TP-modelisation-images/super_pixel.m

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function [germes, img_labelise, E] = super_pixel(img, K, m, n, seuil_E, q_max)
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img = im2double(img);
width = size(img, 1);
height = size(img, 2);
N = width * height;
% création des germes
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S = sqrt(N / K);
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X = S / 2:S:width;
Y = S / 2:S:height;
germes = zeros(length(X) * length(Y), 5);
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c = 1;
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for x = X
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for y = Y
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germes(c, :) = [x y 0 0 0];
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c = c + 1;
end
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end
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% affichage des germes
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scatter(germes(:, 2), germes(:, 1), 'g.');
drawnow nocallbacks
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c = 1;
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% intialisation des germes (petit déplacement, pour ne pas se trouver sur un contour)
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for germe = germes'
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x = germe(1);
y = germe(2);
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xmin = floor(max(x - n, 1));
interval_x = xmin:min(x + n, width);
ymin = floor(max(y - n, 1));
interval_y = ymin:min(y + n, height);
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Gmag = imgradient(img(interval_x, interval_y));
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[~, ind_min] = min(Gmag(:));
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[nr, nc] = ind2sub(size(Gmag), ind_min);
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x = xmin + nr - 1;
y = ymin + nc - 1;
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germes(c, :) = [x y img(x, y, 1) img(x, y, 2) img(x, y, 3)];
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c = c + 1;
end
% affichage des germes
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scatter(germes(:, 2), germes(:, 1), 'r.');
drawnow nocallbacks
% création de l'image labelisée par les germes
img_labelise = zeros(width, height);
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% mélange mélange mélange
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germes = germes(randperm(length(germes)), :);
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% boucle princiaple
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for q = 1:q_max
for x = 1:width
for y = 1:height
% initialisation des minimums
min_Ds = 1e5;
for index_germe = 1:length(germes)
germe = germes(index_germe, :);
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% on récupère les coordonnées du germe
xg = germe(1);
yg = germe(2);
% on calcule la distance spatiale entre le germe et le pixel
Dxy = norm([x - xg y - yg]);
% si le germe est trop loin on skip
if Dxy > S
continue;
end
% on récupère les couleurs du germe
rg = germe(3);
gg = germe(4);
bg = germe(5);
% on récupère les couleurs du pixel
r = img(x, y, 1);
g = img(x, y, 2);
b = img(x, y, 3);
% on calcule la distance chromatique entre le germe et le pixel
Dlab = norm([r - rg g - gg b - bg]);
% on calcule Ds
Ds = Dlab + m / S * Dxy;
% Si Ds est meilleur on le prend
if Ds < min_Ds
img_labelise(x, y) = index_germe;
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min_Ds = Ds;
end
end
end
end
% affichage des labels
image(img_labelise * 255 / length(germes));
colormap hsv;
drawnow nocallbacks
old_germes = germes;
% kmeans, déplacement des germes par rapport à leurs pixels associés
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for index_germe = 1:length(germes)
truc = img_labelise == index_germe;
truc_rgb = reshape(img(repmat(truc, [1 1 3])), [], 3);
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m_rgb = mean(truc_rgb);
mx = 0;
my = 0;
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for i = find(truc == 1)'
[x, y] = ind2sub(size(img), i);
mx = mx + x;
my = my + y;
end
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mx = mx / sum(truc, 'all');
my = my / sum(truc, 'all');
germes(index_germe, :) = [mx my m_rgb];
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end
% affichage des germes
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scatter(germes(:, 2), germes(:, 1), 'w.');
drawnow nocallbacks
% calcul de l'erreur résiduel
E = norm(old_germes(:, 1:2) - germes(:, 1:2));
% si notre erreur est inférieur au seuil, on stop l'algo
if E < seuil_E
break
end
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end
end