test-surprise.C

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00001 /*!@file Surprise/test-surprise.C test basic behavior of SurpriseMap and contents */
00002 
00003 // //////////////////////////////////////////////////////////////////// //
00004 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2000-2003   //
00005 // by the University of Southern California (USC) and the iLab at USC.  //
00006 // See http://iLab.usc.edu for information about this project.          //
00007 // //////////////////////////////////////////////////////////////////// //
00008 // Major portions of the iLab Neuromorphic Vision Toolkit are protected //
00009 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency //
00010 // in Visual Environments, and Applications'' by Christof Koch and      //
00011 // Laurent Itti, California Institute of Technology, 2001 (patent       //
00012 // pending; application number 09/912,225 filed July 23, 2001; see      //
00013 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status).     //
00014 // //////////////////////////////////////////////////////////////////// //
00015 // This file is part of the iLab Neuromorphic Vision C++ Toolkit.       //
00016 //                                                                      //
00017 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can   //
00018 // redistribute it and/or modify it under the terms of the GNU General  //
00019 // Public License as published by the Free Software Foundation; either  //
00020 // version 2 of the License, or (at your option) any later version.     //
00021 //                                                                      //
00022 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope  //
00023 // that it will be useful, but WITHOUT ANY WARRANTY; without even the   //
00024 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR      //
00025 // PURPOSE.  See the GNU General Public License for more details.       //
00026 //                                                                      //
00027 // You should have received a copy of the GNU General Public License    //
00028 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write   //
00029 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330,   //
00030 // Boston, MA 02111-1307 USA.                                           //
00031 // //////////////////////////////////////////////////////////////////// //
00032 //
00033 // Primary maintainer for this file: Laurent Itti <itti@usc.edu>
00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/Surprise/test-surprise.C $
00035 // $Id: test-surprise.C 6191 2006-02-01 23:56:12Z rjpeters $
00036 //
00037 
00038 #include "Image/MathOps.H"
00039 #include "Raster/Raster.H"
00040 #include "Surprise/SurpriseMap.H"
00041 
00042 #define QLEN       3
00043 #define UPDFAC     0.75
00044 #define NUPDFAC    0.75
00045 #define INIVAL     0.0
00046 #define VARIANCE   25.0
00047 #define NEIGHSIGMA 0.5f
00048 #define LOCSIGMA   3.0f
00049 #define NITER      20
00050 
00051 int main(const int argc, const char** argv)
00052 {
00053   if (argc != 2) LFATAL("USAGE: %s <image.pgm>", argv[0]);
00054 
00055   // let's start by trying out a single model: it starts with our
00056   // initial conditions and we give it a steady input of 255:
00057   SurpriseModelSP m(UPDFAC, INIVAL, VARIANCE);  // the model
00058   SurpriseModelSP s(UPDFAC, 255.0f, VARIANCE);  // the sample
00059   for (int i = 0; i < NITER; i ++)
00060     LINFO("iter = %d, mean = %f, stdev = %f, surprise = %f",
00061           i, m.getMean(), sqrt(m.getVar()), m.surprise(s));
00062 
00063   // get the input feature map:
00064   Image<byte> input = Raster::ReadGray(argv[1]);
00065 
00066   // convert to double:
00067   Image<double> in(input);
00068 
00069   // create sample variances:
00070   Image<double> invar(input.getDims(), NO_INIT);
00071   invar.clear(VARIANCE);
00072 
00073   // create SurpriseImage from our samples and their variances:
00074   SurpriseImage<SurpriseModelSP> sample(UPDFAC, in, invar);
00075 
00076   // create an ImageCache to accumulate our results:
00077   ImageCacheMinMax<float> cache;
00078 
00079   // create a surprise map:
00080   SurpriseMap<SurpriseModelSP> smap;
00081   smap.init(QLEN, UPDFAC, NUPDFAC, INIVAL, VARIANCE, NEIGHSIGMA, LOCSIGMA);
00082 
00083   // let's do it!
00084   for (int i = 0; i < NITER; i ++)
00085     {
00086       // get the surprise:
00087       Image<float> surp = smap.surprise(sample);
00088       float mi, ma; getMinMax(surp, mi, ma);
00089       LINFO("Done %d/%d: [%f .. %f]", i+1, NITER, mi, ma);
00090 
00091       // cache it:
00092       cache.push_back(surp);
00093     }
00094 
00095   // ok, let's save the results. First find the global max:
00096   Image<float> imax = cache.getMax();
00097   float mi, ma; getMinMax(imax, mi, ma);
00098   LINFO("Global max is %f", ma);
00099 
00100   for (int i = 0; i < NITER; i ++)
00101     {
00102       Image<byte> sav(cache.pop_front() * 255.0f / ma);
00103       Raster::WriteGray(sav, sformat("SURP%03d%s", i, argv[1]));
00104     }
00105 
00106   return 0;
00107 }
00108 
00109 // ######################################################################
00110 /* So things look consistent in everyone's emacs... */
00111 /* Local Variables: */
00112 /* indent-tabs-mode: nil */
00113 /* End: */
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