

"""simple docstring"""





class        SCREAMING_SNAKE_CASE      :






					"""simple docstring"""



					def __init__( self    :       Any     ,lowercase_    :       int	):
						lowerCAmelCase__			:		Optional[int]						       =			data
						lowerCAmelCase__			:		int
						lowerCAmelCase__			:		Node

def 						__SCREAMING_SNAKE_CASE						(   A_				):
	lowerCAmelCase__			:		List[str]						       =			0
	lowerCAmelCase__			:		List[Any]						       =			x

def 						__SCREAMING_SNAKE_CASE						(   A_		,  A_				):
	lowerCAmelCase__			:		List[Any]						       =			find_set(A_				), find_set(A_				)
	if x == y:
		return

	elif x.rank > y.rank:
		lowerCAmelCase__			:		Tuple						       =			x
	else:
		lowerCAmelCase__			:		Optional[Any]						       =			y
		if x.rank == y.rank:
			y.rank += 1

def 						__SCREAMING_SNAKE_CASE						(   A_				):
	if x != x.parent:
		lowerCAmelCase__			:		Tuple						       =			find_set(x.parent				)
	return x.parent

def 						__SCREAMING_SNAKE_CASE						(   A_				):
	lowerCAmelCase__			:		str						       =			({0, 1, 2}, {3, 4, 5})
	for s in sets:
		if node.data in s:
			return s
	lowerCAmelCase__			:		str						       =			f'{node.data} is not in {sets}'
	raise ValueError(A_				)

def 						__SCREAMING_SNAKE_CASE						(   ):
	lowerCAmelCase__			:		Union[str, Any]						       =			[Node(A_				) for i in range(6				)]
	for v in vertex:
		make_set(A_				)

	union_set(vertex[0]		,  vertex[1]				)
	union_set(vertex[1]		,  vertex[2]				)
	union_set(vertex[3]		,  vertex[4]				)
	union_set(vertex[3]		,  vertex[5]				)

	for nodea in vertex:
		for nodea in vertex:
			if find_python_set(A_				).isdisjoint(find_python_set(A_				)				):
				assert find_set(A_				) != find_set(A_				)
			else:
				assert find_set(A_				) == find_set(A_				)


if __name__ == "__main__":
							test_disjoint_set()







"""simple docstring"""





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

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


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

							# get values with two different mask size
							__UpperCamelCase						:   int							   =	median_filter(gray, 3)
							__UpperCamelCase						:   Tuple							   =	median_filter(gray, 5)

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




