


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 	_lowerCAmelCase					( UpperCamelCase__:  str				,       UpperCamelCase__:  Union[str, Any]    )			-> Optional[Any]:





	"""simple docstring"""







	A             =					k_size // 2
	A             =					mgrid[0 - center : k_size - center, 0 - center : k_size - center]
	A             =					1 / (2 * pi * sigma) * exp(-(square(_lowercase    ) + square(_lowercase    )) / (2 * square(_lowercase    ))    )
	return g





def 	_lowerCAmelCase					( UpperCamelCase__:  List[str]				,       UpperCamelCase__:  Optional[int]				,       UpperCamelCase__:  str    )			-> Optional[Any]:





	"""simple docstring"""







	A             =					image.shape[0], image.shape[1]
	# dst image height and width
	A             =					height - k_size + 1
	A             =					width - k_size + 1

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

	#  turn the kernel into shape(k*k, 1)
	A             =					gen_gaussian_kernel(_lowercase				,       _lowercase    )
	A             =					ravel(_lowercase    )

	# reshape and get the dst image
	A             =					dot(_lowercase				,       _lowercase    ).reshape(_lowercase				,       _lowercase    ).astype(_lowercase    )

	return dst


if __name__ == "__main__":
				# read original image
				_lowercase							:   Optional[Any]						=						imread(R"../image_data/lena.jpg")
				# turn image in gray scale value
				_lowercase							:   int						=						cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				_lowercase							:   Optional[int]						=						gaussian_filter(gray, 3, sigma=1)
				_lowercase							:   List[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()










from ..utils import DummyObject, requires_backends


class       __lowerCAmelCase					(       metaclass=_UpperCamelCase      ):


	'''simple docstring'''





	_A													=				["note_seq"]

	def __init__(						self:						int,					*lowerCamelCase_:						Optional[int],					**lowerCamelCase_:						Tuple			):
			requires_backends(self,					['note_seq']			)

	@classmethod
	def    snake_case__(						cls:						Optional[Any],					*lowerCamelCase_:						Tuple,					**lowerCamelCase_:						Optional[Any]			):
			requires_backends(cls,					['note_seq']			)





	@classmethod
	def    snake_case__(						cls:						Any,					*lowerCamelCase_:						Dict,					**lowerCamelCase_:						str			):
			requires_backends(cls,					['note_seq']			)


