"""simple docstring"""
import cva
import numpy as np

from digital_image_processing.filters.convolve import img_convolve
from digital_image_processing.filters.sobel_filter import sobel_filter

lowercase__   			=      180







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Union[str, Any]:
  a__:	List[str]     				=      k_size // 2
  a__				,       a__:	Union[str, Any]     				=      np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  a__:	Tuple     				=      (
      1
      / (2 * np.pi * sigma)
      * np.exp(-(np.square(_SCREAMING_SNAKE_CASE  ) + np.square(_SCREAMING_SNAKE_CASE  )) / (2 * np.square(_SCREAMING_SNAKE_CASE  ))  )
  )
  return g







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Optional[int]:
  a__:	Union[str, Any]     				=      np.zeros(_SCREAMING_SNAKE_CASE  )

  for row in range(1						,	image_shape[0] - 1  ):
    for col in range(1						,	image_shape[1] - 1  ):
      a__:	int     				=      gradient_direction[row, col]

      if (
          0 <= direction < PI / 8
          or 15 * PI / 8 <= direction <= 2 * PI
          or 7 * PI / 8 <= direction <= 9 * PI / 8
      ):
        a__:	List[Any]     				=      sobel_grad[row, col - 1]
        a__:	Any     				=      sobel_grad[row, col + 1]
        if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
          a__:	Optional[Any]     				=      sobel_grad[row, col]

      elif (
          PI / 8 <= direction < 3 * PI / 8
          or 9 * PI / 8 <= direction < 11 * PI / 8
      ):
        a__:	Optional[int]     				=      sobel_grad[row + 1, col - 1]
        a__:	int     				=      sobel_grad[row - 1, col + 1]
        if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
          a__:	int     				=      sobel_grad[row, col]

      elif (
          3 * PI / 8 <= direction < 5 * PI / 8
          or 11 * PI / 8 <= direction < 13 * PI / 8
      ):
        a__:	List[Any]     				=      sobel_grad[row - 1, col]
        a__:	List[str]     				=      sobel_grad[row + 1, col]
        if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
          a__:	List[str]     				=      sobel_grad[row, col]

      elif (
          5 * PI / 8 <= direction < 7 * PI / 8
          or 13 * PI / 8 <= direction < 15 * PI / 8
      ):
        a__:	Tuple     				=      sobel_grad[row - 1, col - 1]
        a__:	str     				=      sobel_grad[row + 1, col + 1]
        if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
          a__:	Optional[Any]     				=      sobel_grad[row, col]

  return destination







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Any:
  for row in range(1						,	image_shape[0] - 1  ):
    for col in range(1						,	image_shape[1] - 1  ):
      if destination[row, col] >= threshold_high:
        a__:	Union[str, Any]     				=      strong
      elif destination[row, col] <= threshold_low:
        a__:	Dict     				=      0
      else:
        a__:	int     				=      weak







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->int:
  for row in range(1						,	image_shape[0]  ):
    for col in range(1						,	image_shape[1]  ):
      if destination[row, col] == weak:
        if 255 in (
            destination[row, col + 1],
            destination[row, col - 1],
            destination[row - 1, col],
            destination[row + 1, col],
            destination[row - 1, col - 1],
            destination[row + 1, col - 1],
            destination[row - 1, col + 1],
            destination[row + 1, col + 1],
        ):
          a__:	Optional[int]     				=      strong
        else:
          a__:	List[str]     				=      0







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE=15						,	_SCREAMING_SNAKE_CASE=30						,	_SCREAMING_SNAKE_CASE=128						,	_SCREAMING_SNAKE_CASE=255  )      ->Tuple:
  # gaussian_filter
  a__:	Union[str, Any]     				=      img_convolve(_SCREAMING_SNAKE_CASE						,	gen_gaussian_kernel(9						,	sigma=1.4  )  )
  # get the gradient and degree by sobel_filter
  a__				,       a__:	Optional[int]     				=      sobel_filter(_SCREAMING_SNAKE_CASE  )
  a__:	Optional[Any]     				=      PI + np.radadeg(_SCREAMING_SNAKE_CASE  )

  a__:	Tuple     				=      suppress_non_maximum(image.shape						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  detect_high_low_threshold(
      image.shape						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  track_edge(image.shape						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  return destination


if __name__ == "__main__":
 # read original image in gray mode
 lowercase__   			=      cva.imread(r'../image_data/lena.jpg', 0)
 # canny edge detection
 lowercase__   			=      canny(lena)
 cva.imshow('canny', canny_destination)
 cva.waitKey(0)








def        lowerCamelCase_     (     SCREAMING_SNAKE_CASE ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE     =       len(SCREAMING_SNAKE_CASE )
			SCREAMING_SNAKE_CASE     =       [0] * length
			SCREAMING_SNAKE_CASE     =       [[False for i in range(SCREAMING_SNAKE_CASE )] for j in range(SCREAMING_SNAKE_CASE )]
			for i, c in enumerate(SCREAMING_SNAKE_CASE ):
						SCREAMING_SNAKE_CASE     =       i
						for j in range(i + 1 ):
									if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
												SCREAMING_SNAKE_CASE     =       True
												SCREAMING_SNAKE_CASE     =       min(SCREAMING_SNAKE_CASE       ,						0 if j == 0 else (cut[j - 1] + 1) )
						SCREAMING_SNAKE_CASE     =       mincut
			return cut[length - 1]


if __name__ == "__main__":
		__A    :				Optional[int]    						=	input("""Enter the string: """).strip()
		__A    :				List[Any]    						=	find_minimum_partitions(s)
		print(f'''Minimum number of partitions required for the \'{s}\' is {ans}''')






