// STL includes #include #include #include // nice-vislearning includes #include "vislearning/baselib/ColorSpace.h" #include "vislearning/features/localfeatures/LocalFeatureColorWeijer.h" using namespace OBJREC; using namespace std; using namespace NICE; //! color representation for visualization const int colors[11][3] = { {0, 0, 0}, // black {0, 0, 255}, // blue {165, 42, 42}, // brown {190, 190, 190}, // grey { 0, 255, 0}, // green {255, 165, 0}, // orange {255, 192, 203}, // pink {160, 32, 240}, // purple {255, 0, 0}, // red {255, 255, 255}, // white {255, 255, 0}, // yellow }; LocalFeatureColorWeijer::LocalFeatureColorWeijer( const Config *c ) { conf = c; tfile = conf->gS( "LocalFeatureColorWeijer", "table", "/home/dbv/bilder/colorWeijer/w2c.txt"); restore(); } LocalFeatureColorWeijer::~LocalFeatureColorWeijer() { } int LocalFeatureColorWeijer::getDescSize() const { return LASTCOLOR; } void LocalFeatureColorWeijer::restore() { ifstream fin( tfile.c_str() ); if(!fin.is_open()) { fthrow(Exception,"ColorWeijer: could not find lookup table file."); } while(!fin.eof()) { double rd,gd,bd; int r,g,b; fin >> rd; fin >> gd; fin >> bd; r = rd/8; g = gd/8; b = bd/8; for(int i = 0; i < 11; i++) { fin >> hist[r][g][b][i]; } } /* for(int r = 0; r < 32; r++) { for(int g = 0; g < 32; g++) { for(int b = 0; b < 32; b++) { for(int i = 0; i < 11; i++) { fin >> hist[r][g][b][i]; } } } } */ } int LocalFeatureColorWeijer::getDescriptors( const NICE::Image & img, VVector & positions, VVector & features ) const { throw NICE::Exception ( "LocalFeatureColorWeijer extracts COLOR Features, it won't work on gray value images"); } int LocalFeatureColorWeijer::getDescriptors( const NICE::ColorImage & img, VVector & positions, VVector & features ) const { int width = ( int )img.width(); int height = ( int )img.height(); for ( int j = 0; j < ( int )positions.size(); j++ ) { int x = positions[j][0]; int y = positions[j][1]; int r = img(x,y,0)/8; int g = img(x,y,1)/8; int b = img(x,y,2)/8; Vector feat( 11 ); for ( uint i = 0; i < 11; i++ ) { feat[i] = hist[r][g][b][i]; } features.push_back( feat ); } return 1; } void LocalFeatureColorWeijer::visualizeFeatures( NICE::Image & mark, const VVector & positions, size_t color ) const { } int LocalFeatureColorWeijer::findColor( string &fn ) { if ( fn.find( "black" ) != string::npos ) return BLACK; if ( fn.find( "blue" ) != string::npos ) return BLUE; if ( fn.find( "brown" ) != string::npos ) return BROWN; if ( fn.find( "grey" ) != string::npos ) return GREY; if ( fn.find( "green" ) != string::npos ) return GREEN; if ( fn.find( "orange" ) != string::npos ) return ORANGE; if ( fn.find( "pink" ) != string::npos ) return PINK; if ( fn.find( "purple" ) != string::npos ) return PURPLE; if ( fn.find( "red" ) != string::npos ) return RED; if ( fn.find( "white" ) != string::npos ) return WHITE; if ( fn.find( "yellow" ) != string::npos ) return YELLOW; return -1; } void LocalFeatureColorWeijer::visualizeFeatures( NICE::ColorImage & out, const VVector & features, const VVector & position ) const { for ( int i = 0; i < ( int )position.size(); i++ ) { int maxpos = 0; double maxval = 0.0; for ( int j = 0; j < ( int )features[i].size(); j++ ) { if ( maxval < features[i][j] ) { maxval = features[i][j]; maxpos = j; } } out.setPixel( position[i][0], position[i][1], colors[maxpos][0], colors[maxpos][1], colors[maxpos][2] ); } } void LocalFeatureColorWeijer::visualizeFeatures( const NICE::ColorImage & cimg ) const { ColorImage out; visualizeFeatures( cimg, out ); } void LocalFeatureColorWeijer::visualizeFeatures( const NICE::ColorImage & cimg, NICE::ColorImage &out ) const { VVector pos, feats; for ( int y = 0; y < cimg.height(); y++ ) { for ( int x = 0; x < cimg.width(); x++ ) { Vector vec( 2 ); vec[0] = x; vec[1] = y; pos.push_back( vec ); } } getDescriptors( cimg, pos, feats ); //heatmap for a special class /*ofstream fout("out.txt"); int counter = 0; for ( int y = 0; y < cimg.height(); y++ ) { for ( int x = 0; x < cimg.width(); x++, counter++ ) { fout << feats[counter][8] << " "; } } cout << "counter: " << counter << " feats.size(): " << feats.size() << endl; fout.close();*/ out.resize( cimg.width(), cimg.height() ); out.set( 0, 0, 0 ); visualizeFeatures( out, feats, pos ); ColorImage combinedout( cimg.width()*2, cimg.height() ); int width = ( int )cimg.width(); for ( int y = 0; y < ( int )cimg.height(); y++ ) { for ( int x = 0; x < width; x++ ) { combinedout.setPixel( x, y, cimg.getPixel( x, y, 0 ), cimg.getPixel( x, y, 1 ), cimg.getPixel( x, y, 2 ) ); combinedout.setPixel( x + width, y, out.getPixel( x, y, 0 ), out.getPixel( x, y, 1 ), out.getPixel( x, y, 2 ) ); } } showImage( combinedout, "result" ); } void LocalFeatureColorWeijer::getFeats( const ColorImage &img, MultiChannelImageT &feats ) { int width = ( int )img.width(); int height = ( int )img.height(); feats.reInit( width, height, 11); for ( int y = 0; y < height; y++ ) { for ( int x = 0; x < width; x++ ) { int r = img(x,y,0)/8; int g = img(x,y,1)/8; int b = img(x,y,2)/8; for ( uint i = 0; i < 11; i++ ) { feats.set( x, y, hist[r][g][b][i], i ); } } } return; }