code: 
  
  
  
  
  
  
  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       = 180
  
  
  
  
  
  
  
  def       lowerCAmelCase__(	lowercase       :    Any   ,     lowercase       :    int				) ->    Dict:
    __snake_case   :				Union[str, Any]        =       k_size // 2
    __snake_case   :				Dict        =       np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
    __snake_case   :				Dict        =       (
        1
        / (2 * np.pi * sigma)
        * np.exp(-(np.square(lowercase				) + np.square(lowercase				)) / (2 * np.square(lowercase				))				)
    )
    return g
  
  
  
  
  
  
  
  def       lowerCAmelCase__(	lowercase       :    List[str]   ,     lowercase       :    List[str]   ,     lowercase       :    int				) ->    List[Any]:
    __snake_case   :				Union[str, Any]        =       np.zeros(lowercase				)
  
    for row in range(1   ,     image_shape[0] - 1				):
      for col in range(1   ,     image_shape[1] - 1				):
        __snake_case   :				Union[str, Any]        =       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   :				Any        =       sobel_grad[row, col - 1]
          __snake_case   :				Union[str, Any]        =       sobel_grad[row, col + 1]
          if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
            __snake_case   :				Any        =       sobel_grad[row, col]
  
        elif (
            PI / 8 <= direction < 3 * PI / 8
            or 9 * PI / 8 <= direction < 11 * PI / 8
        ):
          __snake_case   :				List[str]        =       sobel_grad[row + 1, col - 1]
          __snake_case   :				Optional[Any]        =       sobel_grad[row - 1, col + 1]
          if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
            __snake_case   :				List[str]        =       sobel_grad[row, col]
  
        elif (
            3 * PI / 8 <= direction < 5 * PI / 8
            or 11 * PI / 8 <= direction < 13 * PI / 8
        ):
          __snake_case   :				Optional[int]        =       sobel_grad[row - 1, col]
          __snake_case   :				Optional[int]        =       sobel_grad[row + 1, col]
          if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
            __snake_case   :				Union[str, Any]        =       sobel_grad[row, col]
  
        elif (
            5 * PI / 8 <= direction < 7 * PI / 8
            or 13 * PI / 8 <= direction < 15 * PI / 8
        ):
          __snake_case   :				int        =       sobel_grad[row - 1, col - 1]
          __snake_case   :				Any        =       sobel_grad[row + 1, col + 1]
          if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
            __snake_case   :				Optional[Any]        =       sobel_grad[row, col]
  
    return destination
  
  
  
  
  
  
  
  def       lowerCAmelCase__(	lowercase       :    str   ,     lowercase       :    List[str]   ,     lowercase       :    Dict   ,     lowercase       :    List[str]   ,     lowercase       :    Union[str, Any]   ,     lowercase       :    Optional[int]				) ->    Union[str, 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:
          __snake_case   :				List[str]        =       strong
        elif destination[row, col] <= threshold_low:
          __snake_case   :				str        =       0
        else:
          __snake_case   :				Dict        =       weak
  
  
  
  
  
  
  
  def       lowerCAmelCase__(	lowercase       :    Optional[int]   ,     lowercase       :    Any   ,     lowercase       :    List[str]   ,     lowercase       :    Dict				) ->    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   :				List[Any]        =       strong
          else:
            __snake_case   :				str        =       0
  
  
  
  
  
  
  
  def       lowerCAmelCase__(	lowercase       :    Dict   ,     lowercase       :    Any=15   ,     lowercase       :    Dict=30   ,     lowercase       :    Optional[int]=128   ,     lowercase       :    Union[str, Any]=255				) ->    Optional[Any]:
    # gaussian_filter
    __snake_case   :				int        =       img_convolve(lowercase   ,     gen_gaussian_kernel(9   ,     sigma=1.4				)				)
    # get the gradient and degree by sobel_filter
    __snake_case   :				int        =       sobel_filter(lowercase				)
    __snake_case   :				str        =       PI + np.radadeg(lowercase				)
  
    __snake_case   :				str        =       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       = cva.imread(R'''../image_data/lena.jpg''', 0)
       # canny edge detection
       _UpperCamelCase       = canny(lena)
       cva.imshow('''canny''', canny_destination)
       cva.waitKey(0)
  
  
style_context: 
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  _UpperCamelCase       = {
      '''configuration_deta''': ['''DETA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetaConfig'''],
  }
  
  try:
       if not is_vision_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _UpperCamelCase       = ['''DetaImageProcessor''']
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _UpperCamelCase       = [
           '''DETA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''DetaForObjectDetection''',
           '''DetaModel''',
           '''DetaPreTrainedModel''',
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig
  
       try:
            if not is_vision_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .image_processing_deta import DetaImageProcessor
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_deta import (
                DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
                DetaForObjectDetection,
                DetaModel,
                DetaPreTrainedModel,
            )
  
  else:
       import sys
  
       _UpperCamelCase       = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  