text: import numpy as np
  import matplotlib.pyplot as plt
  
  from skimage import data
  from skimage.transform import pyramid_gaussian
  
  import cv2
  image = cv2.imread("Berkeley.jpg")
  
  rows, cols, dim = image.shape
  pyramid = tuple(pyramid_gaussian(image, downscale=2))
  
  composite_image = np.zeros((rows, cols + cols // 2, 3), dtype=np.double)
  
  composite_image[:rows, :cols, :] = pyramid[0]
  i_row = 0
  x=0
  for p in pyramid[1:]:
      x+=1
      if x >4:
          break
      n_rows, n_cols = p.shape[:2]
      composite_image[i_row:i_row + n_rows, cols:cols + n_cols] = p
      i_row += n_rows
  
  fig, ax = plt.subplots()
  ax.imshow(composite_image)
  plt.show()