


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											=       None
lowerCamelCase											=       '<' 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											=       [
    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 A  :
      UpperCamelCase__							:  bool      =True
      UpperCamelCase__							:  Optional[str]      =None
      # Automatically constructed
      UpperCamelCase__							:  ClassVar[str]      ="PIL.Image.Image"
      UpperCamelCase__							:  ClassVar[Any]      =pa.struct({'bytes': pa.binary(), 'path': pa.string()}     )
      UpperCamelCase__							:  str      =field(default='Image'    ,							init=UpperCamelCase_    ,							repr=UpperCamelCase_     )






      def __call__(					self						:     Any )					->						Optional[Any]:
             """simple docstring"""




             return self.pa_type






      def        lowerCamelCase       (					self						:     int			,   lowercase_						:     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(lowercase_			,   lowercase_ ):
                    _lowerCamelCase       :		Optional[Any]		=np.array(lowercase_ )

             if isinstance(lowercase_			,   lowercase_ ):
                    return {"path": value, "bytes": None}
             elif isinstance(lowercase_			,   lowercase_ ):
                    return {"path": None, "bytes": value}
             elif isinstance(lowercase_			,   np.ndarray ):
                    # convert the image array to PNG/TIFF bytes
                    return encode_np_array(lowercase_ )
             elif isinstance(lowercase_			,   PIL.Image.Image ):
                    # convert the PIL image to bytes (default format is PNG/TIFF)
                    return encode_pil_image(lowercase_ )
             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        lowerCamelCase       (					self						:     List[Any]			,   lowercase_						:     dict			,   lowercase_						:     int=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:
                    _lowerCamelCase       :		Union[str, Any]		={}

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






      def        lowerCamelCase       (					self						:     Dict )					->						Union["FeatureType", Dict[str, "FeatureType"]]:
             """simple docstring"""




             from .features import Value

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






      def        lowerCamelCase       (					self						:     Union[str, Any]			,   lowercase_						:     Union[pa.StringArray, pa.StructArray, pa.ListArray] )					->						pa.StructArray:
             """simple docstring"""




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






      def        lowerCamelCase       (					self						:     Optional[int]			,   lowercase_						:     pa.StructArray )					->						pa.StructArray:
             """simple docstring"""




             @no_op_if_value_is_null
             def path_to_bytes(lowercase_						:     Any ):
                    with xopen(lowercase_			,   'rb' ) as f:
                           _lowerCamelCase       :		Tuple		=f.read()
                    return bytes_

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




def 	a_      (    ):
       '''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()
              _lowerCamelCase       :		List[Any]		=list(set(PIL.Image.OPEN.keys()     ) & set(PIL.Image.SAVE.keys()     )     )
       return _IMAGE_COMPRESSION_FORMATS




def 	a_      (    SCREAMING_SNAKE_CASE__					:      "PIL.Image.Image"     ):
       '''simple docstring'''





       _lowerCamelCase       :		Tuple		=BytesIO()
       if image.format in list_image_compression_formats():
              _lowerCamelCase       :		List[str]		=image.format
       else:
              _lowerCamelCase       :		Any		='PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
       image.save(SCREAMING_SNAKE_CASE__		,			format=SCREAMING_SNAKE_CASE__     )
       return buffer.getvalue()




def 	a_      (    SCREAMING_SNAKE_CASE__					:      "PIL.Image.Image"     ):
       '''simple docstring'''





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




def 	a_      (    SCREAMING_SNAKE_CASE__					:      np.ndarray     ):
       '''simple docstring'''





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

       _lowerCamelCase       :		List[Any]		=array.dtype
       _lowerCamelCase       :		Dict		=dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
       _lowerCamelCase       :		List[str]		=dtype.kind
       _lowerCamelCase       :		List[Any]		=dtype.itemsize

       _lowerCamelCase       :		str		=None

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




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]     ):
       '''simple docstring'''





