code: 
  
  
  
  
  
  '''simple docstring'''
  
  import numpy as np
  from PIL import Image
  
  
  
  
  
  def lowerCamelCase		(  __lowerCamelCase				:					np.array					)		->np.array:
      _SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE             =    rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
      return 0.2989 * r + 0.5870 * g + 0.1140 * b
  
  
  
  
  
  def lowerCamelCase		(  __lowerCamelCase				:					np.array					)		->np.array:
      return (gray > 127) & (gray <= 255)
  
  
  
  
  
  def lowerCamelCase		(  __lowerCamelCase				:					np.array      , __lowerCamelCase				:					np.array					)		->np.array:
      _SCREAMING_SNAKE_CASE             =    np.zeros_like(__lowerCamelCase					)
      _SCREAMING_SNAKE_CASE             =    np.zeros(
          (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)					)
  
      # Copy image to padded image
      _SCREAMING_SNAKE_CASE             =    image
  
      # Iterate over image & apply kernel
      for x in range(image.shape[1]					):
          for y in range(image.shape[0]					):
              _SCREAMING_SNAKE_CASE             =    (
                  kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
              ).sum()
              _SCREAMING_SNAKE_CASE             =    int(summation == 5					)
      return output
  
  
  # kernel to be applied
  lowercase_			       =				np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
  
  if __name__ == "__main__":
        # read original image
        lowercase_			       =				np.array(Image.open(R"""..\image_data\lena.jpg"""))
        # Apply erosion operation to a binary image
        lowercase_			       =				erosion(grayabinary(rgbagray(image)), structuring_element)
        # Save the output image
        lowercase_			       =				Image.fromarray(output).convert("""RGB""")
        pil_img.save("""result_erosion.png""")
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  def lowerCamelCase		(  __lowerCamelCase				:					str					)		->str:
      _SCREAMING_SNAKE_CASE             =    word.upper()
      _SCREAMING_SNAKE_CASE             =    0
      _SCREAMING_SNAKE_CASE             =    {}
      _SCREAMING_SNAKE_CASE             =    []
  
      for letter in word:
          if letter not in letter_nums:
              _SCREAMING_SNAKE_CASE             =    str(__lowerCamelCase					)
              next_num += 1
          word_pattern.append(letter_nums[letter]					)
      return ".".join(__lowerCamelCase					)
  
  
  if __name__ == "__main__":
        import pprint
        import time
  
        lowercase_			       =				time.time()
        with open("""dictionary.txt""") as in_file:
              lowercase_			       =				in_file.read().splitlines()
  
        lowercase_			       =				{}
        for word in word_list:
              lowercase_			       =				get_word_pattern(word)
              if pattern in all_patterns:
                    all_patterns[pattern].append(word)
              else:
                    lowercase_			       =				[word]
  
        with open("""word_patterns.txt""", """w""") as out_file:
              out_file.write(pprint.pformat(all_patterns))
  
        lowercase_			       =				round(time.time() - start_time, 2)
        print(f"""Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.""")
        # Done!  9,581 word patterns found in 0.58 seconds.
  
  
  
  