






'''simple docstring'''





import cva
import numpy as np
def __UpperCAmelCase (			A			:	np.ndarray	,   A			:	int	,   A			:	int	,   A			:	int						)  -> int:

   try:
      return int(image[x_coordinate][y_coordinate] >= center						)
   except (IndexError, TypeError):
      return 0
def __UpperCAmelCase (			A			:	np.ndarray	,   A			:	int	,   A			:	int						)  -> int:
   UpperCAmelCase_     :   Optional[Any]       =   image[x_coordinate][y_coordinate]
   UpperCAmelCase_     :   int       =   [1, 2, 4, 8, 1_6, 3_2, 6_4, 1_2_8]

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

   # Starting from the top right, assigning value to pixels clockwise
   UpperCAmelCase_     :   Union[str, Any]       =   [
       get_neighbors_pixel(A	,   x_coordinate - 1	,   y_coordinate + 1	,   A						),
       get_neighbors_pixel(A	,   A	,   y_coordinate + 1	,   A						),
       get_neighbors_pixel(A	,   x_coordinate - 1	,   A	,   A						),
       get_neighbors_pixel(A	,   x_coordinate + 1	,   y_coordinate + 1	,   A						),
       get_neighbors_pixel(A	,   x_coordinate + 1	,   A	,   A						),
       get_neighbors_pixel(A	,   x_coordinate + 1	,   y_coordinate - 1	,   A						),
       get_neighbors_pixel(A	,   A	,   y_coordinate - 1	,   A						),
       get_neighbors_pixel(A	,   x_coordinate - 1	,   y_coordinate - 1	,   A						),
   ]

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


if __name__ == "__main__":
      # Reading the image and converting it to grayscale.
      _UpperCamelCase		:		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
      _UpperCamelCase		:		Union[str, 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]):
                  _UpperCamelCase		:		Tuple								=			local_binary_value(image, i, j)

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










'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available


_UpperCamelCase		:		str								=			{}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase		:		List[Any]								=			['MBart50Tokenizer']

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase		:		List[str]								=			['MBart50TokenizerFast']


if TYPE_CHECKING:
						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_mbartaa import MBartaaTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_mbartaa_fast import MBartaaTokenizerFast

else:
						import sys

						_UpperCamelCase		:		Optional[int]								=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


