





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__   : Optional[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__   : Dict					  = [
    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   _UpperCamelCase  :







					'''simple docstring'''

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





					def __call__(						self    :  List[Any]		):






						'''simple docstring'''







						return self.pa_type





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict ,					__lowercase    :  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(__lowercase ,					__lowercase		):
							UpperCAmelCase_								=     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        SCREAMING_SNAKE_CASE							(						self    :  List[str] ,					__lowercase    :  dict ,					__lowercase    :  Dict=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(__lowercase		):
									UpperCAmelCase_								=     PIL.Image.open(__lowercase		)
								else:
									UpperCAmelCase_								=     path.split("""::"""		)[-1]
									try:
										UpperCAmelCase_								=     string_to_dict(__lowercase ,					config.HUB_DATASETS_URL		)["""repo_id"""]
										UpperCAmelCase_								=     token_per_repo_id.get(__lowercase		)
									except ValueError:
										UpperCAmelCase_								=     None
									with xopen(__lowercase ,					"""rb""" ,					use_auth_token=__lowercase		) 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    :  Optional[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 ,					__lowercase    :  Union[pa.StringArray, pa.StructArray, pa.ListArray]		):






						'''simple docstring'''







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





					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any] ,					__lowercase    :  pa.StructArray		):






						'''simple docstring'''







						@no_op_if_value_is_null
						def path_to_bytes(__lowercase    :  Dict		):
							with xopen(__lowercase ,					"""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(__lowercase		) 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(__lowercase ,					self.pa_type		)




def    A_(			):
	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    A_(			A   ):
	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(A				,      format=A   )
	return buffer.getvalue()




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




def    A_(			A   ):
	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(A   )
			UpperCAmelCase_								=     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}"""   )
	UpperCAmelCase_								=     PIL.Image.fromarray(array.astype(A   )   )
	return {"path": None, "bytes": image_to_bytes(A   )}




def    A_(			A   ):
	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(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   ):
			UpperCAmelCase_								=     no_op_if_value_is_null(A   )
			return [obj_to_image_dict_func(A   ) for obj in objs]
		elif isinstance(A				,      PIL.Image.Image   ):
			UpperCAmelCase_								=     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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__   : List[Any]					  = {"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__   : List[str]					  = [
				    """SEW_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """SEWForCTC""",
				    """SEWForSequenceClassification""",
				    """SEWModel""",
				    """SEWPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_sew import (
								    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SEWForCTC,
								    SEWForSequenceClassification,
								    SEWModel,
								    SEWPreTrainedModel,
								)


else:
				import sys

				UpperCamelCase__   : str					  = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


