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  snake_case						(__lowercase ,      __lowercase						)	->	Tuple:

						'''simple docstring'''



						_snake_case						:					List[Any]    =   k_size // 2
						_snake_case						:					Any    =   mgrid[0 - center : k_size - center, 0 - center : k_size - center]
						_snake_case						:					Optional[Any]    =   1 / (2 * pi * sigma) * exp(-(square(__a						) + square(__a						)) / (2 * square(__a						))						)
						return g






def  snake_case						(__lowercase ,      __lowercase ,      __lowercase						)	->	List[Any]:

						'''simple docstring'''



						_snake_case						:					Union[str, Any]    =   image.shape[0], image.shape[1]
						# dst image height and width
						_snake_case						:					int    =   height - k_size + 1
						_snake_case						:					Optional[int]    =   width - k_size + 1

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

						#  turn the kernel into shape(k*k, 1)
						_snake_case						:					List[Any]    =   gen_gaussian_kernel(__a ,      __a						)
						_snake_case						:					str    =   ravel(__a						)

						# reshape and get the dst image
						_snake_case						:					Optional[int]    =   dot(__a ,      __a						).reshape(__a ,      __a						).astype(__a						)

						return dst


if __name__ == "__main__":
				# read original image
				__SCREAMING_SNAKE_CASE						:   List[str]         =			imread(R'../image_data/lena.jpg')
				# turn image in gray scale value
				__SCREAMING_SNAKE_CASE						:   str         =			cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				__SCREAMING_SNAKE_CASE						:   List[Any]         =			gaussian_filter(gray, 3, sigma=1)
				__SCREAMING_SNAKE_CASE						:   Optional[int]         =			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()
from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass



@dataclass
class        lowercase_   :
							_lowerCamelCase						=		42
							_lowerCamelCase						=		42




class        lowercase_   :



							def __init__(						self				,    lowercase_    ):
													_snake_case						:					list[list[Edge]]    =   [[] for _ in range(lowercase_    )]
													_snake_case						:					Union[str, Any]    =   size



							def __getitem__(						self				,    lowercase_    ):
													return iter(self._graph[vertex]    )



							@property
							def 	UpperCamelCase	(						self    ):
													return self._size



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_				,    lowercase_    ):
													if weight not in (0, 1):
																			raise ValueError("Edge weight must be either 0 or 1."    )

													if to_vertex < 0 or to_vertex >= self.size:
																			raise ValueError("Vertex indexes must be in [0; size)."    )

													self._graph[from_vertex].append(Edge(lowercase_				,    lowercase_    )    )



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_    ):
													_snake_case						:					Optional[int]    =   deque([start_vertex]    )
													_snake_case						:					list[int | None]    =   [None] * self.size
													_snake_case						:					Tuple    =   0

													while queue:
																			_snake_case						:					List[Any]    =   queue.popleft()
																			_snake_case						:					Tuple    =   distances[current_vertex]
																			if current_distance is None:
																									continue

																			for edge in self[current_vertex]:
																									_snake_case						:					Dict    =   current_distance + edge.weight
																									_snake_case						:					str    =   distances[edge.destination_vertex]
																									if (
																									    isinstance(lowercase_				,    lowercase_    )
																									    and new_distance >= dest_vertex_distance
																									):
																															continue
																									_snake_case						:					List[Any]    =   new_distance
																									if edge.weight == 0:
																															queue.appendleft(edge.destination_vertex    )
																									else:
																															queue.append(edge.destination_vertex    )

													if distances[finish_vertex] is None:
																			raise ValueError("No path from start_vertex to finish_vertex."    )

													return distances[finish_vertex]


if __name__ == "__main__":
				import doctest

				doctest.testmod()