text: import cv2
  import numpy as np
  import matplotlib.pyplot as plt
  image = cv2.imread('Dhoni.jpg')
  image = cv2.cvtColor(image , cv2.COLOR_BGR2RGB)
  gray = cv2.cvtColor(image , cv2.COLOR_BGR2GRAY)
  eye_cascade = cv2.CascadeClassifier("haarcascade_eye.xml")
  eyes = eye_cascade.detectMultiScale(gray)
  filter = cv2.cvtColor(cv2.imread('blue.png') , cv2.COLOR_BGR2RGB)
  for x, y, w, h in eyes:
      centre_x = x+w/2 
      centre_y = y + h/2
      filter = cv2.resize(filter , (int( w / 4)  ,int( h /4) ))
      print(filter.shape) 
      if max(filter.shape) == max(image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)):int(centre_x+(w/8))].shape):
          filter = cv2.resize(filter , (int( w / 4)  ,int( h /4) ))
      elif max(filter.shape) > max(image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)):int(centre_x+(w/8))].shape):
          n = max(filter.shape) - max(image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)):int(centre_x+(w/8))].shape)
          filter = cv2.resize(filter , (int( w / 4) +n ,int( h /4) + n))
      elif max(filter.shape) < max(image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)):int(centre_x+(w/8))].shape):
          n = max(image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)):int(centre_x+(w/8))].shape) - max(filter.shape) 
          filter = cv2.resize(filter , (int( w / 4) +n ,int( h /4) + n))
      alpha_filter =   filter[:,:,2] / 255
      alpha_back =  1 - alpha_filter
      for c in range(0,3):
          image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)+4):int(centre_x+(w/8)+4),c]=(alpha_back*image[int(centre_y-(h/8)):int(centre_y+(h/8)),int(centre_x-(w/8)+4):int(centre_x+(w/8)+4),c]+alpha_filter*filter[:,:,c])
      plt.imshow(image)
      plt.imsave('filter1.png' , image)
  
  