



"""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 					snake_case__       (		__lowerCamelCase    :   Union[str, Any]							,		__lowerCamelCase    :   Any     ):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]		     =k_size // 2
			lowerCamelCase__     ,       lowerCamelCase__		:		int		     =mgrid[0 - center : k_size - center, 0 - center : k_size - center]
			lowerCamelCase__		:		Dict		     =1 / (2 * pi * sigma) * exp(-(square(__lowerCamelCase     ) + square(__lowerCamelCase     )) / (2 * square(__lowerCamelCase     ))     )
			return g






def 					snake_case__       (		__lowerCamelCase    :   Tuple							,		__lowerCamelCase    :   Optional[Any]							,		__lowerCamelCase    :   List[str]     ):
			"""simple docstring"""
			lowerCamelCase__     ,       lowerCamelCase__		:		List[str]		     =image.shape[0], image.shape[1]
			# dst image height and width
			lowerCamelCase__		:		Optional[Any]		     =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__		:		str		     =zeros((dst_height * dst_width, k_size * k_size)     )
			lowerCamelCase__		:		List[Any]		     =0
			for i, j in product(range(__lowerCamelCase     )							,		range(__lowerCamelCase     )     ):
						lowerCamelCase__		:		Tuple		     =ravel(image[i : i + k_size, j : j + k_size]     )
						lowerCamelCase__		:		Dict		     =window
						row += 1

			#  turn the kernel into shape(k*k, 1)
			lowerCamelCase__		:		Optional[int]		     =gen_gaussian_kernel(__lowerCamelCase							,		__lowerCamelCase     )
			lowerCamelCase__		:		Any		     =ravel(__lowerCamelCase     )

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

			return dst


if __name__ == "__main__":
		# read original image
		_lowercase			:			str										=						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[Any]										=						gaussian_filter(gray, 3, sigma=1)
		_lowercase			:			List[str]										=						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 ..utils import DummyObject, requires_backends

class 	__SCREAMING_SNAKE_CASE     (				metaclass=lowerCAmelCase_       ):


					'''simple docstring'''





					_a             =							['torch', 'torchsde']



					def __init__(	self							:  Union[str, Any],  *lowerCamelCase							:  str,  **lowerCamelCase							:  int					)-> Tuple:
								requires_backends(self,  ['''torch''', '''torchsde''']					)



					@classmethod
					def 		snake_case	(	cls							:  List[str],  *lowerCamelCase							:  Optional[Any],  **lowerCamelCase							:  Dict					)-> str:
								requires_backends(cls,  ['''torch''', '''torchsde''']					)




					@classmethod
					def 		snake_case	(	cls							:  Tuple,  *lowerCamelCase							:  Dict,  **lowerCamelCase							:  Tuple					)-> List[str]:
								requires_backends(cls,  ['''torch''', '''torchsde''']					)




