






"""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    :   Optional[List[str]]   			=						None
_UpperCamelCase    :   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
_UpperCamelCase    :   List[str]   			=						[
    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 						snake_case  :
    __magic_name__   					=					True
    __magic_name__   					=					None
    # Automatically constructed
    __magic_name__   					=					"PIL.Image.Image"
    __magic_name__   					=					pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()}	)
    __magic_name__   					=					field(default='''Image'''       ,			init=UpperCAmelCase       ,			repr=UpperCAmelCase	)





    def __call__(							self     : List[str]      ):


      '''simple docstring'''




      return self.pa_type





    def     lowerCamelCase__				(							self     : List[str]    ,		A     : Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]      ):


      '''simple docstring'''




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

      if isinstance(A    ,		A      ):
        a					:      str    =       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     lowerCamelCase__				(							self     : Dict    ,		A     : dict    ,		A     : Union[str, Any]=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:
        a					:      int    =       {}

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





    def     lowerCamelCase__				(							self     : str      ):


      '''simple docstring'''




      from .features import Value

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





    def     lowerCamelCase__				(							self     : Union[str, Any]    ,		A     : Union[pa.StringArray, pa.StructArray, pa.ListArray]      ):


      '''simple docstring'''




      if pa.types.is_string(storage.type      ):
        a					:      Optional[Any]    =       pa.array([None] * len(A      )    ,		type=pa.binary()      )
        a					:      Any    =       pa.StructArray.from_arrays([bytes_array, storage]    ,		['bytes', 'path']    ,		mask=storage.is_null()      )
      elif pa.types.is_binary(storage.type      ):
        a					:      Union[str, Any]    =       pa.array([None] * len(A      )    ,		type=pa.string()      )
        a					:      List[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:
          a					:      Dict    =       storage.field('bytes'      )
        else:
          a					:      str    =       pa.array([None] * len(A      )    ,		type=pa.binary()      )
        if storage.type.get_field_index('path'      ) >= 0:
          a					:      Tuple    =       storage.field('path'      )
        else:
          a					:      str    =       pa.array([None] * len(A      )    ,		type=pa.string()      )
        a					:      Dict    =       pa.StructArray.from_arrays([bytes_array, path_array]    ,		['bytes', 'path']    ,		mask=storage.is_null()      )
      elif pa.types.is_list(storage.type      ):
        a					:      List[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()    ,		)
        a					:      Optional[int]    =       pa.array([None] * len(A      )    ,		type=pa.string()      )
        a					:      Dict    =       pa.StructArray.from_arrays(
            [bytes_array, path_array]    ,		['bytes', 'path']    ,		mask=bytes_array.is_null()      )
      return array_cast(A    ,		self.pa_type      )





    def     lowerCamelCase__				(							self     : str    ,		A     : pa.StructArray      ):


      '''simple docstring'''




      @no_op_if_value_is_null
      def path_to_bytes(A     : Union[str, Any]      ):
        with xopen(A    ,		'rb'      ) as f:
          a					:      Optional[int]    =       f.read()
        return bytes_

      a					:      Optional[Any]    =       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()    ,		)
      a					:      int    =       pa.array(
          [os.path.basename(A      ) if path is not None else None for path in storage.field('path'      ).to_pylist()]    ,		type=pa.string()    ,		)
      a					:      Optional[int]    =       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  ():







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




def       snake_case  (A_				:"PIL.Image.Image"				):







  '''simple docstring'''

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




def       snake_case  (A_				:"PIL.Image.Image"				):







  '''simple docstring'''

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




def       snake_case  (A_				:np.ndarray				):







  '''simple docstring'''

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

  a					:      Union[str, Any]    =       array.dtype
  a					:      Optional[Any]    =       dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
  a					:      List[Any]    =       dtype.kind
  a					:      Dict    =       dtype.itemsize

  a					:      Any    =       None

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






def       snake_case  (A_				: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:
    a,					a					:      Union[str, Any]    =       first_non_null_value(A_				)
    if isinstance(A_     ,      A_				):
      return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
    if isinstance(A_     ,      np.ndarray				):
      a					:      Optional[Any]    =       no_op_if_value_is_null(A_				)
      return [obj_to_image_dict_func(A_				) for obj in objs]
    elif isinstance(A_     ,      PIL.Image.Image				):
      a					:      Tuple    =       no_op_if_value_is_null(A_				)
      return [obj_to_image_dict_func(A_				) for obj in objs]
    else:
      return objs
  else:
    return objs












"""simple docstring"""


def       snake_case  (A_				:str     ,      A_				:bool = False				):







  '''simple docstring'''

  if not isinstance(A_     ,      A_				):
    a					:      Union[str, Any]    =       f'''Expected string as input, found {type(A_				)}'''
    raise ValueError(A_				)
  if not isinstance(A_     ,      A_				):
    a					:      Optional[int]    =       f'''Expected boolean as use_pascal parameter, found {type(A_				)}'''
    raise ValueError(A_				)

  a					:      Tuple    =       input_str.split('_'				)

  a					:      Dict    =       0 if use_pascal else 1

  a					:      int    =       words[start_index:]

  a					:      int    =       [word[0].upper() + word[1:] for word in words_to_capitalize]

  a					:      List[str]    =       '' if use_pascal else words[0]

  return "".join([initial_word, *capitalized_words]				)


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

   testmod()




