



import cva
import numpy as np

def      A_ (		__a       :			np.ndarray	,						__a       :			int	,						__a       :			int	,						__a       :			int						):

				"""simple docstring"""

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

def      A_ (		__a       :			np.ndarray	,						__a       :			int	,						__a       :			int						):

				"""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(__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								=   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 __future__ import annotations

def      A_ (		__a       :			list[int | float]						):

				"""simple docstring"""
				if len(__a						) == 0:
								raise ValueError("""find_max() arg is an empty sequence"""						)
				a__			 =						nums[0]
				for x in nums:
								if x > max_num:
												a__			 =						x
				return max_num


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)

