'''simple docstring'''

def lowerCamelCase__						(       A_       ):
 UpperCAmelCase_				       =					len(A_       )
 for _ in range(
     0       ,			int(((no_of_elements - 1) / 2) + 1       )       ):  # we don't need to traverse to end of list as
  for j in range(0       ,			no_of_elements - 1       ):
   if (
       lst[j + 1] < lst[j]
   ):  # applying bubble sort algorithm from left to right (or forwards)
    UpperCAmelCase_				       =					lst[j + 1]
    UpperCAmelCase_				       =					lst[j]
    UpperCAmelCase_				       =					temp
   if (
       lst[no_of_elements - 1 - j] < lst[no_of_elements - 2 - j]
   ):  # applying bubble sort algorithm from right to left (or backwards)
    UpperCAmelCase_				       =					lst[no_of_elements - 1 - j]
    UpperCAmelCase_				       =					lst[no_of_elements - 2 - j]
    UpperCAmelCase_				       =					temp
 return lst


if __name__ == "__main__":
      print('''enter the list to be sorted''')
      __snake_case       :   List[str]  		=    [int(x) for x in input().split()]  # inputing elements of the list in one line
      __snake_case       :   Optional[int]  		=    double_sort(lst)
      print('''the sorted list is''')
      print(sorted_lst)

'''simple docstring'''

import numpy as np
from PIL import Image



def lowerCamelCase__						(       A_       ):
 UpperCAmelCase_       ,       UpperCAmelCase_       ,       UpperCAmelCase_				       =					rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
 return 0.2989 * r + 0.5870 * g + 0.1140 * b



def lowerCamelCase__						(       A_       ):
 return (gray > 127) & (gray <= 255)



def lowerCamelCase__						(       A_       ,			A_       ):
 UpperCAmelCase_				       =					np.zeros_like(A_       )
 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
__snake_case       :   List[str]  		=    np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])

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