




'''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


UpperCAmelCase_				 =					None
UpperCAmelCase_				 =					'<' 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
UpperCAmelCase_				 =					[
    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'''







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


  def __call__(  self			:		Optional[Any]       ):






   """simple docstring"""






   return self.pa_type


  def 							SCREAMING_SNAKE_CASE__	(  self			:		Tuple  ,						_UpperCAmelCase			:		Optional[Any]       ):






   """simple docstring"""






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

   if isinstance(_UpperCAmelCase  ,						_UpperCAmelCase       ):
    UpperCAmelCase__								=			np.array(_UpperCAmelCase       )

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






   """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(_UpperCAmelCase       ):
      UpperCAmelCase__								=			PIL.Image.open(_UpperCAmelCase       )
     else:
      UpperCAmelCase__								=			path.split("""::"""       )[-1]
      try:
       UpperCAmelCase__								=			string_to_dict(_UpperCAmelCase  ,						config.HUB_DATASETS_URL       )["""repo_id"""]
       UpperCAmelCase__								=			token_per_repo_id.get(_UpperCAmelCase       )
      except ValueError:
       UpperCAmelCase__								=			None
      with xopen(_UpperCAmelCase  ,						"""rb"""  ,						use_auth_token=_UpperCAmelCase       ) 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 							SCREAMING_SNAKE_CASE__	(  self			:		int       ):






   """simple docstring"""






   from .features import Value

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


  def 							SCREAMING_SNAKE_CASE__	(  self			:		Dict  ,						_UpperCAmelCase			:		List[Any]       ):






   """simple docstring"""






   if pa.types.is_string(storage.type       ):
    UpperCAmelCase__								=			pa.array([None] * len(_UpperCAmelCase       )  ,						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(_UpperCAmelCase       )  ,						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(_UpperCAmelCase       )  ,						type=pa.binary()       )
    if storage.type.get_field_index("""path"""       ) >= 0:
     UpperCAmelCase__								=			storage.field("""path"""       )
    else:
     UpperCAmelCase__								=			pa.array([None] * len(_UpperCAmelCase       )  ,						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(_UpperCAmelCase       )       )["""bytes"""] if arr is not None else None for arr in storage.to_pylist()]  ,						type=pa.binary()  ,						)
    UpperCAmelCase__								=			pa.array([None] * len(_UpperCAmelCase       )  ,						type=pa.string()       )
    UpperCAmelCase__								=			pa.StructArray.from_arrays(
        [bytes_array, path_array]  ,						["""bytes""", """path"""]  ,						mask=bytes_array.is_null()       )
   return array_cast(_UpperCAmelCase  ,						self.pa_type       )



  def 							SCREAMING_SNAKE_CASE__	(  self			:		Any  ,						_UpperCAmelCase			:		Any       ):






   """simple docstring"""






   @no_op_if_value_is_null
   def path_to_bytes(_UpperCAmelCase			:		Tuple       ):
    with xopen(_UpperCAmelCase  ,						"""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(_UpperCAmelCase       ) 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(_UpperCAmelCase  ,						self.pa_type       )

def       _UpperCamelCase					( ):
 '''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       _UpperCamelCase					( SCREAMING_SNAKE_CASE__	:					"PIL.Image.Image"				):
 '''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(__lowerCamelCase				,  format=__lowerCamelCase				)
 return buffer.getvalue()

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





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

def       _UpperCamelCase					( SCREAMING_SNAKE_CASE__	:					np.ndarray				):
 '''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(__lowerCamelCase				)
   UpperCAmelCase__								=			np.dtype(__lowerCamelCase				)
   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(__lowerCamelCase				)				)
 return {"path": None, "bytes": image_to_bytes(__lowerCamelCase				)}







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







'''simple docstring'''

from string import ascii_lowercase, ascii_uppercase





def lowerCamelCase						(     __lowerCamelCase :    str    )						->str:
    if not sentence:
        return ""
    _SCREAMING_SNAKE_CASE									=			dict(zip(__lowerCamelCase					,       __lowerCamelCase    )    )
    return lower_to_upper.get(sentence[0]					,       sentence[0]    ) + sentence[1:]


if __name__ == "__main__":
      from doctest import testmod

      testmod()



