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85 lines
2.2 KiB
C++
85 lines
2.2 KiB
C++
/*Authors
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* Manuela Chessa, Fabio Solari, Fabio Tatti, Silvio P. Sabatini
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*
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* manuela.chessa@unige.it, fabio.solari@unige.it
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*
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* PSPC-lab - University of Genoa
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*/
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#include "opencv2/contrib.hpp"
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#include "opencv2/highgui.hpp"
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#include <iostream>
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#include <cmath>
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using namespace cv;
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using namespace std;
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static void help()
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{
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cout << "LogPolar Blind Spot Model sample.\nShortcuts:"
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"\n\tn for nearest pixel technique"
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"\n\tb for bilinear interpolation technique"
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"\n\to for overlapping circular receptive fields"
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"\n\ta for adjacent receptive fields"
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"\n\tq or ESC quit\n";
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}
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int main(int argc, char** argv)
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{
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Mat img = imread(argc > 1 ? argv[1] : "lena.jpg",1); // open the image
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if(img.empty()) // check if we succeeded
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{
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cout << "can not load image\n";
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return 0;
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}
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help();
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Size s=img.size();
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int w=s.width, h=s.height;
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int ro0=3; //radius of the blind spot
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int R=120; //number of rings
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//Creation of the four different objects that implement the four log-polar transformations
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//Off-line computation
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Point2i center(w/2,h/2);
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LogPolar_Interp nearest(w, h, center, R, ro0, INTER_NEAREST);
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LogPolar_Interp bilin(w,h, center,R,ro0);
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LogPolar_Overlapping overlap(w,h,center,R,ro0);
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LogPolar_Adjacent adj(w,h,center,R,ro0,0.25);
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namedWindow("Cartesian",1);
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namedWindow("retinal",1);
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namedWindow("cortical",1);
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int wk='n';
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Mat Cortical, Retinal;
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//On-line computation
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for(;;)
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{
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if(wk=='n'){
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Cortical=nearest.to_cortical(img);
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Retinal=nearest.to_cartesian(Cortical);
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}else if (wk=='b'){
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Cortical=bilin.to_cortical(img);
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Retinal=bilin.to_cartesian(Cortical);
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}else if (wk=='o'){
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Cortical=overlap.to_cortical(img);
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Retinal=overlap.to_cartesian(Cortical);
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}else if (wk=='a'){
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Cortical=adj.to_cortical(img);
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Retinal=adj.to_cartesian(Cortical);
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}
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imshow("Cartesian", img);
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imshow("cortical", Cortical);
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imshow("retinal", Retinal);
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int c=waitKey(15);
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if (c>0) wk=c;
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if(wk =='q' || (wk & 255) == 27) break;
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}
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return 0;
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}
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