



from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros


def 						UpperCAmelCase__   (   UpperCAmelCase__			:Union[str, Any]			,       UpperCAmelCase__			:Dict       ):






 '''simple docstring'''

 a		,	a							=		image.shape
 a							=		cols - block_size[1] + 1
 a							=		rows - block_size[0] + 1
 a							=		zeros((dst_height * dst_width, block_size[1] * block_size[0])       )
 a							=		0
 for i in range(0			,       UpperCAmelCase__       ):
  for j in range(0			,       UpperCAmelCase__       ):
   a							=		ravel(image[i : i + block_size[0], j : j + block_size[1]]       )
   a							=		window
   row += 1

 return image_array


def 						UpperCAmelCase__   (   UpperCAmelCase__			:Any			,       UpperCAmelCase__			:int       ):






 '''simple docstring'''

 a		,	a							=		image.shape[0], image.shape[1]
 a							=		filter_kernel.shape[0]
 a							=		k_size // 2
 # Pads image with the edge values of array.
 a							=		pad(UpperCAmelCase__			,       UpperCAmelCase__			,       mode="edge"       )

 # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
 a							=		imacol(UpperCAmelCase__			,       (k_size, k_size)       )

 #  turn the kernel into shape(k*k, 1)
 a							=		ravel(UpperCAmelCase__       )
 # reshape and get the dst image
 a							=		dot(UpperCAmelCase__			,       UpperCAmelCase__       ).reshape(UpperCAmelCase__			,       UpperCAmelCase__       )
 return dst


if __name__ == "__main__":
     # read original image
     A_		:  Union[str, Any]										=  imread(r'''../image_data/lena.jpg''')
     # turn image in gray scale value
     A_		:  Dict										=  cvtColor(img, COLOR_BGR2GRAY)
     # Laplace operator
     A_		:  Optional[int]										=  array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
     A_		:  str										=  img_convolve(gray, Laplace_kernel).astype(uinta)
     imshow('''Laplacian''', out)
     waitKey(0)




"""simple docstring"""





def     _A    (    UpperCamelCase_	:			int,     UpperCamelCase_	:			int = 1000)      ->		str:
   '''simple docstring'''


   if (not isinstance(UpperCamelCase_,     UpperCamelCase_)) or (digit_position <= 0):
      raise ValueError("Digit position must be a positive integer")
   elif (not isinstance(UpperCamelCase_,     UpperCamelCase_)) or (precision < 0):
      raise ValueError("Precision must be a nonnegative integer")

   # compute an approximation of (16 ** (n - 1)) * pi whose fractional part is mostly
   # accurate
   __lowercase								=		(
       4 * _subsum(UpperCamelCase_,     1,     UpperCamelCase_)
       - 2 * _subsum(UpperCamelCase_,     4,     UpperCamelCase_)
       - _subsum(UpperCamelCase_,     5,     UpperCamelCase_)
       - _subsum(UpperCamelCase_,     6,     UpperCamelCase_)
   )

   # return the first hex digit of the fractional part of the result
   return hex(int((sum_result % 1) * 16))[2:]




def     _A    (    UpperCamelCase_	:			int,     UpperCamelCase_	:			int,     UpperCamelCase_	:			int)      ->		float:
   '''simple docstring'''


   __lowercase								=		0.0
   for sum_index in range(digit_pos_to_extract + precision):
      __lowercase								=		8 * sum_index + denominator_addend
      if sum_index < digit_pos_to_extract:
         # if the exponential term is an integer and we mod it by the denominator
         # before dividing, only the integer part of the sum will change;
         # the fractional part will not
         __lowercase								=		pow(
             16,     digit_pos_to_extract - 1 - sum_index,     UpperCamelCase_)
      else:
         __lowercase								=		pow(16,     digit_pos_to_extract - 1 - sum_index)
      total += exponential_term / denominator
   return total


if __name__ == "__main__":
   import doctest

   doctest.testmod()




