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
  
  lowerCAmelCase__   	=				1_80
  def 							_UpperCAmelCase       (UpperCamelCase__  :						Optional[Any]       ,							UpperCamelCase__  :						Optional[Any]		):
         _A   : int       					=				k_size // 2
         _A					,    _A   : Tuple       					=				np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
         _A   : Union[str, Any]       					=				(
             1
             / (2 * np.pi * sigma)
             * np.exp(-(np.square(UpperCamelCase__		) + np.square(UpperCamelCase__		)) / (2 * np.square(UpperCamelCase__		))		)
         )
         return g
  def 							_UpperCAmelCase       (UpperCamelCase__  :						str       ,							UpperCamelCase__  :						Any       ,							UpperCamelCase__  :						Tuple		):
         _A   : Optional[int]       					=				np.zeros(UpperCamelCase__		)
  
         for row in range(1       ,							image_shape[0] - 1		):
                for col in range(1       ,							image_shape[1] - 1		):
                       _A   : 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
                       ):
                              _A   : Dict       					=				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   : List[Any]       					=				sobel_grad[row, col]
  
                       elif (
                           PI / 8 <= direction < 3 * PI / 8
                           or 9 * PI / 8 <= direction < 11 * PI / 8
                       ):
                              _A   : List[str]       					=				sobel_grad[row + 1, col - 1]
                              _A   : str       					=				sobel_grad[row - 1, col + 1]
                              if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
                                     _A   : List[Any]       					=				sobel_grad[row, col]
  
                       elif (
                           3 * PI / 8 <= direction < 5 * PI / 8
                           or 11 * PI / 8 <= direction < 13 * PI / 8
                       ):
                              _A   : Any       					=				sobel_grad[row - 1, col]
                              _A   : int       					=				sobel_grad[row + 1, col]
                              if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
                                     _A   : Any       					=				sobel_grad[row, col]
  
                       elif (
                           5 * PI / 8 <= direction < 7 * PI / 8
                           or 13 * PI / 8 <= direction < 15 * PI / 8
                       ):
                              _A   : List[str]       					=				sobel_grad[row - 1, col - 1]
                              _A   : Optional[Any]       					=				sobel_grad[row + 1, col + 1]
                              if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
                                     _A   : List[Any]       					=				sobel_grad[row, col]
  
         return destination
  def 							_UpperCAmelCase       (UpperCamelCase__  :						Dict       ,							UpperCamelCase__  :						Optional[Any]       ,							UpperCamelCase__  :						str       ,							UpperCamelCase__  :						Dict       ,							UpperCamelCase__  :						Optional[Any]       ,							UpperCamelCase__  :						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   : Optional[int]       					=				strong
                       elif destination[row, col] <= threshold_low:
                              _A   : Optional[int]       					=				0
                       else:
                              _A   : Union[str, Any]       					=				weak
  def 							_UpperCAmelCase       (UpperCamelCase__  :						Optional[Any]       ,							UpperCamelCase__  :						Optional[int]       ,							UpperCamelCase__  :						Any       ,							UpperCamelCase__  :						Any		):
         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   : str       					=				strong
                              else:
                                     _A   : Any       					=				0
  def 							_UpperCAmelCase       (UpperCamelCase__  :						Dict       ,							UpperCamelCase__  :						int=15       ,							UpperCamelCase__  :						Dict=30       ,							UpperCamelCase__  :						int=128       ,							UpperCamelCase__  :						Union[str, Any]=255		):
         # gaussian_filter
         _A   : Union[str, Any]       					=				img_convolve(UpperCamelCase__       ,							gen_gaussian_kernel(9       ,							sigma=1.4		)		)
         # get the gradient and degree by sobel_filter
         _A					,    _A   : Dict       					=				sobel_filter(UpperCamelCase__		)
         _A   : Tuple       					=				PI + np.radadeg(UpperCamelCase__		)
  
         _A   : Optional[int]       					=				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
      lowerCAmelCase__   	=				cva.imread(R'../image_data/lena.jpg', 0)
      # canny edge detection
      lowerCAmelCase__   	=				canny(lena)
      cva.imshow('canny', canny_destination)
      cva.waitKey(0)
  
style_context: 
  
  
  import importlib
  import inspect
  from functools import wraps
  from typing import TYPE_CHECKING, Optional, Union
  
  from .download.streaming_download_manager import (
      xbasename,
      xdirname,
      xet_parse,
      xexists,
      xgetsize,
      xglob,
      xgzip_open,
      xisdir,
      xisfile,
      xjoin,
      xlistdir,
      xnumpy_load,
      xopen,
      xpandas_read_csv,
      xpandas_read_excel,
      xPath,
      xrelpath,
      xsio_loadmat,
      xsplit,
      xsplitext,
      xwalk,
      xxml_dom_minidom_parse,
  )
  from .utils.logging import get_logger
  from .utils.patching import patch_submodule
  from .utils.py_utils import get_imports
  
  
  lowerCAmelCase__   	=				get_logger(__name__)
  
  
  if TYPE_CHECKING:
      from .builder import DatasetBuilder
  def 							_UpperCAmelCase       (UpperCamelCase__  :						Optional[Any]       ,							UpperCamelCase__  :						Optional[Union[str, bool]] = None		):
         _A   : Dict       					=				importlib.import_module(UpperCamelCase__		)
  
