


from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import divide, inta, multiply, ravel, sort, zeros_like



def       lowerCAmelCase			(		lowerCAmelCase_			, lowerCAmelCase_=3			)->			List[Any]:
				lowerCAmelCase_			:   Optional[Any]     					=					int(mask / 2			)
				# copy image size
				lowerCAmelCase_			:   Dict     					=					zeros_like(lowerCAmelCase_			)
				for i in range(lowerCAmelCase_			, gray_img.shape[0] - bd			):
								for j in range(lowerCAmelCase_			, gray_img.shape[1] - bd			):
												# get mask according with mask
												lowerCAmelCase_			:   Tuple     					=					ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]			)
												# calculate mask median
												lowerCAmelCase_			:   Optional[Any]     					=					sort(lowerCAmelCase_			)[inta(divide((multiply(lowerCAmelCase_			, lowerCAmelCase_			))			, 2			) + 1			)]
												lowerCAmelCase_			:   List[str]     					=					median
				return median_img


if __name__ == "__main__":
						# read original image
						_UpperCAmelCase      :	List[Any]  =imread("""../image_data/lena.jpg""")
						# turn image in gray scale value
						_UpperCAmelCase      :	Optional[int]  =cvtColor(img, COLOR_BGR2GRAY)

						# get values with two different mask size
						_UpperCAmelCase      :	Dict  =median_filter(gray, 3)
						_UpperCAmelCase      :	List[Any]  =median_filter(gray, 5)

						# show result images
						imshow("""median filter with 3x3 mask""", medianaxa)
						imshow("""median filter with 5x5 mask""", medianaxa)
						waitKey(0)



def       lowerCAmelCase			(		lowerCAmelCase_			)->			int:
				lowerCAmelCase_			:   Optional[int]     					=					len(lowerCAmelCase_			)
				if n in (0, 1):
								return 0
				return sum(query * (n - i - 1) for i, query in enumerate(sorted(lowerCAmelCase_			)			)			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()