


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


class 		_SCREAMING_SNAKE_CASE    :


     def __init__(     self       ,				A_       ,				A_						):
       _UpperCAmelCase		:       Optional[Any]       =    0
       # max greyscale value for #FFFFFF
       _UpperCAmelCase		:       Any       =    int(self.get_greyscale(2_55       ,				2_55       ,				2_55						)						)

       if not self.min_threshold < threshold < self.max_threshold:
         _UpperCAmelCase		:       List[Any]       =    F'''Factor value should be from 0 to {self.max_threshold}'''
         raise ValueError(A_						)

       _UpperCAmelCase		:       Any       =    input_img
       _UpperCAmelCase		:       List[Any]       =    threshold
       _UpperCAmelCase,_UpperCAmelCase		:       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
       _UpperCAmelCase		:       List[str]       =    [
           [0 for _ in range(self.height + 4						)] for __ in range(self.width + 1						)
       ]
       _UpperCAmelCase		:       Optional[Any]       =    np.ones((self.width, self.height, 3)       ,				np.uinta						) * 2_55


     @classmethod
     def 					__snake_case(     cls       ,				A_       ,				A_       ,				A_						):
       return 0.1_1_4 * blue + 0.5_8_7 * green + 0.2_1_2_6 * red




     def 					__snake_case(     self						):
       for y in range(self.height						):
         for x in range(self.width						):
           _UpperCAmelCase		:       Tuple       =    int(self.get_greyscale(*self.input_img[y][x]						)						)
           if self.threshold > greyscale + self.error_table[y][x]:
             _UpperCAmelCase		:       Tuple       =    (0, 0, 0)
             _UpperCAmelCase		:       Union[str, Any]       =    greyscale + self.error_table[x][y]
           else:
             _UpperCAmelCase		:       int       =    (2_55, 2_55, 2_55)
             _UpperCAmelCase		:       List[Any]       =    greyscale + self.error_table[x][y] - 2_55
           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
 SCREAMING_SNAKE_CASE__				:    Any         =    [
     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()









from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available


@dataclass
class 		_SCREAMING_SNAKE_CASE    (	A    ):
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 1_5,
         '''sld_guidance_scale''': 2_0,
         '''sld_threshold''': 0.0,
         '''sld_momentum_scale''': 0.0,
         '''sld_mom_beta''': 0.0,
     }
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 1_0,
         '''sld_guidance_scale''': 1_0_0_0,
         '''sld_threshold''': 0.01,
         '''sld_momentum_scale''': 0.3,
         '''sld_mom_beta''': 0.4,
     }
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 7,
         '''sld_guidance_scale''': 2_0_0_0,
         '''sld_threshold''': 0.025,
         '''sld_momentum_scale''': 0.5,
         '''sld_mom_beta''': 0.7,
     }
     __SCREAMING_SNAKE_CASE    				=						{
         '''sld_warmup_steps''': 0,
         '''sld_guidance_scale''': 5_0_0_0,
         '''sld_threshold''': 1.0,
         '''sld_momentum_scale''': 0.5,
         '''sld_mom_beta''': 0.7,
     }


@dataclass
class 		_SCREAMING_SNAKE_CASE    (	A    ):
     __SCREAMING_SNAKE_CASE    				=						42
     __SCREAMING_SNAKE_CASE    				=						42
     __SCREAMING_SNAKE_CASE    				=						42
     __SCREAMING_SNAKE_CASE    				=						42


if is_transformers_available() and is_torch_available():
 from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
 from .safety_checker import SafeStableDiffusionSafetyChecker





