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

img = cv.imread('Photos/cats.jpg')

blank = np.zeros(img.shape[:2], dtype='uint8') 

gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

mask = cv.circle(blank, (img.shape[1]//2, img.shape[0]//2), 100, 255, -1)

# mask = cv.bitwise_and(gray,gray,mask=circle)
masked = cv.bitwise_and(img,img,mask=mask)
cv.imshow('Mask', masked)
# Grayscale histogram
# gray_hist = cv.calcHist([gray], [0], mask, [256], [0,256])

# plt.figure()
# plt.title('Grayscale Histogram')  # distribution of pixels (intensity) in the image
# plt.xlabel('Bins')
# plt.ylabel('# of pixels')
# plt.plot(gray_hist)
# plt.xlim([0,256])
# plt.show()

# Color histogram

plt.figure()
plt.title('Colour Histogram')  
plt.xlabel('Bins')
plt.ylabel('# of pixels')

colors = ('b', 'g', 'r')
for i,col in enumerate(colors):
    hist = cv.calcHist([img], [i], mask, [256], [0,256])
    plt.plot(hist, color = col)
    plt.xlim(0, 256)

plt.show()

cv.waitKey(0)