


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


class        A_					:




      '''simple docstring'''


      def __init__(				self:       List[str]						,      a:       Tuple						,      a:       int				):
       __lowerCamelCase		:							List[Any]							=						0
       # max greyscale value for #FFFFFF
       __lowerCamelCase		:							List[Any]							=						int(self.get_greyscale(255						,      255						,      255				)				)

       if not self.min_threshold < threshold < self.max_threshold:
        __lowerCamelCase		:							str							=						F'Factor value should be from 0 to {self.max_threshold}'
        raise ValueError(a				)

       __lowerCamelCase		:							str							=						input_img
       __lowerCamelCase		:							int							=						threshold
       __lowerCamelCase					,     __lowerCamelCase		:							Tuple							=						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
       __lowerCamelCase		:							Optional[int]							=						[
           [0 for _ in range(self.height + 4				)] for __ in range(self.width + 1				)
       ]
       __lowerCamelCase		:							Tuple							=						np.ones((self.width, self.height, 3)						,      np.uinta				) * 255




      @classmethod
      def      _snake_case	(				cls:       Any						,      a:       int						,      a:       int						,      a:       int				):
       return 0.1_1_4 * blue + 0.5_8_7 * green + 0.2_1_2_6 * red




      def      _snake_case	(				self:       Dict				):
       for y in range(self.height				):
        for x in range(self.width				):
         __lowerCamelCase		:							List[Any]							=						int(self.get_greyscale(*self.input_img[y][x]				)				)
         if self.threshold > greyscale + self.error_table[y][x]:
          __lowerCamelCase		:							Tuple							=						(0, 0, 0)
          __lowerCamelCase		:							List[Any]							=						greyscale + self.error_table[x][y]
         else:
          __lowerCamelCase		:							Optional[Any]							=						(255, 255, 255)
          __lowerCamelCase		:							Optional[Any]							=						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
       lowercase_           =	[
           Burkes(imread('image_data/lena.jpg', 1), threshold)
           for threshold in (1, 1_2_6, 1_3_0, 1_4_0)
       ]

       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()





from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


lowercase_           =	datasets.utils.logging.get_logger(__name__)


class        A_					(       folder_based_builder.FolderBasedBuilderConfig    ):




      '''simple docstring'''


      __snake_case					       =   None
      __snake_case					       =   None



class        A_					(       folder_based_builder.FolderBasedBuilder    ):




      '''simple docstring'''


      __snake_case					       =   datasets.Image()
      __snake_case					       =   """image"""
      __snake_case					       =   ImageFolderConfig
      __snake_case					       =   42  # definition at the bottom of the script
      __snake_case					       =   ImageClassification(image_column="""image"""					,      label_column="""label"""    )



lowercase_           =	[
    '.blp',
    '.bmp',
    '.dib',
    '.bufr',
    '.cur',
    '.pcx',
    '.dcx',
    '.dds',
    '.ps',
    '.eps',
    '.fit',
    '.fits',
    '.fli',
    '.flc',
    '.ftc',
    '.ftu',
    '.gbr',
    '.gif',
    '.grib',
    '.h5',
    '.hdf',
    '.png',
    '.apng',
    '.jp2',
    '.j2k',
    '.jpc',
    '.jpf',
    '.jpx',
    '.j2c',
    '.icns',
    '.ico',
    '.im',
    '.iim',
    '.tif',
    '.tiff',
    '.jfif',
    '.jpe',
    '.jpg',
    '.jpeg',
    '.mpg',
    '.mpeg',
    '.msp',
    '.pcd',
    '.pxr',
    '.pbm',
    '.pgm',
    '.ppm',
    '.pnm',
    '.psd',
    '.bw',
    '.rgb',
    '.rgba',
    '.sgi',
    '.ras',
    '.tga',
    '.icb',
    '.vda',
    '.vst',
    '.webp',
    '.wmf',
    '.emf',
    '.xbm',
    '.xpm',
]
lowercase_           =	IMAGE_EXTENSIONS

