



import numpy as np
from PIL import Image



def __lowerCAmelCase       (   SCREAMING_SNAKE_CASE_     ):
			lowercase__         = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
			return 0.2989 * r + 0.5870 * g + 0.1140 * b



def __lowerCAmelCase       (   SCREAMING_SNAKE_CASE_     ):
			return (gray > 127) & (gray <= 255)



def __lowerCAmelCase       (   SCREAMING_SNAKE_CASE_  ,     SCREAMING_SNAKE_CASE_     ):
			lowercase__         = np.zeros_like(lowercase_     )
			lowercase__         = np.zeros(
			    (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)     )

			# Copy image to padded image
			lowercase__         = image

			# Iterate over image & apply kernel
			for x in range(image.shape[1]     ):
						for y in range(image.shape[0]     ):
									lowercase__         = (
									    kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
									).sum()
									lowercase__         = 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""")











"""simple docstring"""


def     lowercase__			(    lowercase_	)    ->						str:




      """simple docstring"""

      return " ".join(sorted(set(sentence.split()	)	)	)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
