108 lines
2.8 KiB
Mathematica
108 lines
2.8 KiB
Mathematica
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donnees;
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% Param<EFBFBD>tres de la m<EFBFBD>thode de segmentation :
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T_0 = 1.0;
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alpha = 0.99;
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q_max = 50;
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beta = 2.0;
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% Estimation des param<EFBFBD>tres des N classes :
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N = 4;
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nb_tirages = 100000;
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[moyennes, variances, poids] = estimation_non_super(I, N, nb_tirages);
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% trac<EFBFBD>/calcul des histogrammes :
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[fxi, x] = ksdensity(I(:), 1:255);
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fxe = sum(poids ./ sqrt(2 * pi * variances) .* exp(- (x - moyennes).^2 ./ variances / 2));
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figure;
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plot(x, fxi);
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hold on;
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plot(x, fxe);
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legend(["image", "MAP"])
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export_fig(gcf, "saves/exo2hist_" + num2str(N) + "N_" + num2str(beta) + "B_" + num2str(alpha) + "A" + ".png", '-png', '-painters', '-m2');
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% Permutation des classes pour pouvoir calculer le pourcentage de bonnes classifications :
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[~, indices] = sort(moyennes, 'ascend');
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moyennes = moyennes(indices);
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variances = variances(indices);
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couleurs_classes = couleurs_classes(indices, :);
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% Calcul de l'attache aux donn<EFBFBD>es (vraisemblance) :
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AD = attache_donnees(I, moyennes, variances);
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% Initialisation des classes :
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couleurs_pixels = zeros(nb_lignes, nb_colonnes, 3);
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[U, k] = min(AD, [], 3);
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for i = 1:nb_lignes
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for j = 1:nb_colonnes
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couleurs_pixels(i, j, :) = couleurs_classes(k(i, j), :);
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end
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end
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% close all;
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figure;
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% subplot(1,2,2);
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imagesc(couleurs_pixels);
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axis equal;
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axis off;
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[fimage, map] = rgb2ind(couleurs_pixels, 256);
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imwrite(fimage, map, "saves/exo2mv.png");
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% title(['Maximum de vraisemblance'],'FontSize',20);
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% fprintf('Tapez un caractere pour lancer le recuit simule\n');
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% pause;
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% Calcul de l'<EFBFBD>nergie initiale :
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for i = 1:nb_lignes
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for j = 1:nb_colonnes
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U(i, j) = U(i, j) + beta * regularisation(i, j, k, k(i, j));
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end
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end
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% Minimisation de l'<EFBFBD>nergie par recuit simul<EFBFBD> :
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temps_affichage = 0.05;
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T = T_0;
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for q = 1:q_max
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% Boucle du recuit simul<EFBFBD> :
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[U, k] = recuit_simule(U, k, AD, T, beta);
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% Mise <EFBFBD> jour de l'affichage :
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for i = 1:nb_lignes
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for j = 1:nb_colonnes
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couleurs_pixels(i, j, :) = couleurs_classes(k(i, j), :);
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end
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end
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imagesc(couleurs_pixels);
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axis equal;
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axis off;
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title([num2str(q) + "/" + num2str(q_max) + ", " + num2str(N) + "N, " + num2str(beta) + "B, " + num2str(alpha) + "A"]);
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pause(temps_affichage);
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if q == 1
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delete("saves/recuit_MAP_" + num2str(N) + "N_" + num2str(beta) + "B_" + num2str(alpha) + "A" + ".gif")
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end
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export_fig(gcf, "saves/recuit_MAP_" + num2str(N) + "N_" + num2str(beta) + "B_" + num2str(alpha) + "A" + ".gif", '-png', '-painters', '-m2', '-append');
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% Mise <EFBFBD> jour de la temp<EFBFBD>rature :
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T = alpha * T;
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end
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% Calcul du pourcentage de pixels correctement class<EFBFBD>s :
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pixels_correctement_classes = find(k == k_exact);
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nb_pixels = nb_lignes * nb_colonnes;
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fprintf('Pixels correctement classes : %.2f %%\n', 100 * length(pixels_correctement_classes(:)) / nb_pixels);
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