text: ############# BEFORE AND AFTER ARE ALMOST IDENTICAL #########
  
  import cv2
  import numpy as np
  
  image = cv2.imread(r'C:\Users\harrizazham98\Desktop\OpenCVForPython\resources\Day 2\wood.jpg')
  
  # Print error message if image is null
  if image is None:
      print('Could not read image')
  
  # Apply identity kernel
  kernel1 = np.array([[0, 0, 0],
                      [0, 1, 0],
                      [0, 0, 0]])
  
  identity = cv2.filter2D(src=image, ddepth=-1, kernel=kernel1)
  
  cv2.imshow('Original', image)
  cv2.imshow('Identity', identity)
  
  cv2.waitKey()
  cv2.imwrite('identity.jpg', identity)
  cv2.destroyAllWindows()
  
  # Apply blurring kernel
  kernel2 = np.ones((5, 5), np.float32) / 25
  img = cv2.filter2D(src=image, ddepth=-1, kernel=kernel2)
  
  cv2.imshow('Original', image)
  cv2.imshow('Kernel Blur', img)
  
  cv2.waitKey()
  #cv2.imwrite('blur_kernel.jpg', img)
  cv2.destroyAllWindows()