
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey



class       a_   :






			def __init__(			self							, __UpperCamelCase							, __UpperCamelCase     ):
									_lowercase									=				0
									# max greyscale value for #FFFFFF
									_lowercase									=				int(self.get_greyscale(255							, 255							, 255     )     )

									if not self.min_threshold < threshold < self.max_threshold:
															_lowercase									=				f"""Factor value should be from 0 to {self.max_threshold}"""
															raise ValueError(__UpperCamelCase     )

									_lowercase									=				input_img
									_lowercase									=				threshold
									_lowercase					,	_lowercase									=				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
									_lowercase									=				[
									    [0 for _ in range(self.height + 4     )] for __ in range(self.width + 1     )
									]
									_lowercase									=				np.ones((self.width, self.height, 3)							, np.uinta     ) * 255






			@classmethod
			def       UpperCamelCase_							(			cls							, __UpperCamelCase							, __UpperCamelCase							, __UpperCamelCase     ):
									return 0.1_14 * blue + 0.5_87 * green + 0.21_26 * red






			def       UpperCamelCase_							(			self     ):
									for y in range(self.height     ):
															for x in range(self.width     ):
																					_lowercase									=				int(self.get_greyscale(*self.input_img[y][x]     )     )
																					if self.threshold > greyscale + self.error_table[y][x]:
																											_lowercase									=				(0, 0, 0)
																											_lowercase									=				greyscale + self.error_table[x][y]
																					else:
																											_lowercase									=				(255, 255, 255)
																											_lowercase									=				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()

import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


A		:   Optional[int]         =    TypeVar('''T''', bound='''TaskTemplate''')



@dataclass(frozen=_a						)
class       a_   ( abc.ABC						):
			# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
			a  : str
			a  : ClassVar[Features]
			a  : ClassVar[Features]






			def       UpperCamelCase_							(			self							, __UpperCamelCase     ):
									return copy.deepcopy(self     )






			@property
			def       UpperCamelCase_							(			self     ):
									return Features(**self.input_schema							, **self.label_schema     )






			@property
			@abc.abstractmethod
			def       UpperCamelCase_							(			self     ):
									raise NotImplementedError






			@classmethod
			def       UpperCamelCase_							(			cls							, __UpperCamelCase     ):
									_lowercase									=				{f.name for f in dataclasses.fields(cls     )}
									return cls(**{k: v for k, v in template_dict.items() if k in field_names}     )