import cva
import numpy as np



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			np.ndarray					,	__UpperCamelCase       :			int					,	__UpperCamelCase       :			int					,	__UpperCamelCase       :			int      )				->   int:







  """simple docstring"""





  try:
    return int(image[x_coordinate][y_coordinate] >= center      )
  except (IndexError, TypeError):
    return 0



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			np.ndarray					,	__UpperCamelCase       :			int					,	__UpperCamelCase       :			int      )				->   int:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= image[x_coordinate][y_coordinate]
  SCREAMING_SNAKE_CASE__     				= [1, 2, 4, 8, 16, 32, 64, 1_28]

  # skip get_neighbors_pixel if center is null
  if center is None:
    return 0

  # Starting from the top right, assigning value to pixels clockwise
  SCREAMING_SNAKE_CASE__     				= [
      get_neighbors_pixel(__UpperCamelCase					,	x_coordinate - 1					,	y_coordinate + 1					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	__UpperCamelCase					,	y_coordinate + 1					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	x_coordinate - 1					,	__UpperCamelCase					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	x_coordinate + 1					,	y_coordinate + 1					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	x_coordinate + 1					,	__UpperCamelCase					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	x_coordinate + 1					,	y_coordinate - 1					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	__UpperCamelCase					,	y_coordinate - 1					,	__UpperCamelCase      ),
      get_neighbors_pixel(__UpperCamelCase					,	x_coordinate - 1					,	y_coordinate - 1					,	__UpperCamelCase      ),
  ]

  # Converting the binary value to decimal.
  return sum(
      binary_value * power for binary_value, power in zip(__UpperCamelCase					,	__UpperCamelCase      )      )


if __name__ == "__main__":
   # Reading the image and converting it to grayscale.
   __lowerCamelCase     :					List[str]				  =						cva.imread(
       '''digital_image_processing/image_data/lena.jpg''', cva.IMREAD_GRAYSCALE
   )

   # Create a numpy array as the same height and width of read image
   __lowerCamelCase     :					Optional[Any]				  =						np.zeros((image.shape[0], image.shape[1]))

   # Iterating through the image and calculating the
   # local binary pattern value for each pixel.
   for i in range(0, image.shape[0]):
      for j in range(0, image.shape[1]):
         __lowerCamelCase     :					Optional[Any]				  =						local_binary_value(image, i, j)

   cva.imshow('''local binary pattern''', lbp_image)
   cva.waitKey(0)
   cva.destroyAllWindows()

import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


__lowerCamelCase     :					Union[str, Any]				  =						logging.get_logger(__name__)







class __snake_case							(		lowerCamelCase_						):




   def __init__(       self     :							str			,      *_lowercase     :							str			,      **_lowercase     :							str ):



     """simple docstring"""






     warnings.warn(
         """The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
         """ use ViTImageProcessor instead."""			,      _lowercase			,      )
     super().__init__(*_lowercase			,      **_lowercase )
