


def      _lowercase(				__a							:	str    ):
							a__     						=[]
							a__     						=1

							for i in range(len(__a    )    ):
														if i + 1 < len(__a    ) and text[i] == text[i + 1]:
																					count += 1
														else:
																					encoded.append((text[i], count)    )
																					a__     						=1

							return encoded






def      _lowercase(				__a							:	list    ):
							return "".join(char * length for char, length in encoded    )


if __name__ == "__main__":
	from doctest import testmod

	testmod(name='run_length_encode', verbose=True)
	testmod(name='run_length_decode', verbose=True)








import numpy as np
from PIL import Image






def      _lowercase(				__a							:	np.array    ):
							a__						,    a__						,    a__     						=rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
							return 0.29_89 * r + 0.58_70 * g + 0.11_40 * b






def      _lowercase(				__a							:	np.array    ):
							return (gray > 127) & (gray <= 255)






def      _lowercase(				__a							:	np.array						,    __a							:	np.array    ):
							a__     						=np.zeros_like(__a    )
							a__     						=np.zeros(
							    (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)    )

							# Copy image to padded image
							a__     						=image

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


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

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

