





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 						A_							(	_lowerCAmelCase				,  _lowerCAmelCase	)		->					str:
 UpperCamelCase      :   List[Any]			      =  k_size // 2
 UpperCamelCase      ,       UpperCamelCase      :   Any			      =  mgrid[0 - center : k_size - center, 0 - center : k_size - center]
 UpperCamelCase      :   List[Any]			      =  1 / (2 * pi * sigma) * exp(-(square(lowerCAmelCase__	) + square(lowerCAmelCase__	)) / (2 * square(lowerCAmelCase__	))	)
 return g



def 						A_							(	_lowerCAmelCase				,  _lowerCAmelCase				,  _lowerCAmelCase	)		->					Optional[int]:
 UpperCamelCase      ,       UpperCamelCase      :   Any			      =  image.shape[0], image.shape[1]
 # dst image height and width
 UpperCamelCase      :   Optional[Any]			      =  height - k_size + 1
 UpperCamelCase      :   List[Any]			      =  width - k_size + 1

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

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

 # reshape and get the dst image
 UpperCamelCase      :   Optional[Any]			      =  dot(lowerCAmelCase__				,  lowerCAmelCase__	).reshape(lowerCAmelCase__				,  lowerCAmelCase__	).astype(lowerCAmelCase__	)

 return dst


if __name__ == "__main__":
    # read original image
    __lowerCamelCase			:	Union[str, Any]					    =	imread(r"""../image_data/lena.jpg""")
    # turn image in gray scale value
    __lowerCamelCase			:	Dict					    =	cvtColor(img, COLOR_BGR2GRAY)

    # get values with two different mask size
    __lowerCamelCase			:	Any					    =	gaussian_filter(gray, 3, sigma=1)
    __lowerCamelCase			:	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 collections.abc import Sequence






def  lowerCamelCase_	(      lowerCAmelCase__	:	Sequence[int] | None = None				)       ->							int:

							'''simple docstring'''






							if nums is None or not nums:
														raise ValueError('Input sequence should not be empty'				)

							A      						=    nums[0]
							for i in range(1			,	len(lowerCAmelCase__				)				):
														A      						=    nums[i]
														A      						=    max(lowerCAmelCase__			,	ans + num			,	lowerCAmelCase__				)

							return ans


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				# Try on a sample input from the user
				__snake_case     :str			       =int(input('Enter number of elements : ').strip())
				__snake_case     :Optional[int]			       =list(map(int, input('\nEnter the numbers : ').strip().split()))[:n]
				print(max_subsequence_sum(array))