test-GeomHash.C

00001 /*! @file SceneUnderstanding/test-GeomHash */
00002 
00003 // //////////////////////////////////////////////////////////////////// //
00004 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2000-2005   //
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: Lior Elazary <elazary@usc.edu>
00034 // $HeadURL: svn://isvn.usc.edu/software/invt/trunk/saliency/src/FeatureMatching/test-GeomHash.C $
00035 // $Id: test-GeomHash.C 12962 2010-03-06 02:13:53Z irock $
00036 //
00037 
00038 #include "FeatureMatching/GeometricHashing.H"
00039 #include "Image/Point2D.H"
00040 #include "GUI/DebugWin.H"
00041 #include "Util/MathFunctions.H"
00042 
00043 #include <signal.h>
00044 #include <sys/types.h>
00045 
00046 void drawInput(std::vector<Point2D<float> >& input,
00047     std::vector<Point2D<float> >& model)
00048 {
00049   float binWidth = 20;
00050   Image<PixRGB<byte> > img(int(32*binWidth), int(32*binWidth), ZEROS);
00051   drawGrid(img, (int)binWidth, (int)binWidth, 1, 1, PixRGB<byte>(0,0,255));
00052   drawLine(img, Point2D<int>(0, img.getHeight()/2),
00053                 Point2D<int>(img.getWidth(), img.getHeight()/2),
00054                 PixRGB<byte>(0,0,255),2);
00055   drawLine(img, Point2D<int>(img.getWidth()/2, 0),
00056                 Point2D<int>(img.getWidth()/2, img.getHeight()),
00057                 PixRGB<byte>(0,0,255),2);
00058 
00059   //draw the Input
00060   float scale = 20;
00061   for(uint i=0; i<input.size(); i++)
00062   {
00063     int x = (img.getWidth()/2) + (int)(scale*input[i].i);
00064     int y = (img.getHeight()/2) - (int)(scale*input[i].j);
00065     drawCircle(img, Point2D<int>(x,y), 3, PixRGB<byte>(255,0,0));
00066   }
00067 
00068   //draw the Model
00069   for(uint i=0; i<model.size(); i++)
00070   {
00071     int x = (img.getWidth()/2) + (int)(scale*model[i].i);
00072     int y = (img.getHeight()/2) - (int)(scale*model[i].j);
00073     drawCircle(img, Point2D<int>(x,y), 5, PixRGB<byte>(0,255,0));
00074   }
00075 
00076   SHOWIMG(img);
00077 }
00078 int main(const int argc, const char **argv)
00079 {
00080 
00081   GeometricHashing gHash;
00082 
00083   GeometricHashing::Model model;
00084 
00085   //model.v.push_back(Point2D<float>(5+2,2+3.464102));
00086   //model.v.push_back(Point2D<float>(5+7.556922, 2+3.488973));
00087   //model.v.push_back(Point2D<float>(5+-1.110512, 2+6.876537));
00088   //model.v.push_back(Point2D<float>(5+-2.000000, 2+-3.464102));
00089   //model.v.push_back(Point2D<float>(5+6.022947, 2+-1.167949));
00090 
00091   //std::vector<Point2D<float> > input;
00092   //input.push_back(Point2D<float>(1, 7));
00093   //input.push_back(Point2D<float>(9, 6));
00094   //input.push_back(Point2D<float>(1+2,1+3.464102));
00095   //input.push_back(Point2D<float>(1+7.556922, 1+3.488973));
00096   //input.push_back(Point2D<float>(1+-1.110512, 1+6.876537));
00097   //input.push_back(Point2D<float>(1+-2.000000, 1+-3.464102));
00098   //input.push_back(Point2D<float>(1+6.022947, 1+-1.167949));
00099   //input.push_back(Point2D<float>(1+1.022947, 1+-3.167949));
00100   //input.push_back(Point2D<float>(1+2.022947, 1+-2.167949));
00101   //input.push_back(Point2D<float>(1+3.022947, 1+-7.167949));
00102   //input.push_back(Point2D<float>(-1.022947, -3.167949));
00103   //input.push_back(Point2D<float>(-2.022947, -2.167949));
00104   //
00105   //gHash.addModel(model);
00106   //Image<PixRGB<byte> > img = gHash.getHashTableImage();
00107   //LINFO("Show Hash table\n");
00108   ////SHOWIMG(img);
00109 
00110   //LINFO("Show Input");
00111   //std::vector<Point2D<float> > modelF;
00112   ////drawInput(input, modelF);
00113 
00114   ////Find the model in the input
00115   //std::vector<GeometricHashing::Acc> acc = gHash.getVotes(input);
00116   //if (acc.size() > 0)
00117   //{
00118   //  //Find the max
00119   //  GeometricHashing::Acc maxAcc = acc[0];
00120   //  for(uint i=1; i<acc.size(); i++)
00121   //    if (acc[i].votes > maxAcc.votes)
00122   //      maxAcc = acc[i];
00123 
00124   //  LINFO("Found model at: %i %i %i %i (%i %i)\n",
00125   //      maxAcc.P1, maxAcc.P2, maxAcc.modelId, maxAcc.votes,
00126   //      maxAcc.inputP1, maxAcc.inputP2);
00127 
00128   //  //Change the basis of the model to find the input
00129   //  Point2D<float> p1 = input[maxAcc.inputP1]; //Get the input basis
00130   //  Point2D<float> p2 = input[maxAcc.inputP2]; //Get the input basis
00131 
00132   //  //Find the transformation
00133   //  float modelScale = sqrt( squareOf(p2.i - p1.i) + squareOf(p2.j - p1.j) );
00134   //  float ang = atan((p2.j - p1.j)/(p2.i - p1.i));
00135   //  Point2D<float> center(p1.i+(p2.i - p1.i)/2, p1.j+(p2.j - p1.j)/2);
00136   //
00137   //  //Change the basis of the model to the basis that we found
00138   //  modelF = gHash.changeBasis(model.v, maxAcc.P1, maxAcc.P2);
00139 
00140   //  //Change the basis of the mode to the input
00141   //  for(uint i=0; i<modelF.size(); i++)
00142   //  {
00143   //    float x = modelScale*(modelF[i].i);
00144   //    float y = modelScale*(modelF[i].j);
00145   //    modelF[i] = Point2D<float>((x * cos(ang) - y * sin(ang)),
00146   //          (y * cos(ang) + x * sin(ang)));
00147   //  }
00148   //  for(uint i=0; i<modelF.size(); i++)
00149   //    modelF[i] += center;
00150 
00151   //  drawInput(input, modelF);
00152   //}
00153 
00154 
00155   return 0;
00156 }
00157 
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