



"""simple docstring"""




import cva
import numpy as np

def      A_ (		__a       :			List[str]	,						__a       :			Optional[int]	,						__a       :			Optional[Any]	,						__a       :			Tuple						):

				"""simple docstring"""







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

def      A_ (		__a       :			Tuple	,						__a       :			Optional[Any]	,						__a       :			Union[str, Any]						):

				"""simple docstring"""
				a__			 =						image[x_coordinate][y_coordinate]
				a__			 =						[1, 2, 4, 8, 16, 32, 64, 128]

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

				# Starting from the top right, assigning value to pixels clockwise
				a__			 =						[
				    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.
	UpperCAmelCase								=   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								=   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								=   local_binary_value(image, i, j)

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






from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase								=   logging.get_logger(__name__)

UpperCAmelCase								=   {
    """facebook/regnet-y-040""": """https://huggingface.co/facebook/regnet-y-040/blob/main/config.json""",
}

class 	__snake_case (				SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__			: Tuple             =   """regnet"""
							UpperCamelCase__			: int             =   ["""x""", """y"""]


							def __init__(							self					,					a_=3					,					a_=32					,					a_=[128, 192, 512, 1_088]					,					a_=[2, 6, 12, 2]					,					a_=64					,					a_="y"					,					a_="relu"					,					**a_					,					):
											super().__init__(**a_						)
											if layer_type not in self.layer_types:
															raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types						)}'''						)
											a__			 =						num_channels
											a__			 =						embedding_size
											a__			 =						hidden_sizes
											a__			 =						depths
											a__			 =						groups_width
											a__			 =						layer_type
											a__			 =						hidden_act
											# always downsample in the first stage
											a__			 =						True

