




from PIL import Image

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Image	):


      '''simple docstring'''



      lowerCamelCase_							=       image.size
      lowerCamelCase_							=       0
      lowerCamelCase_							=       image.load()
      for i in range(lowerCamelCase_	):
            for j in range(lowerCamelCase_	):
                  lowerCamelCase_							=       pixels[j, i]
                  mean += pixel
      mean //= width * height

      for j in range(lowerCamelCase_	):
            for i in range(lowerCamelCase_	):
                  lowerCamelCase_							=       2_55 if pixels[i, j] > mean else 0
      return image


if __name__ == "__main__":
 lowerCamelCase							:						Any					       =  mean_threshold(Image.open("path_to_image").convert("L"))
 image.save("output_image_path")









from ....configuration_utils import PretrainedConfig
from ....utils import logging


UpperCamelCase__ :   Any						=							logging.get_logger(__name__)

UpperCamelCase__ :   Any						=							{
    '''Visual-Attention-Network/van-base''': (
        '''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
    ),
}







class 				lowerCAmelCase_       (					lowerCamelCase_							):
				__a     :       List[Any]						=     "van"






				def __init__(			self      ,snake_case__=224      ,snake_case__=3      ,snake_case__=[7, 3, 3, 3]      ,snake_case__=[4, 2, 2, 2]      ,snake_case__=[64, 128, 320, 512]      ,snake_case__=[3, 3, 12, 3]      ,snake_case__=[8, 8, 4, 4]      ,snake_case__="gelu"      ,snake_case__=0.02      ,snake_case__=1E-6      ,snake_case__=1E-2      ,snake_case__=0.0      ,snake_case__=0.0      ,**snake_case__      ,):
							super().__init__(**snake_case__ )
							SCREAMING_SNAKE_CASE_   : Tuple					  =      image_size
							SCREAMING_SNAKE_CASE_   : List[str]					  =      num_channels
							SCREAMING_SNAKE_CASE_   : Dict					  =      patch_sizes
							SCREAMING_SNAKE_CASE_   : str					  =      strides
							SCREAMING_SNAKE_CASE_   : str					  =      hidden_sizes
							SCREAMING_SNAKE_CASE_   : str					  =      depths
							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      mlp_ratios
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      hidden_act
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      initializer_range
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      layer_norm_eps
							SCREAMING_SNAKE_CASE_   : int					  =      layer_scale_init_value
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      drop_path_rate
							SCREAMING_SNAKE_CASE_   : List[str]					  =      dropout_rate



