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: */