


'''simple docstring'''


import cva
import numpy as np






def 			__lowerCAmelCase			(__lowerCAmelCase   ,			__lowerCAmelCase   ,			__lowerCAmelCase   ,			__lowerCAmelCase ):





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






def 			__lowerCAmelCase			(__lowerCAmelCase   ,			__lowerCAmelCase   ,			__lowerCAmelCase ):
		_UpperCAmelCase		:							int             =   image[x_coordinate][y_coordinate]
		_UpperCAmelCase		:							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
		_UpperCAmelCase		:							Optional[Any]             =   [
		    get_neighbors_pixel(__lowerCAmelCase   ,			x_coordinate - 1   ,			y_coordinate + 1   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			__lowerCAmelCase   ,			y_coordinate + 1   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			x_coordinate - 1   ,			__lowerCAmelCase   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			x_coordinate + 1   ,			y_coordinate + 1   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			x_coordinate + 1   ,			__lowerCAmelCase   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			x_coordinate + 1   ,			y_coordinate - 1   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			__lowerCAmelCase   ,			y_coordinate - 1   ,			__lowerCAmelCase ),
		    get_neighbors_pixel(__lowerCAmelCase   ,			x_coordinate - 1   ,			y_coordinate - 1   ,			__lowerCAmelCase ),
		]

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


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()









from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


UpperCAmelCase__    :							Tuple       		=     [
    'AutomaticSpeechRecognition',
    'AudioClassification',
    'ImageClassification',
    'LanguageModeling',
    'QuestionAnsweringExtractive',
    'Summarization',
    'TaskTemplate',
    'TextClassification',
]

UpperCAmelCase__    :							Tuple       		=     get_logger(__name__)


UpperCAmelCase__    :							List[Any]       		=     {
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}


def 		_lowerCamelCase					(       UpperCamelCase				)      ->		Optional[TaskTemplate]:





  """simple docstring"""





  _lowercase:			Union[str, Any]      =     task_template_dict.get('task'				)
  if task_name is None:
    logger.warning(F'Couldn\'t find template for task \'{task_name}\'. Available templates: {list(UpperCamelCase				)}'				)
    return None
  _lowercase:			int      =     NAMEaTEMPLATE.get(UpperCamelCase				)
  return template.from_dict(UpperCamelCase				)
