

import cva
import numpy as np

def 	lowerCamelCase__	(   _a							,     _a							,     _a							,     _a):







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

def 	lowerCamelCase__	(   _a							,     _a							,     _a):
 SCREAMING_SNAKE_CASE				: Optional[Any]			       =    image[x_coordinate][y_coordinate]
 SCREAMING_SNAKE_CASE				: Union[str, Any]			       =    [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
 SCREAMING_SNAKE_CASE				: Tuple			       =    [
     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.
   a_         =      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
   a_         =      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]):
         a_         =      local_binary_value(image, i, j)

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


from typing import TYPE_CHECKING

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


a_         =      {
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      ['CodeGenTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_         =      [
			    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CodeGenForCausalLM',
			    'CodeGenModel',
			    'CodeGenPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
			from .tokenization_codegen import CodeGenTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_codegen_fast import CodeGenTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_codegen import (
						    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CodeGenForCausalLM,
						    CodeGenModel,
						    CodeGenPreTrainedModel,
						)

else:
			import sys

			a_         =      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)