





"""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


lowerCAmelCase:						Optional[List[str]]				   =None
lowerCAmelCase:						Union[str, 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
lowerCAmelCase:						List[Any]				   =[
    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__	:
   __UpperCAmelCase										=       True
   __UpperCAmelCase										=       None
   # Automatically constructed
   __UpperCAmelCase										=       "PIL.Image.Image"
   __UpperCAmelCase										=       pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}					)
   __UpperCAmelCase										=       field(default="""Image"""	,					init=lowerCAmelCase__	,					repr=lowerCAmelCase__					)



   def __call__(							self						)			->     Optional[int]:







      """simple docstring"""
      return self.pa_type



   def  _UpperCAmelCase						(							self   , snake_case						)			->     int:







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

      if isinstance(__a   , __a						):
         lowercase     :      Tuple	=							np.array(__a						)

      if isinstance(__a   , __a						):
         return {"path": value, "bytes": None}
      elif isinstance(__a   , __a						):
         return {"path": None, "bytes": value}
      elif isinstance(__a   , np.ndarray						):
         # convert the image array to PNG/TIFF bytes
         return encode_np_array(__a						)
      elif isinstance(__a   , PIL.Image.Image						):
         # convert the PIL image to bytes (default format is PNG/TIFF)
         return encode_pil_image(__a						)
      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  _UpperCAmelCase						(							self   , snake_case   , snake_case=None						)			->     Tuple:







      """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:
         lowercase     :      List[str]	=							{}

      lowercase	,       lowercase     :      str	=							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(__a						):
               lowercase     :      List[str]	=							PIL.Image.open(__a						)
            else:
               lowercase     :      Optional[int]	=							path.split("""::"""						)[-1]
               try:
                  lowercase     :      List[Any]	=							string_to_dict(__a   , config.HUB_DATASETS_URL						)["""repo_id"""]
                  lowercase     :      Any	=							token_per_repo_id.get(__a						)
               except ValueError:
                  lowercase     :      Tuple	=							None
               with xopen(__a   , """rb"""   , use_auth_token=__a						) as f:
                  lowercase     :      List[str]	=							BytesIO(f.read()						)
               lowercase     :      List[str]	=							PIL.Image.open(bytes_						)
      else:
         lowercase     :      Tuple	=							PIL.Image.open(BytesIO(bytes_						)						)
      image.load()  # to avoid "Too many open files" errors
      return image



   def  _UpperCAmelCase						(							self						)			->     Union[str, Any]:







      """simple docstring"""
      from .features import Value

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



   def  _UpperCAmelCase						(							self   , snake_case						)			->     Any:







      """simple docstring"""
      if pa.types.is_string(storage.type						):
         lowercase     :      Union[str, Any]	=							pa.array([None] * len(__a						)   , type=pa.binary()						)
         lowercase     :      List[str]	=							pa.StructArray.from_arrays([bytes_array, storage]   , ["""bytes""", """path"""]   , mask=storage.is_null()						)
      elif pa.types.is_binary(storage.type						):
         lowercase     :      str	=							pa.array([None] * len(__a						)   , type=pa.string()						)
         lowercase     :      Tuple	=							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:
            lowercase     :      List[Any]	=							storage.field("""bytes"""						)
         else:
            lowercase     :      str	=							pa.array([None] * len(__a						)   , type=pa.binary()						)
         if storage.type.get_field_index("""path"""						) >= 0:
            lowercase     :      Optional[Any]	=							storage.field("""path"""						)
         else:
            lowercase     :      List[Any]	=							pa.array([None] * len(__a						)   , type=pa.string()						)
         lowercase     :      Any	=							pa.StructArray.from_arrays([bytes_array, path_array]   , ["""bytes""", """path"""]   , mask=storage.is_null()						)
      elif pa.types.is_list(storage.type						):
         lowercase     :      Union[str, Any]	=							pa.array(
             [encode_np_array(np.array(__a						)						)["""bytes"""] if arr is not None else None for arr in storage.to_pylist()]   , type=pa.binary()   , )
         lowercase     :      int	=							pa.array([None] * len(__a						)   , type=pa.string()						)
         lowercase     :      List[str]	=							pa.StructArray.from_arrays(
             [bytes_array, path_array]   , ["""bytes""", """path"""]   , mask=bytes_array.is_null()						)
      return array_cast(__a   , self.pa_type						)





   def  _UpperCAmelCase						(							self   , snake_case						)			->     Tuple:







      """simple docstring"""

      @no_op_if_value_is_null
      def path_to_bytes(snake_case						):
         with xopen(__a   , """rb"""						) as f:
            lowercase     :      Any	=							f.read()
         return bytes_

      lowercase     :      str	=							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()   , )
      lowercase     :      Union[str, Any]	=							pa.array(
          [os.path.basename(__a						) if path is not None else None for path in storage.field("""path"""						).to_pylist()]   , type=pa.string()   , )
      lowercase     :      Union[str, Any]	=							pa.StructArray.from_arrays([bytes_array, path_array]   , ["""bytes""", """path"""]   , mask=bytes_array.is_null()						)
      return array_cast(__a   , self.pa_type						)




def       __snake_case    (   )		->					Optional[Any]:




   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()
      lowercase     :      Tuple	=							list(set(PIL.Image.OPEN.keys()     ) & set(PIL.Image.SAVE.keys()     )     )
   return _IMAGE_COMPRESSION_FORMATS




def       __snake_case    (   __A     )		->					Tuple:
   lowercase     :      Any	=							BytesIO()
   if image.format in list_image_compression_formats():
      lowercase     :      Any	=							image.format
   else:
      lowercase     :      int	=							"""PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
   image.save(_UpperCamelCase			,format=_UpperCamelCase     )
   return buffer.getvalue()




def       __snake_case    (   __A     )		->					Optional[Any]:




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




def       __snake_case    (   __A     )		->					Tuple:




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

   lowercase     :      Union[str, Any]	=							array.dtype
   lowercase     :      Tuple	=							dtype.byteorder if dtype.byteorder != """=""" else _NATIVE_BYTEORDER
   lowercase     :      Union[str, Any]	=							dtype.kind
   lowercase     :      str	=							dtype.itemsize

   lowercase     :      List[str]	=							None

   # Multi-channel array case (only np.dtype("|u1") is allowed)
   if array.shape[2:]:
      lowercase     :      Dict	=							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:
      lowercase     :      List[Any]	=							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:
         lowercase     :      Tuple	=							dtype_byteorder + dtype_kind + str(_UpperCamelCase     )
         lowercase     :      str	=							np.dtype(_UpperCamelCase     )
         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}'''     )
   lowercase     :      str	=							PIL.Image.fromarray(array.astype(_UpperCamelCase     )     )
   return {"path": None, "bytes": image_to_bytes(_UpperCamelCase     )}







def       __snake_case    (   __A     )		->					str:




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

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






"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


A	:  Optional[Any]            =     logging.get_logger(__name__)
class     _UpperCamelCase    (  lowerCAmelCase__						):
							'''simple docstring'''







							def __init__(	self       ,  *__a       ,  **__a      ):
										warnings.warn(
										    "The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
										    " use YolosImageProcessor instead."       ,  __a       ,  )
										super().__init__(*__a       ,  **__a      )




