

"""simple docstring"""





from __future__ import annotations







class        SCREAMING_SNAKE_CASE      :






					"""simple docstring"""



					def __init__( self    :       Any     ,lowercase_    :       int	):
						lowerCAmelCase__			:		Any						       =			value
						lowerCAmelCase__			:		Node | None						       =			None
						lowerCAmelCase__			:		Node | None						       =			None







class        SCREAMING_SNAKE_CASE      :






					"""simple docstring"""



					lowercase__       				= 42







					def __init__( self    :       Optional[int]	):
						lowerCAmelCase__			:		List[str]						       =			0







					def  __lowerCAmelCase				( self    :       Any     ,lowercase_    :       Node | None     ,lowercase_    :       int	):
						if node is None:
							return

						if path_sum == self.target:
							self.paths += 1

						if node.left:
							self.depth_first_search(node.left     ,path_sum + node.left.value	)
						if node.right:
							self.depth_first_search(node.right     ,path_sum + node.right.value	)







					def  __lowerCAmelCase				( self    :       List[Any]     ,lowercase_    :       Node | None     ,lowercase_    :       int | None = None	):
						if node is None:
							return 0
						if target is not None:
							lowerCAmelCase__			:		Dict						       =			target

						self.depth_first_search(lowercase_     ,node.value	)
						self.path_sum(node.left	)
						self.path_sum(node.right	)

						return self.paths


if __name__ == "__main__":
							import doctest

							doctest.testmod()







"""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)