         # TODO(QL): always update the module to add subsequent new authentication
         if hasattr(UpperCamelCase__       ,							"_patched_for_streaming"		) and module._patched_for_streaming:
                return
  
         def wrap_auth(UpperCamelCase__  :						Optional[int]		):
                @wraps(UpperCamelCase__		)
                def wrapper(*UpperCamelCase__  :						str       ,							**UpperCamelCase__  :						Optional[int]		):
                       return function(*UpperCamelCase__       ,							use_auth_token=UpperCamelCase__       ,							**UpperCamelCase__		)
  
                _A   : List[Any]       					=				"wrap_auth"
                return wrapper
  
         # open files in a streaming fashion
         patch_submodule(UpperCamelCase__       ,							"open"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"os.listdir"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"os.walk"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"glob.glob"       ,							wrap_auth(UpperCamelCase__		)		).start()
         # allow to navigate in remote zip files
         patch_submodule(UpperCamelCase__       ,							"os.path.join"       ,							UpperCamelCase__		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.dirname"       ,							UpperCamelCase__		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.basename"       ,							UpperCamelCase__		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.relpath"       ,							UpperCamelCase__		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.split"       ,							UpperCamelCase__		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.splitext"       ,							UpperCamelCase__		).start()
         # allow checks on paths
         patch_submodule(UpperCamelCase__       ,							"os.path.exists"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.isdir"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.isfile"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"os.path.getsize"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"pathlib.Path"       ,							UpperCamelCase__		).start()
         # file readers
         patch_submodule(UpperCamelCase__       ,							"gzip.open"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"numpy.load"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"pandas.read_csv"       ,							wrap_auth(UpperCamelCase__		)       ,							attrs=["__version__"]		).start()
         patch_submodule(UpperCamelCase__       ,							"pandas.read_excel"       ,							wrap_auth(UpperCamelCase__		)       ,							attrs=["__version__"]		).start()
         patch_submodule(UpperCamelCase__       ,							"scipy.io.loadmat"       ,							wrap_auth(UpperCamelCase__		)       ,							attrs=["__version__"]		).start()
         patch_submodule(UpperCamelCase__       ,							"xml.etree.ElementTree.parse"       ,							wrap_auth(UpperCamelCase__		)		).start()
         patch_submodule(UpperCamelCase__       ,							"xml.dom.minidom.parse"       ,							wrap_auth(UpperCamelCase__		)		).start()
         _A   : Any       					=				True
  
  
  
  
  
  
  def 							_UpperCAmelCase       (UpperCamelCase__  :						"DatasetBuilder"		):
         extend_module_for_streaming(builder.__module__       ,							use_auth_token=builder.use_auth_token		)
         # if needed, we also have to extend additional internal imports (like wmt14 -> wmt_utils)
         if not builder.__module__.startswith("datasets."		):  # check that it's not a packaged builder like csv
                for imports in get_imports(inspect.getfile(builder.__class__		)		):
                       if imports[0] == "internal":
                              _A   : Optional[Any]       					=				imports[1]
                              _A   : int       					=				".".join(builder.__module__.split("."		)[:-1] + [internal_import_name]		)
                              extend_module_for_streaming(UpperCamelCase__       ,							use_auth_token=builder.use_auth_token		)
  
      # builders can inherit from other builders that might use streaming functionality
      # (for example, ImageFolder and AudioFolder inherit from FolderBuilder which implements examples generation)
      # but these parents builders are not patched automatically as they are not instantiated, so we patch them here
         from .builder import DatasetBuilder
  
         _A   : Tuple       					=				[
             cls.__module__
             for cls in type(UpperCamelCase__		).__mro__[1:]  # make sure it's not the same module we've already patched
             if issubclass(cls       ,							UpperCamelCase__		) and cls.__module__ != DatasetBuilder.__module__
         ]  # check it's not a standard builder from datasets.builder
         for module in parent_builder_modules:
                extend_module_for_streaming(UpperCamelCase__       ,							use_auth_token=builder.use_auth_token		)
  