code: 
  '''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
  
  A           =   1_8_0
  
  def   snake_case_       (							_a     :							Optional[Any] ,					_a     :							Optional[int]			):
        snake_case_						       =							k_size // 2
        snake_case_       ,	snake_case_						       =							np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
        snake_case_						       =							(
            1
            / (2 * np.pi * sigma)
            * np.exp(-(np.square(UpperCamelCase__			) + np.square(UpperCamelCase__			)) / (2 * np.square(UpperCamelCase__			))			)
        )
        return g
  
  def   snake_case_       (							_a     :							Any ,					_a     :							Optional[int] ,					_a     :							List[str]			):
        snake_case_						       =							np.zeros(UpperCamelCase__			)
  
        for row in range(1 ,					image_shape[0] - 1			):
              for col in range(1 ,					image_shape[1] - 1			):
                    snake_case_						       =							gradient_direction[row, col]
  
                    if (
                        0 <= direction < PI / 8
                        or 15 * PI / 8 <= direction <= 2 * PI
                        or 7 * PI / 8 <= direction <= 9 * PI / 8
                    ):
                          snake_case_						       =							sobel_grad[row, col - 1]
                          snake_case_						       =							sobel_grad[row, col + 1]
                          if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
                                snake_case_						       =							sobel_grad[row, col]
  
                    elif (
                        PI / 8 <= direction < 3 * PI / 8
                        or 9 * PI / 8 <= direction < 11 * PI / 8
                    ):
                          snake_case_						       =							sobel_grad[row + 1, col - 1]
                          snake_case_						       =							sobel_grad[row - 1, col + 1]
                          if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
                                snake_case_						       =							sobel_grad[row, col]
  
                    elif (
                        3 * PI / 8 <= direction < 5 * PI / 8
                        or 11 * PI / 8 <= direction < 13 * PI / 8
                    ):
                          snake_case_						       =							sobel_grad[row - 1, col]
                          snake_case_						       =							sobel_grad[row + 1, col]
                          if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
                                snake_case_						       =							sobel_grad[row, col]
  
                    elif (
                        5 * PI / 8 <= direction < 7 * PI / 8
                        or 13 * PI / 8 <= direction < 15 * PI / 8
                    ):
                          snake_case_						       =							sobel_grad[row - 1, col - 1]
                          snake_case_						       =							sobel_grad[row + 1, col + 1]
                          if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
                                snake_case_						       =							sobel_grad[row, col]
  
        return destination
  
  def   snake_case_       (							_a     :							List[str] ,					_a     :							Optional[int] ,					_a     :							Any ,					_a     :							Optional[int] ,					_a     :							Dict ,					_a     :							Dict			):
  
  
  
  
  
  
        for row in range(1 ,					image_shape[0] - 1			):
              for col in range(1 ,					image_shape[1] - 1			):
                    if destination[row, col] >= threshold_high:
                          snake_case_						       =							strong
                    elif destination[row, col] <= threshold_low:
                          snake_case_						       =							0
                    else:
                          snake_case_						       =							weak
  
  def   snake_case_       (							_a     :							List[str] ,					_a     :							Optional[Any] ,					_a     :							str ,					_a     :							List[str]			):
  
  
  
  
  
  
        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],
                          ):
                                snake_case_						       =							strong
                          else:
                                snake_case_						       =							0
  
  def   snake_case_       (							_a     :							List[Any] ,					_a     :							int=15 ,					_a     :							Union[str, Any]=30 ,					_a     :							Union[str, Any]=128 ,					_a     :							Optional[Any]=255			):
        snake_case_						       =							img_convolve(UpperCamelCase__ ,					gen_gaussian_kernel(9 ,					sigma=1.4			)			)
        # get the gradient and degree by sobel_filter
        snake_case_       ,	snake_case_						       =							sobel_filter(UpperCamelCase__			)
        snake_case_						       =							PI + np.radadeg(UpperCamelCase__			)
  
        snake_case_						       =							suppress_non_maximum(image.shape ,					UpperCamelCase__ ,					UpperCamelCase__			)
  
        detect_high_low_threshold(
            image.shape ,					UpperCamelCase__ ,					UpperCamelCase__ ,					UpperCamelCase__ ,					UpperCamelCase__ ,					UpperCamelCase__			)
  
        track_edge(image.shape ,					UpperCamelCase__ ,					UpperCamelCase__ ,					UpperCamelCase__			)
  
        return destination
  
  
  if __name__ == "__main__":
       # read original image in gray mode
       A           =   cva.imread(r"../image_data/lena.jpg", 0)
       # canny edge detection
       A           =   canny(lena)
       cva.imshow("canny", canny_destination)
       cva.waitKey(0)
  
  
style_context: 
  '''simple docstring'''
  
  
  
  
  
  def   snake_case_       (							_a     :							List[str] ,					_a     :							List[str]			):
        snake_case_						       =							1
        while b > 0:
              if b & 1:
                    res *= a
  
              a *= a
              b >>= 1
  
        return res
  def   snake_case_       (							_a     :							Union[str, Any] ,					_a     :							Tuple ,					_a     :							Optional[Any]			):
        snake_case_						       =							1
        while b > 0:
              if b & 1:
                    snake_case_						       =							((res % c) * (a % c)) % c
  
              a *= a
              b >>= 1
  
        return res
  
  