





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


__A     =    None
__A     =    "<" 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
__A     =    [
    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        _SCREAMING_SNAKE_CASE						:







 '''simple docstring'''
 lowercase_		=      True
 lowercase_		=      None
 # Automatically constructed
 lowercase_		=      "PIL.Image.Image"
 lowercase_		=      pa.struct({"bytes": pa.binary(), "path": pa.string()}   )
 lowercase_		=      field(default="Image"   ,							init=__SCREAMING_SNAKE_CASE   ,							repr=__SCREAMING_SNAKE_CASE   )

 def __call__(self    :       Dict)	->List[Any]:



   '''simple docstring'''



   return self.pa_type

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       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(UpperCAmelCase_	,			UpperCAmelCase_):
     lowerCamelCase__:				Tuple        =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    :       Tuple	,			UpperCAmelCase_    :       dict	,			UpperCAmelCase_    :       Optional[Any]=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__:				Any        ={}

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

 def 							SCREAMING_SNAKE_CASE_ (self    :       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 							SCREAMING_SNAKE_CASE_ (self    :       int	,			UpperCAmelCase_    :       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(UpperCAmelCase_)	,			type=pa.binary())
     lowerCamelCase__:				Dict        =pa.StructArray.from_arrays([bytes_array, storage]	,			["bytes", "path"]	,			mask=storage.is_null())
   elif pa.types.is_binary(storage.type):
     lowerCamelCase__:				Optional[Any]        =pa.array([None] * len(UpperCAmelCase_)	,			type=pa.string())
     lowerCamelCase__:				Optional[Any]        =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__:				Union[str, Any]        =storage.field("bytes")
     else:
       lowerCamelCase__:				Optional[int]        =pa.array([None] * len(UpperCAmelCase_)	,			type=pa.binary())
     if storage.type.get_field_index("path") >= 0:
       lowerCamelCase__:				Optional[Any]        =storage.field("path")
     else:
       lowerCamelCase__:				Optional[Any]        =pa.array([None] * len(UpperCAmelCase_)	,			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__:				str        =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()	,			)
     lowerCamelCase__:				int        =pa.array([None] * len(UpperCAmelCase_)	,			type=pa.string())
     lowerCamelCase__:				Optional[Any]        =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    :       Union[str, Any]	,			UpperCAmelCase_    :       pa.StructArray)	->pa.StructArray:



   '''simple docstring'''



   @no_op_if_value_is_null
   def path_to_bytes(UpperCAmelCase_    :       Optional[Any]):
     with xopen(UpperCAmelCase_	,			"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(UpperCAmelCase_) if path is not None else None for path in storage.field("path").to_pylist()]	,			type=pa.string()	,			)
   lowerCamelCase__:				Optional[int]        =pa.StructArray.from_arrays([bytes_array, path_array]	,			["bytes", "path"]	,			mask=bytes_array.is_null())
   return array_cast(UpperCAmelCase_	,			self.pa_type)





def 					lowerCAmelCase_			(	)					->		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()
    lowerCamelCase__:				Optional[int]        =list(set(PIL.Image.OPEN.keys()		) & set(PIL.Image.SAVE.keys()		)		)
  return _IMAGE_COMPRESSION_FORMATS





def 					lowerCAmelCase_			(	__a		)					->		bytes:







  """simple docstring"""





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





def 					lowerCAmelCase_			(	__a		)					->		dict:







  """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 					lowerCAmelCase_			(	__a		)					->		dict:







  """simple docstring"""





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

  lowerCamelCase__:				str        =array.dtype
  lowerCamelCase__:				str        =dtype.byteorder if dtype.byteorder != "=" else _NATIVE_BYTEORDER
  lowerCamelCase__:				int        =dtype.kind
  lowerCamelCase__:				str        =dtype.itemsize

  lowerCamelCase__:				Union[str, Any]        =None

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






def 					lowerCAmelCase_			(	__a		)					->		List[dict]:







  """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(__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		):
      lowerCamelCase__:				str        =no_op_if_value_is_null(__a		)
      return [obj_to_image_dict_func(__a		) for obj in objs]
    elif isinstance(__a     ,   PIL.Image.Image		):
      lowerCamelCase__:				List[str]        =no_op_if_value_is_null(__a		)
      return [obj_to_image_dict_func(__a		) for obj in objs]
    else:
      return objs
  else:
    return objs








from ..utils import DummyObject, requires_backends



class        _SCREAMING_SNAKE_CASE						(     metaclass=__SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''
 lowercase_		=      ["torch", "torchsde"]

 def __init__(self    :       Union[str, Any]	,			*UpperCAmelCase_    :       Dict	,			**UpperCAmelCase_    :       Tuple)	->Any:



   '''simple docstring'''



   requires_backends(self	,			["torch", "torchsde"])

 @classmethod
 def 							SCREAMING_SNAKE_CASE_ (cls    :       Dict	,			*UpperCAmelCase_    :       Optional[int]	,			**UpperCAmelCase_    :       Optional[int])	->List[Any]:



   '''simple docstring'''



   requires_backends(cls	,			["torch", "torchsde"])







 @classmethod
 def 							SCREAMING_SNAKE_CASE_ (cls    :       Tuple	,			*UpperCAmelCase_    :       Tuple	,			**UpperCAmelCase_    :       Any)	->Any:



   '''simple docstring'''



   requires_backends(cls	,			["torch", "torchsde"])

