





'''simple docstring'''
def     lowercase__       (       __lowercase						:  str    ,  __lowercase						:  Tuple					)			->				str:



							"""simple docstring"""






							sequence.append(__lowercase					)

							__UpperCamelCase	=  0
							while sequence[index] != target:
														index += 1

							sequence.pop()

							if index == len(__lowercase					):
														return None

							return index


if __name__ == "__main__":
				a__							:							Any			=input('''Enter numbers separated by comma:\n''').strip()
				a__							:							Any			=[int(item) for item in user_input.split(''',''')]

				a__							:							Tuple			=input('''Enter a single number to be found in the list:\n''')
				a__							:							List[Any]			=int(target_input)
				a__							:							List[Any]			=sentinel_linear_search(sequence, target)
				if result is not None:
								print(f'{target} found at positions: {result}')
				else:
								print('''Not found''')







'''simple docstring'''
import numpy as np
from PIL import Image
def     lowercase__       (       __lowercase						:  np.array					)			->				np.array:



       """simple docstring"""






       __UpperCamelCase	,						__UpperCamelCase	,						__UpperCamelCase	=  rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
       return 0.2_9_8_9 * r + 0.5_8_7_0 * g + 0.1_1_4_0 * b
def     lowercase__       (       __lowercase						:  np.array					)			->				np.array:



       """simple docstring"""






       return (gray > 127) & (gray <= 255)
def     lowercase__       (       __lowercase						:  np.array    ,  __lowercase						:  np.array					)			->				np.array:



       """simple docstring"""






       __UpperCamelCase	=  np.zeros_like(__lowercase					)
       __UpperCamelCase	=  np.zeros(
           (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)					)

       # Copy image to padded image
       __UpperCamelCase	=  image

       # Iterate over image & apply kernel
       for x in range(image.shape[1]					):
              for y in range(image.shape[0]					):
                     __UpperCamelCase	=  (
                         kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
                     ).sum()
                     __UpperCamelCase	=  int(summation == 5					)
       return output


# kernel to be applied
a__							:							Dict			=np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])

if __name__ == "__main__":
    # read original image
    a__							:							Any			=np.array(Image.open(r'''..\image_data\lena.jpg'''))
    # Apply erosion operation to a binary image
    a__							:							Union[str, Any]			=erosion(grayabinary(rgbagray(image)), structuring_element)
    # Save the output image
    a__							:							Tuple			=Image.fromarray(output).convert('''RGB''')
    pil_img.save('''result_erosion.png''')
