Image segmentation using k-means - python-2.7

Question

I 'm trying to use k-means algorithm for an image segmentation task . The problem is that my program does not segment the image.
Would you please help me to find the error in my code ?
In fact , I have fixed the number of clusters to 32.
I have used the following data structures:
3 arrays bleu,vert,rouge to store RGB values for each pixel
3 arrays cluster_bleu,cluster_rouge,cluster_vert to store RGB value for each cluster
groupe[i,0]=k maps each pixel i to cluster k
import cv2
import numpy
import random
def main():
MAX_LARGEUR = 400
MAX_HAUTEUR = 400
K = 32 #Le fameux parametre K de l'algorithme
imagecolor = cv2.imread('perr.jpg')
if imagecolor.shape[0] > MAX_LARGEUR or imagecolor.shape[1] > MAX_HAUTEUR:
factor1 = float(MAX_LARGEUR) / imagecolor.shape[0]
factor2 = float(MAX_HAUTEUR) / imagecolor.shape[1]
factor = min(factor1, factor2)
imagecolor = cv2.resize(imagecolor, None, fx=factor, fy=factor, interpolation=cv2.INTER_AREA)
nb_pixels = imagecolor.shape[0] * imagecolor.shape[1]
bleu = imagecolor[:, :, 0].reshape(nb_pixels, 1)
vert = imagecolor[:, :, 1].reshape(nb_pixels, 1)
rouge = imagecolor[:, :, 2].reshape(nb_pixels, 1)
cluster_bleu = numpy.zeros(K)
cluster_vert = numpy.zeros(K)
cluster_rouge = numpy.zeros(K)
groupe = numpy.zeros((nb_pixels, 1))
for i in range(0,K):
groupe[i,0]=i
for i in range(K,nb_pixels):
groupe[i,0]=random.randint(0, K-1)
condition =False
def etape1(indices,i):
s=indices.size
rouge_s=0
vert_s=0
bleu_s=0
#calcul de barycentre des points
if s==0:
cluster_rouge[i]=0
cluster_vert[i]=0
cluster_bleu[i]=0
if s >=1:
for j in range(0,s):
rouge_s=rouge_s+rouge[indices[j]]
vert_s=vert_s+vert[indices[j]]
bleu_s=bleu_s+bleu[indices[j]]
#mise jour des clusters
cluster_rouge[i]=rouge_s/s
cluster_vert[i]=vert_s/s
cluster_bleu[i]=bleu_s/s
iteration=0
oldGroupe = numpy.copy(groupe)
while(condition==False) :
for i in range(0,K):
indices=numpy.where(groupe==i)[0]
etape1(indices,i)
for i in range(0,nb_pixels):
minimum=10000;
dist=0;
index=-1;
for j in range(0,K):
dist=(cluster_rouge[j]-rouge[i])**2+(cluster_vert[j]-vert[i])**2+(cluster_bleu[j]-bleu[i])**2;
if(dist<=minimum):
minimum=dist;
index=j;
groupe[i,0]=index;
condition=numpy.all(groupe==oldGroupe)
oldGroupe = numpy.copy(groupe)
groupe=numpy.reshape(groupe, (imagecolor.shape[0], imagecolor.shape[1]))
for i in range(0, imagecolor.shape[0]):
for j in range(0, imagecolor.shape[1]):
imagecolor[i,j,0] = (cluster_bleu[groupe[i,j]])
imagecolor[i,j,1] = (cluster_vert[groupe[i,j]])
imagecolor[i,j,2] = (cluster_rouge[groupe[i,j]])
cv2.namedWindow("sortie")
cv2.imshow("sortie", imagecolor)
key = cv2.waitKey(0)
if __name__ == "__main__":
main()

Answer 1

The problem is assignment oldGroupe=groupe; which doesn't copy an array, but creates reference with different name (oldGroupe), that points to the same data as groupe. Thus, when you change groupe you also change oldGroupe, and condition is always True.
What you want is to create a copy of data in groupe with oldGroupe = numpy.copy(groupe).