"""simple docstring"""




_a      :		Tuple           =   tuple[float, float, float]
_a      :		Union[str, Any]           =   tuple[float, float, float]





def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Pointad			,_lowerCamelCase						:       Pointad	)       ->      Vectorad:
  _lowerCAmelCase						:       str  			=     end_pointa[0] - end_pointa[0]
  _lowerCAmelCase						:       Union[str, Any]  			=     end_pointa[1] - end_pointa[1]
  _lowerCAmelCase						:       Dict  			=     end_pointa[2] - end_pointa[2]
  return (x, y, z)





def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Vectorad			,_lowerCamelCase						:       Vectorad	)       ->      Vectorad:
  _lowerCAmelCase						:       Any  			=     ab[1] * ac[2] - ab[2] * ac[1]  # *i
  _lowerCAmelCase						:       Tuple  			=     (ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
  _lowerCAmelCase						:       str  			=     ab[0] * ac[1] - ab[1] * ac[0]  # *k
  return (x, y, z)





def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Vectorad			,_lowerCamelCase						:       int	)       ->      bool:
  return tuple(round(_lowerCamelCase			,_lowerCamelCase	) for x in vector	) == (0, 0, 0)






def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Pointad			,_lowerCamelCase						:       Pointad			,_lowerCamelCase						:       Pointad			,_lowerCamelCase						:       int = 10	)       ->      bool:
  _lowerCAmelCase						:       str  			=     create_vector(_lowerCamelCase			,_lowerCamelCase	)
  _lowerCAmelCase						:       Optional[int]  			=     create_vector(_lowerCamelCase			,_lowerCamelCase	)
  return is_zero_vector(get_ad_vectors_cross(_lowerCamelCase			,_lowerCamelCase	)			,_lowerCamelCase	)





"""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 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Optional[Any]			,_lowerCamelCase						:       int	)       ->      List[str]:
  _lowerCAmelCase						:       Tuple  			=     k_size // 2
  _lowerCAmelCase			,	_lowerCAmelCase						:       List[str]  			=     mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  _lowerCAmelCase						:       Union[str, Any]  			=     1 / (2 * pi * sigma) * exp(-(square(_lowerCamelCase	) + square(_lowerCamelCase	)) / (2 * square(_lowerCamelCase	))	)
  return g





def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       Dict			,_lowerCamelCase						:       int			,_lowerCamelCase						:       int	)       ->      Dict:
  _lowerCAmelCase			,	_lowerCAmelCase						:       str  			=     image.shape[0], image.shape[1]
  # dst image height and width
  _lowerCAmelCase						:       Optional[int]  			=     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						:       Tuple  			=     zeros((dst_height * dst_width, k_size * k_size)	)
  _lowerCAmelCase						:       int  			=     0
  for i, j in product(range(_lowerCamelCase	)			,range(_lowerCamelCase	)	):
    _lowerCAmelCase						:       Any  			=     ravel(image[i : i + k_size, j : j + k_size]	)
    _lowerCAmelCase						:       Union[str, Any]  			=     window
    row += 1

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

  # reshape and get the dst image
  _lowerCAmelCase						:       int  			=     dot(_lowerCamelCase			,_lowerCamelCase	).reshape(_lowerCamelCase			,_lowerCamelCase	).astype(_lowerCamelCase	)

  return dst


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

     # get values with two different mask size
     _a      :		Union[str, Any]           =   gaussian_filter(gray, 3, sigma=1)
     _a      :		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()




