import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import cv2

img = cv2.cvtColor(cv2.imread('test.jpg'), cv2.COLOR_BGR2GRAY)
img = cv2.GaussianBlur(img, (15, 15), 0) # poprawia jakosc
img = cv2.resize(img, (8, 8), interpolation=cv2.INTER_AREA)

print(type(img))
print(img.shape)
print(img)
plt.imshow(img ,cmap='binary')
plt.show()

data = []

rows, cols = img.shape
for i in range(rows):
    for j in range(cols):
        k = img[i, j]
        if k > 200:
            k = 0 # brak czarnego
        else:
            k = 1

        data.append(k)

print(data)