from pathlib import Path

import numpy as np
from PIL import Image



def 	_a						(   UpperCAmelCase					)    ->    List[str]:







   """simple docstring"""
   lowerCamelCase__       :						Dict        =							rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
   return 0.29_89 * r + 0.58_70 * g + 0.11_40 * b



def 	_a						(   UpperCAmelCase					)    ->    Union[str, Any]:







   """simple docstring"""
   return (gray > 127) & (gray <= 255)



def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase					)    ->    Dict:







   """simple docstring"""
   lowerCamelCase__       :						Any        =							np.zeros_like(__lowerCamelCase					)
   lowerCamelCase__       :						Any        =							np.zeros(
       (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)					)

   # Copy image to padded image
   lowerCamelCase__       :						Any        =							image

   # Iterate over image & apply kernel
   for x in range(image.shape[1]					):
      for y in range(image.shape[0]					):
         lowerCamelCase__       :						Union[str, Any]        =							(
             kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
         ).sum()
         lowerCamelCase__       :						Tuple        =							int(summation > 0					)
   return output


if __name__ == "__main__":
       # read original image
       _A :   Dict  			=  Path(__file__).resolve().parent / 'image_data' / 'lena.jpg'
       _A :   List[str]  			=  np.array(Image.open(lena_path))
       # kernel to be applied
       _A :   Optional[int]  			=  np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
       _A :   Tuple  			=  dilation(gray_to_binary(rgb_to_gray(lena)), structuring_element)
       # Save the output image
       _A :   Optional[int]  			=  Image.fromarray(output).convert('RGB')
       pil_img.save('result_dilation.png')










from __future__ import annotations

_A :   List[str]  			=  '#'


class        __SCREAMING_SNAKE_CASE      :







       def __init__(				self					:     List[Any]      )       ->None:
          lowerCamelCase__       :						dict        =							{}







       def 						__lowerCamelCase   (				self					:     Union[str, Any]		, A					:     str      )       ->None:
          lowerCamelCase__       :						Any        =							self._trie
          for char in text:
             if char not in trie:
                lowerCamelCase__       :						Any        =							{}
             lowerCamelCase__       :						Any        =							trie[char]
          lowerCamelCase__       :						List[str]        =							True







       def 						__lowerCamelCase   (				self					:     List[Any]		, A					:     str      )       ->tuple | list:
          lowerCamelCase__       :						Dict        =							self._trie
          for char in prefix:
             if char in trie:
                lowerCamelCase__       :						List[Any]        =							trie[char]
             else:
                return []
          return self._elements(A      )







       def 						__lowerCamelCase   (				self					:     Dict		, A					:     dict      )       ->tuple:
          lowerCamelCase__       :						Optional[Any]        =							[]
          for c, v in d.items():
             lowerCamelCase__       :						Any        =							[''' '''] if c == END else [(c + s) for s in self._elements(A      )]
             result.extend(A      )
          return tuple(A      )


_A :   str  			=  Trie()
_A :   List[Any]  			=  ('depart', 'detergent', 'daring', 'dog', 'deer', 'deal')
for word in words:
       trie.insert_word(word)



def 	_a						(   UpperCAmelCase					)    ->    tuple:







   """simple docstring"""
   lowerCamelCase__       :						Optional[int]        =							trie.find_word(UpperCAmelCase					)
   return tuple(string + word for word in suffixes					)



def 	_a						(   )    ->    None:







   """simple docstring"""
   print(autocomplete_using_trie('''de'''					)					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       main()



