




"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


__A 		=			{
    "configuration_speech_to_text_2": ["SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Speech2Text2Config"],
    "processing_speech_to_text_2": ["Speech2Text2Processor"],
    "tokenization_speech_to_text_2": ["Speech2Text2Tokenizer"],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __A 		=			[
           "SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST",
           "Speech2Text2ForCausalLM",
           "Speech2Text2PreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
       from .processing_speech_to_text_a import SpeechaTextaProcessor
       from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_speech_to_text_a import (
                  SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                  SpeechaTextaForCausalLM,
                  SpeechaTextaPreTrainedModel,
              )

else:
       import sys

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







"""simple docstring"""

import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class 			lowerCamelCase__    :


			def __init__(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case		:						int								=				0
					# max greyscale value for #FFFFFF
					snake_case		:						List[str]								=				int(self.get_greyscale(255				, 255				, 255							)							)

					if not self.min_threshold < threshold < self.max_threshold:
							snake_case		:						Union[str, Any]								=				F'''Factor value should be from 0 to {self.max_threshold}'''
							raise ValueError(SCREAMING_SNAKE_CASE							)

					snake_case		:						str								=				input_img
					snake_case		:						Optional[Any]								=				threshold
					snake_case			,				snake_case		:						List[str]								=				self.input_img.shape[1], self.input_img.shape[0]

					# error table size (+4 columns and +1 row) greater than input image because of
					# lack of if statements
					snake_case		:						Union[str, Any]								=				[
					    [0 for _ in range(self.height + 4							)] for __ in range(self.width + 1							)
					]
					snake_case		:						Tuple								=				np.ones((self.width, self.height, 3)				, np.uinta							) * 255


			@classmethod
			def 							lowerCamelCase_				(     cls				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return 0.1_14 * blue + 0.5_87 * green + 0.21_26 * red



			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







					for y in range(self.height							):
							for x in range(self.width							):
									snake_case		:						Dict								=				int(self.get_greyscale(*self.input_img[y][x]							)							)
									if self.threshold > greyscale + self.error_table[y][x]:
											snake_case		:						List[str]								=				(0, 0, 0)
											snake_case		:						List[Any]								=				greyscale + self.error_table[x][y]
									else:
											snake_case		:						int								=				(255, 255, 255)
											snake_case		:						Tuple								=				greyscale + self.error_table[x][y] - 255
									self.error_table[y][x + 1] += int(8 / 32 * current_error							)
									self.error_table[y][x + 2] += int(4 / 32 * current_error							)
									self.error_table[y + 1][x] += int(8 / 32 * current_error							)
									self.error_table[y + 1][x + 1] += int(4 / 32 * current_error							)
									self.error_table[y + 1][x + 2] += int(2 / 32 * current_error							)
									self.error_table[y + 1][x - 1] += int(4 / 32 * current_error							)
									self.error_table[y + 1][x - 2] += int(2 / 32 * current_error							)


if __name__ == "__main__":
							# create Burke's instances with original images in greyscale
							__A 		=			[
							    Burkes(imread("image_data/lena.jpg", 1), threshold)
							    for threshold in (1, 126, 130, 140)
							]

							for burkes in burkes_instances:
														burkes.process()

							for burkes in burkes_instances:
														imshow(
														    f'Original image with dithering threshold: {burkes.threshold}',
														    burkes.output_img,
														)

							waitKey(0)
							destroyAllWindows()

