





'''simple docstring'''

import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
   import PIL.Image

   from .features import FeatureType


lowercase__		:     Optional[List[str]]			=							None
lowercase__		:     List[Any]			=							'<' if sys.byteorder == 'little' else '>'
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
lowercase__		:     int			=							[
    np.dtype('|b1'),
    np.dtype('|u1'),
    np.dtype('<u2'),
    np.dtype('>u2'),
    np.dtype('<i2'),
    np.dtype('>i2'),
    np.dtype('<u4'),
    np.dtype('>u4'),
    np.dtype('<i4'),
    np.dtype('>i4'),
    np.dtype('<f4'),
    np.dtype('>f4'),
    np.dtype('<f8'),
    np.dtype('>f8'),
]
@dataclass
class 							__lowerCAmelCase	:






       """simple docstring"""
       _snake_case      :	bool									=       True
       _snake_case      :	Optional[str]									=       None
       # Automatically constructed
       _snake_case      :	ClassVar[str]									=       "PIL.Image.Image"
       _snake_case      :	ClassVar[Any]									=       pa.struct({'bytes': pa.binary(), 'path': pa.string()}					)
       _snake_case      :	str									=       field(default='Image'		,		init=__magic_name__		,		repr=__magic_name__					)





       def __call__(				self  :						Any	)       ->	str:

            '''simple docstring'''




            return self.pa_type





       def snake_case__		(				self  :						Dict			,					lowerCAmelCase__  :						Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]	)       ->	dict:

            '''simple docstring'''




            if config.PIL_AVAILABLE:
                 import PIL.Image
            else:
                 raise ImportError('''To support encoding images, please install \'Pillow\'.'''	)

            if isinstance(lowerCAmelCase__			,					lowerCAmelCase__	):
                 _UpperCamelCase							       =			np.array(lowerCAmelCase__	)

            if isinstance(lowerCAmelCase__			,					lowerCAmelCase__	):
                 return {"path": value, "bytes": None}
            elif isinstance(lowerCAmelCase__			,					lowerCAmelCase__	):
                 return {"path": None, "bytes": value}
            elif isinstance(lowerCAmelCase__			,					np.ndarray	):
                 # convert the image array to PNG/TIFF bytes
                 return encode_np_array(lowerCAmelCase__	)
            elif isinstance(lowerCAmelCase__			,					PIL.Image.Image	):
                 # convert the PIL image to bytes (default format is PNG/TIFF)
                 return encode_pil_image(lowerCAmelCase__	)
            elif value.get('''path'''	) is not None and os.path.isfile(value['''path''']	):
                 # we set "bytes": None to not duplicate the data if they're already available locally
                 return {"bytes": None, "path": value.get('''path'''	)}
            elif value.get('''bytes'''	) is not None or value.get('''path'''	) is not None:
                 # store the image bytes, and path is used to infer the image format using the file extension
                 return {"bytes": value.get('''bytes'''	), "path": value.get('''path'''	)}
            else:
                 raise ValueError(
                     f"""An image sample should have one of 'path' or 'bytes' but they are missing or None in {value}."""	)





       def snake_case__		(				self  :						Tuple			,					lowerCAmelCase__  :						dict			,					lowerCAmelCase__  :						Dict=None	)       ->	"PIL.Image.Image":

            '''simple docstring'''




            if not self.decode:
                 raise RuntimeError('''Decoding is disabled for this feature. Please use Image(decode=True) instead.'''	)

            if config.PIL_AVAILABLE:
                 import PIL.Image
            else:
                 raise ImportError('''To support decoding images, please install \'Pillow\'.'''	)

            if token_per_repo_id is None:
                 _UpperCamelCase							       =			{}

            _UpperCamelCase       ,							_UpperCamelCase							       =			value['''path'''], value['''bytes''']
            if bytes_ is None:
                 if path is None:
                      raise ValueError(f"""An image should have one of 'path' or 'bytes' but both are None in {value}."""	)
                 else:
                      if is_local_path(lowerCAmelCase__	):
                           _UpperCamelCase							       =			PIL.Image.open(lowerCAmelCase__	)
                      else:
                           _UpperCamelCase							       =			path.split('''::'''	)[-1]
                           try:
                                _UpperCamelCase							       =			string_to_dict(lowerCAmelCase__			,					config.HUB_DATASETS_URL	)['''repo_id''']
                                _UpperCamelCase							       =			token_per_repo_id.get(lowerCAmelCase__	)
                           except ValueError:
                                _UpperCamelCase							       =			None
                           with xopen(lowerCAmelCase__			,					'''rb'''			,					use_auth_token=lowerCAmelCase__	) as f:
                                _UpperCamelCase							       =			BytesIO(f.read()	)
                           _UpperCamelCase							       =			PIL.Image.open(bytes_	)
            else:
                 _UpperCamelCase							       =			PIL.Image.open(BytesIO(bytes_	)	)
            image.load()  # to avoid "Too many open files" errors
            return image





