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67 lines
1.4 KiB
67 lines
1.4 KiB
%% Initialization
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clear
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clear all
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% For reproducibility
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rng(1);
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load('dip_hw_2.mat');
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%% Produces the affinity graphs for both images
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graph1 = Image2Graph(d2a);
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graph2 = Image2Graph(d2b);
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%% Executes recursive experiments for the first image
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figure();
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imshow(d2a);
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clusters = recursiveNCuts(graph1);
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% Presents results
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clusters = reshape(clusters, size(d2a, 1), []);
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clustersR = clusters;
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clustersG = clusters;
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clustersB = clusters;
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for cluster = 1:size(unique(clusters), 1)
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clustersR(clusters == cluster) = rand;
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clustersG(clusters == cluster) = rand;
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clustersB(clusters == cluster) = rand;
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end
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clusters(:, :, 1) = clustersR;
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clusters(:, :, 2) = clustersG;
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clusters(:, :, 3) = clustersB;
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figure();
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imshow(clusters);
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clearvars clustersR clustersG clustersB cluster
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%% Executes recursive experiments for the second image
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figure();
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imshow(d2b);
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clusters = recursiveNCuts(graph2);
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% Presents results
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clusters = reshape(clusters, size(d2b, 1), []);
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figure();
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imshow(meanClustersColorRGB(d2b, clusters));
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clustersR = clusters;
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clustersG = clusters;
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clustersB = clusters;
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for cluster = 1:size(unique(clusters), 1)
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clustersR(clusters == cluster) = rand;
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clustersG(clusters == cluster) = rand;
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clustersB(clusters == cluster) = rand;
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end
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clusters(:, :, 1) = clustersR;
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clusters(:, :, 2) = clustersG;
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clusters(:, :, 3) = clustersB;
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figure();
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imshow(clusters);
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clearvars clustersR clustersG clustersB cluster
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