



import math
import sys

import cva
import numpy as np
def 	snake_case__       (					__lowercase							,     __lowercase       )		->		np.ndarray:







						"""simple docstring"""

						A__	:							List[Any]						    = math.sqrt(__lowercase       )
						A__	:							Tuple						    = 1 / (sigma * math.sqrt(2 * math.pi       ))
						return cons * np.exp(-((img / sigma) ** 2) * 0.5       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase							,     __lowercase       )		->		np.ndarray:







						"""simple docstring"""

						A__	:							Dict						    = kernel_size // 2
						return img[x - half : x + half + 1, y - half : y + half + 1]
def 	snake_case__       (					__lowercase							,     __lowercase       )		->		np.ndarray:







						"""simple docstring"""

						A__	:							Optional[Any]						    = np.zeros((kernel_size, kernel_size)       )
						for i in range(0							,     __lowercase       ):
												for j in range(0							,     __lowercase       ):
																		A__	:							int						    = math.sqrt(
																		    abs(i - kernel_size // 2       ) ** 2 + abs(j - kernel_size // 2       ) ** 2       )
						return vec_gaussian(__lowercase							,     __lowercase       )
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase							,     __lowercase							,     )		->		np.ndarray:







						"""simple docstring"""

						A__	:							str						    = np.zeros(img.shape       )
						A__	:							Optional[int]						    = get_gauss_kernel(__lowercase							,     __lowercase       )
						A__    ,       A__	:							int						    = img.shape
						for i in range(kernel_size // 2							,     size_x - kernel_size // 2       ):
												for j in range(kernel_size // 2							,     size_y - kernel_size // 2       ):
																		A__	:							Optional[Any]						    = get_slice(__lowercase							,     __lowercase							,     __lowercase							,     __lowercase       )
																		A__	:							Optional[int]						    = img_s - img_s[kernel_size // 2, kernel_size // 2]
																		A__	:							int						    = vec_gaussian(__lowercase							,     __lowercase       )
																		A__	:							Optional[Any]						    = np.multiply(__lowercase							,     __lowercase       )
																		A__	:							List[Any]						    = np.multiply(__lowercase							,     __lowercase       )
																		A__	:							List[Any]						    = np.sum(__lowercase       ) / np.sum(__lowercase       )
																		A__	:							int						    = val
						return imga
def 	snake_case__       (					__lowercase       )		->		tuple:







						"""simple docstring"""

						A__	:							Optional[int]						    = args[1] if args[1:] else "../image_data/lena.jpg"
						A__	:							Any						    = float(args[2]       ) if args[2:] else 1.0
						A__	:							str						    = float(args[3]       ) if args[3:] else 1.0
						if args[4:]:
												A__	:							Optional[int]						    = int(args[4]       )
												A__	:							int						    = kernel_size + abs(kernel_size % 2 - 1       )
						else:
												A__	:							List[Any]						    = 5
						return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
		snake_case ,       snake_case ,       snake_case ,       snake_case    :						List[Any]  =						parse_args(sys.argv)
		snake_case    :						List[Any]  =						cva.imread(filename, 0)
		cva.imshow('input image', img)

		snake_case    :						Dict  =						img / 2_5_5
		snake_case    :						List[str]  =						out.astype('float32')
		snake_case    :						Optional[Any]  =						bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
		snake_case    :						Any  =						out * 2_5_5
		snake_case    :						Tuple  =						np.uinta(out)
		cva.imshow('output image', out)
		cva.waitKey(0)
		cva.destroyAllWindows()




from __future__ import annotations

snake_case    :						Optional[Any]  =						{
    'A': ['B', 'C', 'E'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F', 'G'],
    'D': ['B'],
    'E': ['A', 'B', 'D'],
    'F': ['C'],
    'G': ['C'],
}




class 							lowerCAmelCase__  :







					def __init__(       self      :     Optional[Any]			,		_A      :     dict[str, list[str]]			,		_A      :     str):
											A__	:							Optional[Any]						    = graph
											# mapping node to its parent in resulting breadth first tree
											A__	:							dict[str, str | None]						    = {}
											A__	:							List[str]						    = source_vertex







					def  _lowercase			(       self      :     List[Any]):
											A__	:							str						    = {self.source_vertex}
											A__	:							List[str]						    = None
											A__	:							List[str]						    = [self.source_vertex]  # first in first out queue

											while queue:
																	A__	:							int						    = queue.pop(0)
																	for adjacent_vertex in self.graph[vertex]:
																							if adjacent_vertex not in visited:
																													visited.add(_A)
																													A__	:							Any						    = vertex
																													queue.append(_A)







					def  _lowercase			(       self      :     int			,		_A      :     str):
											if target_vertex == self.source_vertex:
																	return self.source_vertex

											A__	:							List[Any]						    = self.parent.get(_A)
											if target_vertex_parent is None:
																	A__	:							Union[str, Any]						    = (
																	    F'No path from vertex: {self.source_vertex} to vertex: {target_vertex}'
																	)
																	raise ValueError(_A)

											return self.shortest_path(_A) + F'->{target_vertex}'


if __name__ == "__main__":
		snake_case    :						Any  =						Graph(graph, 'G')
		g.breath_first_search()
		print(g.shortest_path('D'))
		print(g.shortest_path('G'))
		print(g.shortest_path('Foo'))