LOS KOD SAMO

import numpy as np
from PIL import Image as im
from scipy.spatial import distance

def dist(a,b):
    return distance.euclidean(a,b)

def index(a,l):
    ind=0

    for i in range(l):
        if a[i]<a[ind]:
            ind=i
    return ind

ncenteroids=int(input("Number of colors:\t"))
iterations=int(input("Number of iterations: \t"))

image=im.open('image.jpg')



# pixels=np.array(image.getdata()).reshape(image.size[0],image.size[1],3)
pi=np.array(image).reshape(-1,3)
pixels=np.zeros((137500,4),dtype=int)
for i in range(137500):
    pixels[i][0]=pi[i][0]
    pixels[i][1]=pi[i][1]
    pixels[i][2]=pi[i][2]


centroids=[]



for i in range(ncenteroids):
    centroids.append(pi[np.random.randint(0,137500)])


temp=[0 for i in range(ncenteroids)]

for p in range(iterations):
    print(centroids)
    for i in range(137500):
        for j in range(ncenteroids):
            temp[j]=dist(centroids[j],pi[i])
        pixels[i][3]=index(temp,ncenteroids)

    t=[[0,0,0] for i in range(ncenteroids)]
    count=[0 for i in range(ncenteroids)]

    for pixel in pixels:
        t[pixel[3]][0]+=pixel[0]
        t[pixel[3]][1]+=pixel[1]
        t[pixel[3]][2]+=pixel[2]
        count[pixel[3]]+=1

    for i in range(ncenteroids):
        centroids[i][0]=t[i][0]//count[i]
        centroids[i][1]=t[i][1]//count[i]
        centroids[i][2]=t[i][2]//count[i]

for i in range(137500):
    pi[i][0]=centroids[pixels[i][3]][0]
    pi[i][1]=centroids[pixels[i][3]][1]
    pi[i][2]=centroids[pixels[i][3]][2]

nova=im.fromarray(pi.reshape(220,625,3))
nova.save("nova2","jpeg")