature learning  */

// //////////////////////////////////////////////////////////////////// //
// The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2001 by the //
// University of Southern California (USC) and the iLab at USC.         //
// See http://iLab.usc.edu for information about this project.          //
// //////////////////////////////////////////////////////////////////// //
// Major portions of the iLab Neuromorphic Vision Toolkit are protected //
// under the U.S. patent ``Computation of Intrinsic Perceptual Saliency //
// in Visual Environments, and Applications'' by Christof Koch and      //
// Laurent Itti, California Institute of Technology, 2001 (patent       //
// pending; application number 09/912,225 filed July 23, 2001; see      //
// http://pair.uspto.gov/cgi-bin/final/home.pl for current status).     //
// //////////////////////////////////////////////////////////////////// //
// This file is part of the iLab Neuromorphic Vision C++ Toolkit.       //
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// The iLab Neuromorphic Vision C++ Toolkit is free software; you can   //
// redistribute it and/or modify it under the terms of the GNU General  //
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// The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope  //
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// //////////////////////////////////////////////////////////////////// //
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// Primary maintainer for this file: Laurent Itti <itti@usc.edu>
// $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/HMAX/HmaxFL.H $
// $Id: HmaxFL.H 14139 2010-10-16 02:11:21Z dparks $
//

#ifndef HMAXFL_H_DEFINED
#define HMAXFL_H_DEFINED

#include "Image/Image.H"
#include "HMAX/Hmax.H"
#include <vector>

#include <cmath>
#include <string>
#include <vector>
#include <dirent.h>

#define C1_PATCH_FILE_NAME "C1Patches"

//! Object recognition model inspired from Riesenhuber & Poggio's HMAX model
/*! See Riesenhuber & Poggio, Nature Neuroscience, 1999.
 */

class HmaxFL : public Hmax {
public:
  //! Default constructor. Need to call init() later.
  HmaxFL();

  //! Constructor
  HmaxFL(const int nori, const std::vector<int>& spacess,
         const std::vector<int>& scaless, const int c1spaceol = 2,
         const bool angleflag = true, const float s2t = 1.0F,
         const float s2s = 1.0F, const float gamma = 0.3F, const float divstart = 4.05F,
         const float divstep = -0.05F, const int fsmin = 5, const int fsstep = 2);

  //! Initialization
  void init(const int nori, const std::vector<int>& spacess,
            const std::vector<int>& scaless, const int c1spaceol = 2,
            const bool angleflag = true, const float s2t = 1.0F,
            const float s2s = 1.0F, const float gamma = 0.3F, const float divstart = 4.05F,
            const float divstep = -0.05F, const int fsmin = 5, const int fsstep = 2);

  void initFilters(const float gamma, const float divstart, const float divstep, const int fsmin , const int fsstep);

  //! Free internal memory
  void freeMem();
  void freeC1Patches();

  //! Destructor
  ~HmaxFL();

  //! Compute C2 responses from an input image
  void getC2(const Image<float>& input, float**& c2Res);

  //! Randomly extract a set of C1Patches from positive training images
  void extractRandC1Patch(std::string dirname, Image<float> & image, int index, std::vector<int> patchSizes);
  void extractRandC1Patches(std::string dirname, Image<float> *& posTrainingImages, int numPosTrainImages, std::vector<int> patchSizes, int nPatchesPerSize);

  //! Set the c1patches that should be used
  void setC1Patches(Image<float>***&patches,std::vector<int> patchSizes,int numPatchesPerSize);
  void readInC1Patches(std::string fileName);
  void writeOutC1Patch(std::string dirName, Image<float>& patch, int i, int j,int k);
  void writeOutC1Patches(std::string dirName);
  std::vector<int> getC1PatchSizes();
  int getC1PatchesPerSize();

  //! Get the c1patches that are being used
  Image<float>***& getC1Patches();

  //! Calculate the distance from a patch to an image
  void windowedPatchDistance(Image <float>*& images, int nimages, Image <float> * &patches, int npatches, Image<float>& D);


protected:
  int nswb; //!< number of scales within a scale band
  Image<float> ***c1Patches; //!< patches that should be compared in S2 activation c1Patches[patchSizes][patchesPerSize]
  std::vector<int> c1PatchSizes; //!< Number of square patch sizes of c1Patches
  int nC1PatchesPerSize; //!< Number of patches per patch size of c1Patches
};

#endif

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