def nbColors(img, contour):
lesion = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
lesion = Caracteristics.extractLesion(lesion, contour)
lesion, centers = Preprocess.KMEANS(lesion, K=7)
distances = np.array([])
for i in range(0, len(centers) - 1):
for j in range(i + 1, len(centers)):
center = centers[i]
center2 = centers[j]
r = (float(center[0]) - float(center2[0]))**2 + (float(
center[1]) - float(center2[1]))**2 + (float(center[2]) -
float(center2[2]))**2
d = math.sqrt(r)
distances = np.append(distances, d)
# for i, center in enumerate(centers):
# for j, center2 in enumerate(centers):
# if(i != j):
# r = (float(center[0])-float(center2[0]))**2 + (float(center[1])-float(center2[1]))**2 + (float(center[2])-float(center2[2]))**2
# d = math.sqrt(r)
# distances = np.append(distances, d)
s = np.sum(distances)
print(s)
# cv2.imshow('nb colors', lesion)
return s
