import cv2
import matplotlib.pyplot as plt
import time
import itertools as it
from mpl_toolkits.mplot3d import Axes3D
from sklearn.cluster import KMeans
from multiprocessing import Pool, cpu_count
from tqdm import tqdm


def rgb_hex(rgb):
    return "#{:02x}{:02x}{:02x}".format(int(rgb[0]), int(rgb[1]), int(rgb[2]))

def processing(reform,cluster):
    fig = plt.figure()
    ax = Axes3D(fig)
    #zip(cluster.labels_,reform)
    for color in tqdm(reform):
        ax.scatter(color[0], color[1], color[2], color = rgb_hex(color))
    plt.savefig('figura.png')
    plt.show()

def funkcja(x):
    image = cv2.imread(x)
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    #print('Wczytano zdjęcie i zamieniono na tablice pixeli')
    reform = image.reshape((image.shape[0] * image.shape[1], 3))
    cluster = KMeans(5).fit(reform)
    colors=cluster.cluster_centers_
    start = time.time()
    #print('Rozkładanie punktów w układzie')
    print('...')
    pool = Pool(cpu_count())
    results = pool.map(processing(reform,cluster))
    end = time.time()
    print('Kolorowanie zajęło: ',"{0:.2f}".format(end-start),'s')


#print('Analiza kolorów elementów stron internetowych')
funkcja('C:/Users/Peter/Desktop/praca/python/test/google.com.png')