       def snake_case__		(				self  :						List[str]	)       ->	Union["FeatureType", Dict[str, "FeatureType"]]:

            '''simple docstring'''




            from .features import Value

            return (
                self
                if self.decode
                else {
                    "bytes": Value('''binary'''	),
                    "path": Value('''string'''	),
                }
            )





       def snake_case__		(				self  :						int			,					lowerCAmelCase__  :						Union[pa.StringArray, pa.StructArray, pa.ListArray]	)       ->	pa.StructArray:

            '''simple docstring'''




            if pa.types.is_string(storage.type	):
                 _UpperCamelCase							       =			pa.array([None] * len(lowerCAmelCase__	)			,					type=pa.binary()	)
                 _UpperCamelCase							       =			pa.StructArray.from_arrays([bytes_array, storage]			,					['''bytes''', '''path''']			,					mask=storage.is_null()	)
            elif pa.types.is_binary(storage.type	):
                 _UpperCamelCase							       =			pa.array([None] * len(lowerCAmelCase__	)			,					type=pa.string()	)
                 _UpperCamelCase							       =			pa.StructArray.from_arrays([storage, path_array]			,					['''bytes''', '''path''']			,					mask=storage.is_null()	)
            elif pa.types.is_struct(storage.type	):
                 if storage.type.get_field_index('''bytes'''	) >= 0:
                      _UpperCamelCase							       =			storage.field('''bytes'''	)
                 else:
                      _UpperCamelCase							       =			pa.array([None] * len(lowerCAmelCase__	)			,					type=pa.binary()	)
                 if storage.type.get_field_index('''path'''	) >= 0:
                      _UpperCamelCase							       =			storage.field('''path'''	)
                 else:
                      _UpperCamelCase							       =			pa.array([None] * len(lowerCAmelCase__	)			,					type=pa.string()	)
                 _UpperCamelCase							       =			pa.StructArray.from_arrays([bytes_array, path_array]			,					['''bytes''', '''path''']			,					mask=storage.is_null()	)
            elif pa.types.is_list(storage.type	):
                 _UpperCamelCase							       =			pa.array(
                     [encode_np_array(np.array(lowerCAmelCase__	)	)['''bytes'''] if arr is not None else None for arr in storage.to_pylist()]			,					type=pa.binary()			,					)
                 _UpperCamelCase							       =			pa.array([None] * len(lowerCAmelCase__	)			,					type=pa.string()	)
                 _UpperCamelCase							       =			pa.StructArray.from_arrays(
                     [bytes_array, path_array]			,					['''bytes''', '''path''']			,					mask=bytes_array.is_null()	)
            return array_cast(lowerCAmelCase__			,					self.pa_type	)







       def snake_case__		(				self  :						Union[str, Any]			,					lowerCAmelCase__  :						pa.StructArray	)       ->	pa.StructArray:

            '''simple docstring'''




            @no_op_if_value_is_null
            def path_to_bytes(lowerCAmelCase__  :						Optional[Any]	):
                 with xopen(lowerCAmelCase__			,					'''rb'''	) as f:
                      _UpperCamelCase							       =			f.read()
                 return bytes_

            _UpperCamelCase							       =			pa.array(
                [
                    (path_to_bytes(x['''path''']	) if x['''bytes'''] is None else x['''bytes''']) if x is not None else None
                    for x in storage.to_pylist()
                ]			,					type=pa.binary()			,					)
            _UpperCamelCase							       =			pa.array(
                [os.path.basename(lowerCAmelCase__	) if path is not None else None for path in storage.field('''path'''	).to_pylist()]			,					type=pa.string()			,					)
            _UpperCamelCase							       =			pa.StructArray.from_arrays([bytes_array, path_array]			,					['''bytes''', '''path''']			,					mask=bytes_array.is_null()	)
            return array_cast(lowerCAmelCase__			,					self.pa_type	)







def    a__							(							)						->						List[str]:





