


'''simple docstring'''




from __future__ import annotations

def      _a		(lowercase__ :      list       ,      lowercase__ :      list	) -> list:






     """simple docstring"""
     __snake_case    			=	[None] * (len(a_	) + len(a_	))

     __snake_case    			=	0  # pointer to current index for left Half
     __snake_case    			=	0  # pointer to current index for the right Half
     __snake_case    			=	0  # pointer to current index for the sorted array Half

     while pointera < len(a_	) and pointera < len(a_	):
          if left_half[pointera] < right_half[pointera]:
               __snake_case    			=	left_half[pointera]
               pointera += 1
               index += 1
          else:
               __snake_case    			=	right_half[pointera]
               pointera += 1
               index += 1
     while pointera < len(a_	):
          __snake_case    			=	left_half[pointera]
          pointera += 1
          index += 1

     while pointera < len(a_	):
          __snake_case    			=	right_half[pointera]
          pointera += 1
          index += 1

     return sorted_array

def      _a		(lowercase__ :      list	) -> list:






     """simple docstring"""
     if len(a_	) <= 1:
          return array
     # the actual formula to calculate the middle element = left + (right - left) // 2
     # this avoids integer overflow in case of large N
     __snake_case    			=	0 + (len(a_	) - 0) // 2

     # Split the array into halves till the array length becomes equal to One
     # merge the arrays of single length returned by mergeSort function and
     # pass them into the merge arrays function which merges the array
     __snake_case    			=	array[:middle]
     __snake_case    			=	array[middle:]

     return merge(merge_sort(a_	)       ,      merge_sort(a_	)	)


if __name__ == "__main__":
       import doctest

       doctest.testmod()








'''simple docstring'''




import numpy as np
from PIL import Image





def      _a		(lowercase__ :      np.array	) -> np.array:






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





def      _a		(lowercase__ :      np.array	) -> np.array:






     """simple docstring"""
     return (gray > 1_2_7) & (gray <= 2_5_5)





def      _a		(lowercase__ :      np.array       ,      lowercase__ :      np.array	) -> np.array:






     """simple docstring"""
     __snake_case    			=	np.zeros_like(lowercase__	)
     __snake_case    			=	np.zeros(
         (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)	)

     # Copy image to padded image
     __snake_case    			=	image

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


# kernel to be applied
_a      :      Tuple       				=      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      :      List[Any]       				=      erosion(grayabinary(rgbagray(image)), structuring_element)
       # Save the output image
       _a      :      int       				=      Image.fromarray(output).convert("RGB")
       pil_img.save("result_erosion.png")