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

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






# Lint as: python3
import itertools
import os
import re


lowerCamelCase											=       re.compile(R'([A-Z]+)([A-Z][a-z])')
lowerCamelCase											=       re.compile(R'([a-z\d])([A-Z])')

lowerCamelCase											=       re.compile(R'(?<!_)_(?!_)')
lowerCamelCase											=       re.compile(R'(_{2,})')

lowerCamelCase											=       R'^\w+(\.\w+)*$'

lowerCamelCase											=       R'<>:/\|?*'




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Tuple     ):
       '''simple docstring'''





       _lowerCamelCase       :		List[str]		=_uppercase_uppercase_re.sub(r'\1_\2'		,			SCREAMING_SNAKE_CASE__     )
       _lowerCamelCase       :		List[Any]		=_lowercase_uppercase_re.sub(r'\1_\2'		,			SCREAMING_SNAKE_CASE__     )
       return name.lower()




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[str, Any]     ):
       '''simple docstring'''





       _lowerCamelCase       :		Tuple		=_single_underscore_re.split(SCREAMING_SNAKE_CASE__     )
       _lowerCamelCase       :		Tuple		=[_multiple_underscores_re.split(SCREAMING_SNAKE_CASE__     ) for n in name]
       return "".join(n.capitalize() for n in itertools.chain.from_iterable(SCREAMING_SNAKE_CASE__     ) if n != ''     )




def 	a_      (    SCREAMING_SNAKE_CASE__					:      List[Any]     ):
       '''simple docstring'''





       if os.path.basename(SCREAMING_SNAKE_CASE__     ) != name:
              raise ValueError(F'''Should be a dataset name, not a path: {name}'''     )
       return camelcase_to_snakecase(SCREAMING_SNAKE_CASE__     )




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[str, Any]		,			SCREAMING_SNAKE_CASE__					:      Optional[int]     ):
       '''simple docstring'''





       if os.path.basename(SCREAMING_SNAKE_CASE__     ) != name:
              raise ValueError(F'''Should be a dataset name, not a path: {name}'''     )
       if not re.match(_split_re		,			SCREAMING_SNAKE_CASE__     ):
              raise ValueError(F'''Split name should match \'{_split_re}\'\' but got \'{split}\'.'''     )
       return F'''{filename_prefix_for_name(SCREAMING_SNAKE_CASE__     )}-{split}'''




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Optional[int]		,			SCREAMING_SNAKE_CASE__					:      List[Any]		,			SCREAMING_SNAKE_CASE__					:      Optional[Any]		,			SCREAMING_SNAKE_CASE__					:      int=None     ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		=filename_prefix_for_split(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       if filetype_suffix:
              prefix += F'''.{filetype_suffix}'''
       _lowerCamelCase       :		Optional[Any]		=os.path.join(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       return F'''{filepath}*'''




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Tuple		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      str		,			SCREAMING_SNAKE_CASE__					:      List[str]=None		,			SCREAMING_SNAKE_CASE__					:      Optional[Any]=None     ):
       '''simple docstring'''





       _lowerCamelCase       :		Dict		=filename_prefix_for_split(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       _lowerCamelCase       :		Union[str, Any]		=os.path.join(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )

       if shard_lengths:
              _lowerCamelCase       :		Union[str, Any]		=len(SCREAMING_SNAKE_CASE__     )
              _lowerCamelCase       :		Optional[int]		=[F'''{prefix}-{shard_id:05d}-of-{num_shards:05d}''' for shard_id in range(SCREAMING_SNAKE_CASE__     )]
              if filetype_suffix:
                     _lowerCamelCase       :		List[Any]		=[filename + F'''.{filetype_suffix}''' for filename in filenames]
              return filenames
       else:
              _lowerCamelCase       :		Any		=prefix
              if filetype_suffix:
                     filename += F'''.{filetype_suffix}'''
              return [filename]


