import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt

def take_max(A):
    A = [X]
    max = A[0]
    for i in range (len(A)):
        if A[i]>max:
            max = A[i]
    return max

img = cv.imread('image.png')

imgray = np.average(img,axis=2)

ret,thresh = cv.threshold(imgray,100,255,cv.THRESH_BINARY_INV)

#thresh.reshape((imgray.shape[0],imgray.shape[1],1))*np.array([1.,1.,1.]))


thresh = thresh.astype(np.uint8)


im2,contours, hierarchy = cv.findContours(thresh,cv.RETR_LIST,cv.CHAIN_APPROX_SIMPLE)
cv.drawContours(img,contours,-1,(0,255,0),3)
cv.fillPoly(img, contours, color=(0,0,0))
X = []
Y = []
W = []
H = []
for c in contours:
      x,y,w,h = cv.boundingRect(c)
      cv.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
      X.append(x)
      Y.append(y)
      W.append(w)
      Y.append(h)
x_r = take_max(X)
y_r = take_max(Y)
w_r =take_max(W)
h_r = take_max(H)
max_picture = img[y_r:y_r+h, x_r:x_r+h]
print("-------------------------------------------------------------------------------------------------------------------------------------------------")
plt.imshow(max_picture)
#print(w*h)
plt.show()