
"""simple docstring"""


from typing import TYPE_CHECKING

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


lowerCAmelCase			=		{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase			=		["""SplinterTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase			=		[
							    """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """SplinterForQuestionAnswering""",
							    """SplinterForPreTraining""",
							    """SplinterLayer""",
							    """SplinterModel""",
							    """SplinterPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
							from .tokenization_splinter import SplinterTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_splinter_fast import SplinterTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_splinter import (
														    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    SplinterForPreTraining,
														    SplinterForQuestionAnswering,
														    SplinterLayer,
														    SplinterModel,
														    SplinterPreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase			=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

"""simple docstring"""


import cva
import numpy as np






def      lowerCAmelCase_     (	snake_case_	:    np.ndarray							,					snake_case_	:    int							,					snake_case_	:    int							,					snake_case_	:    int    )     ->int:

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






def      lowerCAmelCase_     (	snake_case_	:    np.ndarray							,					snake_case_	:    int							,					snake_case_	:    int    )     ->int:
			lowerCamelCase__			:  Optional[int]  =image[x_coordinate][y_coordinate]
			lowerCamelCase__			:  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
			lowerCamelCase__			:  int  =[
			    get_neighbors_pixel(snake_case_							,					x_coordinate - 1							,					y_coordinate + 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					snake_case_							,					y_coordinate + 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate - 1							,					snake_case_							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate + 1							,					y_coordinate + 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate + 1							,					snake_case_							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate + 1							,					y_coordinate - 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					snake_case_							,					y_coordinate - 1							,					snake_case_    ),
			    get_neighbors_pixel(snake_case_							,					x_coordinate - 1							,					y_coordinate - 1							,					snake_case_    ),
			]

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


if __name__ == "__main__":
							# Reading the image and converting it to grayscale.
							lowerCAmelCase			=		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			=		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			=		local_binary_value(image, i, j)

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