



'''simple docstring'''





import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCAmelCase										=     logging.get_logger(__name__)

_lowerCAmelCase										=     {
    '''nvidia/segformer-b0-finetuned-ade-512-512''': (
        '''https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'''
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}






class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
  '''simple docstring'''




  __lowercase							:				List[str]           =				'''segformer'''




  def __init__(   self  ,__UpperCAmelCase=3  ,__UpperCAmelCase=4  ,__UpperCAmelCase=[2, 2, 2, 2]  ,__UpperCAmelCase=[8, 4, 2, 1]  ,__UpperCAmelCase=[32, 64, 160, 256]  ,__UpperCAmelCase=[7, 3, 3, 3]  ,__UpperCAmelCase=[4, 2, 2, 2]  ,__UpperCAmelCase=[1, 2, 5, 8]  ,__UpperCAmelCase=[4, 4, 4, 4]  ,__UpperCAmelCase="gelu"  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase=1E-6  ,__UpperCAmelCase=256  ,__UpperCAmelCase=255  ,**__UpperCAmelCase  ,)   ->		Union[str, Any]:
      super().__init__(**__UpperCAmelCase				)

      if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
          warnings.warn(
              """Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be"""
              """ removed, as the behaviour will default to that of reshape_last_stage = True."""  ,__UpperCAmelCase  ,)

      lowerCAmelCase__			:  Optional[int]											= num_channels
      lowerCAmelCase__			:  str											= num_encoder_blocks
      lowerCAmelCase__			:  str											= depths
      lowerCAmelCase__			:  Dict											= sr_ratios
      lowerCAmelCase__			:  Union[str, Any]											= hidden_sizes
      lowerCAmelCase__			:  Union[str, Any]											= patch_sizes
      lowerCAmelCase__			:  Any											= strides
      lowerCAmelCase__			:  List[Any]											= mlp_ratios
      lowerCAmelCase__			:  Union[str, Any]											= num_attention_heads
      lowerCAmelCase__			:  List[str]											= hidden_act
      lowerCAmelCase__			:  Union[str, Any]											= hidden_dropout_prob
      lowerCAmelCase__			:  Optional[Any]											= attention_probs_dropout_prob
      lowerCAmelCase__			:  Optional[Any]											= classifier_dropout_prob
      lowerCAmelCase__			:  List[str]											= initializer_range
      lowerCAmelCase__			:  Optional[Any]											= drop_path_rate
      lowerCAmelCase__			:  List[Any]											= layer_norm_eps
      lowerCAmelCase__			:  Optional[Any]											= decoder_hidden_size
      lowerCAmelCase__			:  Tuple											= kwargs.get("""reshape_last_stage"""  ,__UpperCAmelCase				)
      lowerCAmelCase__			:  Union[str, Any]											= semantic_loss_ignore_index







class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
  '''simple docstring'''




  __lowercase							:				List[Any]           =				version.parse('''1.11'''					)




  @property
  def 							UpperCAmelCase_     (   self				)   ->		Mapping[str, Mapping[int, str]]:
      return OrderedDict(
          [
              ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
          ]				)




  @property
  def 							UpperCAmelCase_     (   self				)   ->		float:
      return 1E-4






  @property
  def 							UpperCAmelCase_     (   self				)   ->		int:
      return 12







'''simple docstring'''





from PIL import Image
def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





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

    for j in range(UpperCamelCase      ):
        for i in range(UpperCamelCase      ):
            lowerCAmelCase__			:  Dict											= 255 if pixels[i, j] > mean else 0
    return image


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


