



"""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

lowerCamelCase				:     str								=  1_8_0


def 							A__ (     UpperCamelCase__       ,							UpperCamelCase__    ):


  '''simple docstring'''


  _SCREAMING_SNAKE_CASE        =			k_size // 2
  _SCREAMING_SNAKE_CASE    ,     _SCREAMING_SNAKE_CASE        =			np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  _SCREAMING_SNAKE_CASE        =			(
      1
      / (2 * np.pi * sigma)
      * np.exp(-(np.square(lowercase__    ) + np.square(lowercase__    )) / (2 * np.square(lowercase__    ))    )
  )
  return g


def 							A__ (     UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__    ):


  '''simple docstring'''


  _SCREAMING_SNAKE_CASE        =			np.zeros(lowercase__    )

  for row in range(1       ,							image_shape[0] - 1    ):
    for col in range(1       ,							image_shape[1] - 1    ):
      _SCREAMING_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
      ):
        _SCREAMING_SNAKE_CASE        =			sobel_grad[row, col - 1]
        _SCREAMING_SNAKE_CASE        =			sobel_grad[row, col + 1]
        if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
          _SCREAMING_SNAKE_CASE        =			sobel_grad[row, col]

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

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

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

  return destination


def 							A__ (     UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__    ):


  '''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:
        _SCREAMING_SNAKE_CASE        =			strong
      elif destination[row, col] <= threshold_low:
        _SCREAMING_SNAKE_CASE        =			0
      else:
        _SCREAMING_SNAKE_CASE        =			weak


def 							A__ (     UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__    ):


  '''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],
        ):
          _SCREAMING_SNAKE_CASE        =			strong
        else:
          _SCREAMING_SNAKE_CASE        =			0


def 							A__ (     UpperCamelCase__       ,							UpperCamelCase__=15       ,							UpperCamelCase__=30       ,							UpperCamelCase__=128       ,							UpperCamelCase__=255    ):


  '''simple docstring'''


  _SCREAMING_SNAKE_CASE        =			img_convolve(lowercase__       ,							gen_gaussian_kernel(9       ,							sigma=1.4    )    )
  # get the gradient and degree by sobel_filter
  _SCREAMING_SNAKE_CASE    ,     _SCREAMING_SNAKE_CASE        =			sobel_filter(lowercase__    )
  _SCREAMING_SNAKE_CASE        =			PI + np.radadeg(lowercase__    )

  _SCREAMING_SNAKE_CASE        =			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
    lowerCamelCase				:     List[str]								=  cva.imread(r"""../image_data/lena.jpg""", 0)
    # canny edge detection
    lowerCamelCase				:     str								=  canny(lena)
    cva.imshow("""canny""", canny_destination)
    cva.waitKey(0)





from typing import TYPE_CHECKING

from ...utils import _LazyModule


_lowercase				:					List[Any]     					={"""tokenization_bert_japanese""": ["""BertJapaneseTokenizer""", """CharacterTokenizer""", """MecabTokenizer"""]}


if TYPE_CHECKING:
	from .tokenization_bert_japanese import BertJapaneseTokenizer, CharacterTokenizer, MecabTokenizer

else:
	import sys

	_lowercase				:					Union[str, Any]     					=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