     """simple docstring"""

     if config.PIL_AVAILABLE:
          import PIL.Image
     else:
          raise ImportError('''To support encoding images, please install \'Pillow\'.''' )

     global _IMAGE_COMPRESSION_FORMATS
     if _IMAGE_COMPRESSION_FORMATS is None:
          PIL.Image.init()
          _UpperCamelCase							       =			list(set(PIL.Image.OPEN.keys() ) & set(PIL.Image.SAVE.keys() ) )
     return _IMAGE_COMPRESSION_FORMATS







def    a__							(							lowercase   :	"PIL.Image.Image" )						->						bytes:





     """simple docstring"""

     _UpperCamelCase							       =			BytesIO()
     if image.format in list_image_compression_formats():
          _UpperCamelCase							       =			image.format
     else:
          _UpperCamelCase							       =			'''PNG''' if image.mode in ['''1''', '''L''', '''LA''', '''RGB''', '''RGBA'''] else '''TIFF'''
     image.save(lowercase,   format=lowercase )
     return buffer.getvalue()







def    a__							(							lowercase   :	"PIL.Image.Image" )						->						dict:





     """simple docstring"""

     if hasattr(lowercase,   '''filename''' ) and image.filename != "":
          return {"path": image.filename, "bytes": None}
     else:
          return {"path": None, "bytes": image_to_bytes(lowercase )}







def    a__							(							lowercase   :	np.ndarray )						->						dict:





     """simple docstring"""

     if config.PIL_AVAILABLE:
          import PIL.Image
     else:
          raise ImportError('''To support encoding images, please install \'Pillow\'.''' )

     _UpperCamelCase							       =			array.dtype
     _UpperCamelCase							       =			dtype.byteorder if dtype.byteorder != '''=''' else _NATIVE_BYTEORDER
     _UpperCamelCase							       =			dtype.kind
     _UpperCamelCase							       =			dtype.itemsize

     _UpperCamelCase							       =			None

     # Multi-channel array case (only np.dtype("|u1") is allowed)
     if array.shape[2:]:
          _UpperCamelCase							       =			np.dtype('''|u1''' )
          if dtype_kind not in ["u", "i"]:
               raise TypeError(
                   F"""Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays.""" )
          if dtype is not dest_dtype:
               warnings.warn(F"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'""" )
    # Exact match
     elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
          _UpperCamelCase							       =			dtype
     else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
          while dtype_itemsize >= 1:
               _UpperCamelCase							       =			dtype_byteorder + dtype_kind + str(lowercase )
               _UpperCamelCase							       =			np.dtype(lowercase )
               if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
                    warnings.warn(F"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'""" )
                    break
               else:
                    dtype_itemsize //= 2

     if dest_dtype is None:
          raise TypeError(
              F"""Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}""" )
     _UpperCamelCase							       =			PIL.Image.fromarray(array.astype(lowercase ) )
     return {"path": None, "bytes": image_to_bytes(lowercase )}







def    a__							(							lowercase   :	Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]] )						->						List[dict]:





     """simple docstring"""

     if config.PIL_AVAILABLE:
          import PIL.Image
     else:
          raise ImportError('''To support encoding images, please install \'Pillow\'.''' )

     if objs:
          _UpperCamelCase       ,							_UpperCamelCase							       =			first_non_null_value(lowercase )
          if isinstance(lowercase,   lowercase ):
               return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
          if isinstance(lowercase,   np.ndarray ):
               _UpperCamelCase							       =			no_op_if_value_is_null(lowercase )
               return [obj_to_image_dict_func(lowercase ) for obj in objs]
          elif isinstance(lowercase,   PIL.Image.Image ):
               _UpperCamelCase							       =			no_op_if_value_is_null(lowercase )
               return [obj_to_image_dict_func(lowercase ) for obj in objs]
          else:
               return objs
     else:
          return objs







"""simple docstring"""



import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


__snake_case       =       logging.get_logger(__name__)







class _lowerCAmelCase							( snake_case_      ):







   def __init__(      self		,      *UpperCamelCase__		,      **UpperCamelCase__		)      ->						None:

       '''simple docstring'''




       warnings.warn(
           "The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
           " Please use SegformerImageProcessor instead."		,      UpperCamelCase__		,      )
       super().__init__(*UpperCamelCase__		,      **UpperCamelCase__		)





