






'''simple docstring'''







from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase    ,      UpperCamelCase				)				->	Optional[Any]:
							lowerCamelCase__ :     Any	  =	k_size // 2
							lowerCamelCase__  ,		lowerCamelCase__ :     Optional[int]	  =	mgrid[0 - center : k_size - center, 0 - center : k_size - center]
							lowerCamelCase__ :     Optional[int]	  =	1 / (2 * pi * sigma) * exp(-(square(UpperCamelCase				) + square(UpperCamelCase				)) / (2 * square(UpperCamelCase				))				)
							return g





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase    ,      UpperCamelCase    ,      UpperCamelCase				)				->	int:
							lowerCamelCase__  ,		lowerCamelCase__ :     List[str]	  =	image.shape[0], image.shape[1]
							# dst image height and width
							lowerCamelCase__ :     Dict	  =	height - k_size + 1
							lowerCamelCase__ :     Dict	  =	width - k_size + 1

							# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
							lowerCamelCase__ :     int	  =	zeros((dst_height * dst_width, k_size * k_size)				)
							lowerCamelCase__ :     Optional[Any]	  =	0
							for i, j in product(range(UpperCamelCase				)    ,      range(UpperCamelCase				)				):
														lowerCamelCase__ :     int	  =	ravel(image[i : i + k_size, j : j + k_size]				)
														lowerCamelCase__ :     List[Any]	  =	window
														row += 1

							#  turn the kernel into shape(k*k, 1)
							lowerCamelCase__ :     Tuple	  =	gen_gaussian_kernel(UpperCamelCase    ,      UpperCamelCase				)
							lowerCamelCase__ :     List[Any]	  =	ravel(UpperCamelCase				)

							# reshape and get the dst image
							lowerCamelCase__ :     Dict	  =	dot(UpperCamelCase    ,      UpperCamelCase				).reshape(UpperCamelCase    ,      UpperCamelCase				).astype(UpperCamelCase				)

							return dst


if __name__ == "__main__":
			# read original image
			_A     :      Any   					=imread(r'''../image_data/lena.jpg''')
			# turn image in gray scale value
			_A     :      Tuple   					=cvtColor(img, COLOR_BGR2GRAY)

			# get values with two different mask size
			_A     :      str   					=gaussian_filter(gray, 3, sigma=1)
			_A     :      Optional[Any]   					=gaussian_filter(gray, 5, sigma=0.8)

			# show result images
			imshow('''gaussian filter with 3x3 mask''', gaussianaxa)
			imshow('''gaussian filter with 5x5 mask''', gaussianaxa)
			waitKey()









'''simple docstring'''







from __future__ import annotations

from typing import Any

class _lowercase     (    _lowercase		):
							pass



class _lowercase     :




							def __init__(							self:    Optional[int]      ,							UpperCamelCase__:    Any					):
														lowerCamelCase__ :     Any	  =	data
														lowerCamelCase__ :     Node | None	  =	None




							def __iter__(							self:    List[Any]					):
														lowerCamelCase__ :     Optional[Any]	  =	self
														lowerCamelCase__ :     int	  =	[]
														while node:
																					if node in visited:
																												raise ContainsLoopError
																					visited.append(UpperCamelCase__					)
																					yield node.data
																					lowerCamelCase__ :     List[str]	  =	node.next_node




							@property
							def 		lowerCamelCase_    (							self:    Optional[Any]					):
														try:
																					list(self					)
																					return False
														except ContainsLoopError:
																					return True


if __name__ == "__main__":
			_A     :      Any   					=Node(1)
			_A     :      Optional[int]   					=Node(2)
			_A     :      Dict   					=Node(3)
			_A     :      Optional[Any]   					=Node(4)
			print(root_node.has_loop)  # False
			_A     :      Any   					=root_node.next_node
			print(root_node.has_loop)  # True

			_A     :      Dict   					=Node(5)
			_A     :      Union[str, Any]   					=Node(6)
			_A     :      str   					=Node(5)
			_A     :      int   					=Node(6)
			print(root_node.has_loop)  # False

			_A     :      Optional[Any]   					=Node(1)
			print(root_node.has_loop)  # False

