


'''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

__UpperCAmelCase     :Optional[int]												=  1_8_0




def       _a      (		_lowercase   :      int     ,   _lowercase   :      Optional[int]    ):





     '''simple docstring'''






     __UpperCAmelCase      :					Tuple    				=     k_size // 2
     __UpperCAmelCase				,  __UpperCAmelCase      :					Optional[Any]    				=     np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
     __UpperCAmelCase      :					List[str]    				=     (
         1
         / (2 * np.pi * sigma)
         * np.exp(-(np.square(_lowercase    ) + np.square(_lowercase    )) / (2 * np.square(_lowercase    ))    )
     )
     return g




def       _a      (		_lowercase   :      Union[str, Any]     ,   _lowercase   :      int     ,   _lowercase   :      Dict    ):





     '''simple docstring'''






     __UpperCAmelCase      :					Dict    				=     np.zeros(_lowercase    )

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

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

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

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

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

     return destination




def       _a      (		_lowercase   :      Optional[Any]     ,   _lowercase   :      List[Any]     ,   _lowercase   :      Union[str, Any]     ,   _lowercase   :      int     ,   _lowercase   :      str     ,   _lowercase   :      Union[str, Any]    ):





     '''simple docstring'''






     for row in range(1     ,   image_shape[0] - 1    ):
          for col in range(1     ,   image_shape[1] - 1    ):
               if destination[row, col] >= threshold_high:
                    __UpperCAmelCase      :					int    				=     strong
               elif destination[row, col] <= threshold_low:
                    __UpperCAmelCase      :					List[str]    				=     0
               else:
                    __UpperCAmelCase      :					int    				=     weak




def       _a      (		_lowercase   :      List[Any]     ,   _lowercase   :      Dict     ,   _lowercase   :      List[Any]     ,   _lowercase   :      Union[str, Any]    ):





     '''simple docstring'''






     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],
                    ):
                         __UpperCAmelCase      :					str    				=     strong
                    else:
                         __UpperCAmelCase      :					Union[str, Any]    				=     0




def       _a      (		_lowercase   :      List[str]     ,   _lowercase   :      Optional[Any]=15     ,   _lowercase   :      Optional[int]=30     ,   _lowercase   :      Optional[int]=128     ,   _lowercase   :      Tuple=255    ):





     '''simple docstring'''






     __UpperCAmelCase      :					Optional[Any]    				=     img_convolve(_lowercase     ,   gen_gaussian_kernel(9     ,   sigma=1.4    )    )
     # get the gradient and degree by sobel_filter
     __UpperCAmelCase				,  __UpperCAmelCase      :					str    				=     sobel_filter(_lowercase    )
     __UpperCAmelCase      :					Any    				=     PI + np.radadeg(_lowercase    )

     __UpperCAmelCase      :					List[Any]    				=     suppress_non_maximum(image.shape     ,   _lowercase     ,   _lowercase    )

     detect_high_low_threshold(
         image.shape     ,   _lowercase     ,   _lowercase     ,   _lowercase     ,   _lowercase     ,   _lowercase    )

     track_edge(image.shape     ,   _lowercase     ,   _lowercase     ,   _lowercase    )

     return destination


if __name__ == "__main__":
      # read original image in gray mode
      __UpperCAmelCase     :Optional[Any]												=  cva.imread(r"../image_data/lena.jpg", 0)
      # canny edge detection
      __UpperCAmelCase     :int												=  canny(lena)
      cva.imshow("canny", canny_destination)
      cva.waitKey(0)



'''simple docstring'''



import re




def       _a      (		_lowercase   :      List[Any]    ):





     '''simple docstring'''






     def docstring_decorator(_lowercase   :      str    ):
          __UpperCAmelCase      :					Tuple    				=     fn.__doc__
          __UpperCAmelCase      :					Tuple    				=     func_doc.split('''\n'''    )
          __UpperCAmelCase      :					Optional[Any]    				=     0
          while i < len(_lowercase    ) and re.search(R'''^\s*Examples?:\s*$'''     ,   lines[i]    ) is None:
               i += 1
          if i < len(_lowercase    ):
               __UpperCAmelCase      :					Optional[int]    				=     example_docstring
               __UpperCAmelCase      :					Tuple    				=     '''\n'''.join(_lowercase    )
          else:
               raise ValueError(
                   F'The function {fn} should have an empty \'Examples:\' in its docstring as placeholder, '
                   F'current docstring is:\n{func_doc}'    )
          __UpperCAmelCase      :					Tuple    				=     func_doc
          return fn

     return docstring_decorator