




from typing import Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_images
from ...utils import TensorType, logging


lowerCAmelCase_						=			logging.get_logger(__name__)
class 						_A (  _lowerCamelCase				):






  """simple docstring"""




  _UpperCamelCase       :      Union[str, Any]			=      ['''pixel_values''']






  def __init__(  self		:     List[str]				,						_A		:     bool = True				,						_A		:     Union[int, float] = 1 / 255				,						_A		:     bool = True				,						_A		:     int = 8				,						**_A		:     List[Any]				,						)		->   None:






       """simple docstring"""







       super().__init__(**_A				)

       lowercase :       Union[str, Any]       =			do_rescale
       lowercase :       Tuple       =			rescale_factor
       lowercase :       Any       =			do_pad
       lowercase :       Dict       =			pad_size






  def  __a      (  self		:     Any				,						_A		:     np.ndarray				,						_A		:     float				,						_A		:     Optional[Union[str, ChannelDimension]] = None				,						**_A		:     Optional[Any]				)		->   np.ndarray:






       """simple docstring"""







       return rescale(_A				,						scale=_A				,						data_format=_A				,						**_A				)






  def  __a      (  self		:     int				,						_A		:     np.ndarray				,						_A		:     int				,						_A		:     Optional[Union[str, ChannelDimension]] = None				)		->   List[str]:






       """simple docstring"""







       lowercase :       Optional[int]       =			get_image_size(_A				)
       lowercase :       str       =			(old_height // size + 1) * size - old_height
       lowercase :       Any       =			(old_width // size + 1) * size - old_width

       return pad(_A				,						((0, pad_height), (0, pad_width))				,						mode='''symmetric'''				,						data_format=_A				)






  def  __a      (  self		:     Any				,						_A		:     ImageInput				,						_A		:     Optional[bool] = None				,						_A		:     Optional[float] = None				,						_A		:     Optional[bool] = None				,						_A		:     Optional[int] = None				,						_A		:     Optional[Union[str, TensorType]] = None				,						_A		:     Union[str, ChannelDimension] = ChannelDimension.FIRST				,						**_A		:     List[Any]				,						)		->   Optional[Any]:






       """simple docstring"""







       lowercase :       List[str]       =			do_rescale if do_rescale is not None else self.do_rescale
       lowercase :       str       =			rescale_factor if rescale_factor is not None else self.rescale_factor
       lowercase :       int       =			do_pad if do_pad is not None else self.do_pad
       lowercase :       Optional[Any]       =			pad_size if pad_size is not None else self.pad_size

       lowercase :       List[str]       =			make_list_of_images(_A				)

       if not valid_images(_A				):
            raise ValueError(
                '''Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '''
                '''torch.Tensor, tf.Tensor or jax.ndarray.'''				)

       if do_rescale and rescale_factor is None:
            raise ValueError('''Rescale factor must be specified if do_rescale is True.'''				)

       # All transformations expect numpy arrays.
       lowercase :       str       =			[to_numpy_array(_A				) for image in images]

       if do_rescale:
            lowercase :       Union[str, Any]       =			[self.rescale(image=_A				,						scale=_A				) for image in images]

       if do_pad:
            lowercase :       Any       =			[self.pad(_A				,						size=_A				) for image in images]

       lowercase :       str       =			[to_channel_dimension_format(_A				,						_A				) for image in images]

       lowercase :       Tuple       =			{'''pixel_values''': images}
       return BatchFeature(data=_A				,						tensor_type=_A				)





import os
from collections.abc import Iterator






def  snake_case(    __magic_name__ = "."   )			->							Iterator[str]:





     '''simple docstring'''


     for dir_path, dir_names, filenames in os.walk(__magic_name__   ):
          lowercase :       Tuple       =			[d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
          for filename in filenames:
               if filename == "__init__.py":
                    continue
               if os.path.splitext(__magic_name__   )[1] in (".py", ".ipynb"):
                    yield os.path.join(__magic_name__			,		__magic_name__   ).lstrip('''./'''   )






def  snake_case(    __magic_name__   )			->							Dict:





     '''simple docstring'''


     return F"""{i * '  '}*""" if i else "\n##"






def  snake_case(    __magic_name__			,		__magic_name__   )			->							str:





     '''simple docstring'''


     lowercase :       Dict       =			old_path.split(os.sep   )
     for i, new_part in enumerate(new_path.split(os.sep   )   ):
          if (i + 1 > len(__magic_name__   ) or old_parts[i] != new_part) and new_part:
               print(F"""{md_prefix(__magic_name__   )} {new_part.replace('_'			,		' '   ).title()}"""   )
     return new_path






def  snake_case(    __magic_name__ = "."   )			->							None:





     '''simple docstring'''


     lowercase :       str       =			''''''
     for filepath in sorted(good_file_paths(__magic_name__   )   ):
          lowercase      ,	lowercase :       Optional[int]       =			os.path.split(__magic_name__   )
          if filepath != old_path:
               lowercase :       str       =			print_path(__magic_name__			,		__magic_name__   )
          lowercase :       Optional[int]       =			(filepath.count(os.sep   ) + 1) if filepath else 0
          lowercase :       Optional[Any]       =			F"""{filepath}/{filename}""".replace(''' '''			,		'''%20'''   )
          lowercase :       List[str]       =			os.path.splitext(filename.replace('''_'''			,		''' '''   ).title()   )[0]
          print(F"""{md_prefix(__magic_name__   )} [{filename}]({url})"""   )


if __name__ == "__main__":
 print_directory_md('.')