text: #  METHOD _!
  import cv2
  import numpy as np
  from matplotlib import pyplot as plt
  
  img = cv2.imread('home.jpg',0)
  plt.hist(img.ravel(),256,[0,256]); plt.show()
  
  #    METHOD _2 
  import cv2
  import numpy as np
  from matplotlib import pyplot as plt
  
  img = cv2.imread('home.jpg')
  color = ('b','g','r')
  for i,col in enumerate(color):
      histr = cv2.calcHist([img],[i],None,[256],[0,256])
      plt.plot(histr,color = col)
      plt.xlim([0,256])
  plt.show()
  
  
  # APPLICATION OF MASK
  img = cv2.imread('home.jpg',0)
  
  # create a mask
  mask = np.zeros(img.shape[:2], np.uint8)
  mask[100:300, 100:400] = 255
  masked_img = cv2.bitwise_and(img,img,mask = mask)
  
  # Calculate histogram with mask and without mask
  # Check third argument for mask
  hist_full = cv2.calcHist([img],[0],None,[256],[0,256])
  hist_mask = cv2.calcHist([img],[0],mask,[256],[0,256])
  
  plt.subplot(221), plt.imshow(img, 'gray')
  plt.subplot(222), plt.imshow(mask,'gray')
  plt.subplot(223), plt.imshow(masked_img, 'gray')
  plt.subplot(224), plt.plot(hist_full), plt.plot(hist_mask)
  plt.xlim([0,256])
  
  plt.show()