
'''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        A_     (						__SCREAMING_SNAKE_CASE						:  Optional[int]			,     __SCREAMING_SNAKE_CASE						:  Optional[Any] )				->       Tuple:





  """simple docstring"""

  __A		:     List[Any]												=		k_size // 2
  __A							,					__A		:     List[str]												=		mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  __A		:     Optional[int]												=		1 / (2 * pi * sigma) * exp(-(square(__SCREAMING_SNAKE_CASE ) + square(__SCREAMING_SNAKE_CASE )) / (2 * square(__SCREAMING_SNAKE_CASE )) )
  return g







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[str]			,     __SCREAMING_SNAKE_CASE						:  Tuple			,     __SCREAMING_SNAKE_CASE						:  List[Any] )				->       int:





  """simple docstring"""

  __A							,					__A		:     Tuple												=		image.shape[0], image.shape[1]
  # dst image height and width
  __A		:     List[Any]												=		height - k_size + 1
  __A		:     Tuple												=		width - k_size + 1

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

  #  turn the kernel into shape(k*k, 1)
  __A		:     Dict												=		gen_gaussian_kernel(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )
  __A		:     Optional[Any]												=		ravel(__SCREAMING_SNAKE_CASE )

  # reshape and get the dst image
  __A		:     List[Any]												=		dot(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE ).reshape(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE ).astype(__SCREAMING_SNAKE_CASE )

  return dst


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

     # get values with two different mask size
     A__   :		Dict 		=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()





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  list			,     __SCREAMING_SNAKE_CASE						:  list			,     __SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  int )				->       int:





  """simple docstring"""

  if index == number_of_items:
    return 0
  __A		:     List[Any]												=		0
  __A		:     Union[str, Any]												=		0
  __A		:     List[Any]												=		knapsack(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     index + 1 )
  if weights[index] <= max_weight:
    __A		:     Tuple												=		values[index] + knapsack(
        __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     max_weight - weights[index]			,     index + 1 )
  return max(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
     import doctest

     doctest.testmod()



