




'''simple docstring'''

import math
import sys

import cva
import numpy as np


def __UpperCAmelCase	(   _UpperCAmelCase		:   Union[str, Any]		,				_UpperCAmelCase		:   Tuple						)      ->      np.ndarray:
			# For applying gaussian function for each element in matrix.
			__snake_case			=		math.sqrt(__lowerCamelCase						)
			__snake_case			=		1 / (sigma * math.sqrt(2 * math.pi						))
			return cons * np.exp(-((img / sigma) ** 2) * 0.5						)


def __UpperCAmelCase	(   _UpperCAmelCase		:   Optional[Any]		,				_UpperCAmelCase		:   List[Any]		,				_UpperCAmelCase		:   Union[str, Any]		,				_UpperCAmelCase		:   Optional[Any]						)      ->      np.ndarray:
			__snake_case			=		kernel_size // 2
			return img[x - half : x + half + 1, y - half : y + half + 1]


def __UpperCAmelCase	(   _UpperCAmelCase		:   List[Any]		,				_UpperCAmelCase		:   Optional[Any]						)      ->      np.ndarray:
			# Creates a gaussian kernel of given dimension.
			__snake_case			=		np.zeros((kernel_size, kernel_size)						)
			for i in range(0		,				__lowerCamelCase						):
						for j in range(0		,				__lowerCamelCase						):
									__snake_case			=		math.sqrt(
									    abs(i - kernel_size // 2						) ** 2 + abs(j - kernel_size // 2						) ** 2						)
			return vec_gaussian(__lowerCamelCase		,				__lowerCamelCase						)


def __UpperCAmelCase	(   _UpperCAmelCase		:   Any		,				_UpperCAmelCase		:   List[Any]		,				_UpperCAmelCase		:   str		,				_UpperCAmelCase		:   Dict		,				)      ->      np.ndarray:
			__snake_case			=		np.zeros(img.shape						)
			__snake_case			=		get_gauss_kernel(__lowerCamelCase		,				__lowerCamelCase						)
			__snake_case		,     __snake_case			=		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						):
									__snake_case			=		get_slice(__lowerCamelCase		,				__lowerCamelCase		,				__lowerCamelCase		,				__lowerCamelCase						)
									__snake_case			=		img_s - img_s[kernel_size // 2, kernel_size // 2]
									__snake_case			=		vec_gaussian(__lowerCamelCase		,				__lowerCamelCase						)
									__snake_case			=		np.multiply(__lowerCamelCase		,				__lowerCamelCase						)
									__snake_case			=		np.multiply(__lowerCamelCase		,				__lowerCamelCase						)
									__snake_case			=		np.sum(__lowerCamelCase						) / np.sum(__lowerCamelCase						)
									__snake_case			=		val
			return imga


def __UpperCAmelCase	(   _UpperCAmelCase		:   int						)      ->      tuple:
			__snake_case			=		args[1] if args[1:] else "../image_data/lena.jpg"
			__snake_case			=		float(args[2]						) if args[2:] else 1.0
			__snake_case			=		float(args[3]						) if args[3:] else 1.0
			if args[4:]:
						__snake_case			=		int(args[4]						)
						__snake_case			=		kernel_size + abs(kernel_size % 2 - 1						)
			else:
						__snake_case			=		5
			return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
						a       :						Optional[int]								=		parse_args(sys.argv)
						a       :						Union[str, Any]								=		cva.imread(filename, 0)
						cva.imshow('''input image''', img)

						a       :						Any								=		img / 255
						a       :						Dict								=		out.astype('''float32''')
						a       :						Union[str, Any]								=		bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
						a       :						Any								=		out * 255
						a       :						Optional[int]								=		np.uinta(out)
						cva.imshow('''output image''', out)
						cva.waitKey(0)
						cva.destroyAllWindows()











import os





def 						__A						(      ) ->			Dict:
	with open(os.path.dirname(__lowerCamelCase       ) + """/p022_names.txt"""       ) as file:
		a									=				str(file.readlines()[0]       )
		a									=				names.replace("""\""""				,     """"""       ).split(""","""       )

	names.sort()

	a									=				0
	a									=				0

	for i, name in enumerate(__lowerCamelCase       ):
		for letter in name:
			name_score += ord(__lowerCamelCase       ) - 64

		total_score += (i + 1) * name_score
		a									=				0
	return total_score


if __name__ == "__main__":
		print(solution())

