





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 	UpperCamelCase_							:
							lowerCamelCase_							     =       True
							lowerCamelCase_							     =       None
							# Automatically constructed
							lowerCamelCase_							     =       "PIL.Image.Image"
							lowerCamelCase_							     =       pa.struct({"bytes": pa.binary(), "path": pa.string()}     )
							lowerCamelCase_							     =       field(default="Image"					,	init=UpperCamelCase__					,	repr=UpperCamelCase__     )


							def __call__(				self     :Optional[Any]		) -> Optional[int]:



									"""simple docstring"""



									return self.pa_type


							def   _snake_case	(				self     :int				,					__A     :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(__A				,					__A		):
											SCREAMING_SNAKE_CASE__								=   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   _snake_case	(				self     :Tuple				,					__A     :dict				,					__A     :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:
											SCREAMING_SNAKE_CASE__								=   {}

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


							def   _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   _snake_case	(				self     :List[Any]				,					__A     :Union[pa.StringArray, pa.StructArray, pa.ListArray]		) -> pa.StructArray:



									"""simple docstring"""



									if pa.types.is_string(storage.type		):
											SCREAMING_SNAKE_CASE__								=   pa.array([None] * len(__A		)				,					type=pa.binary()		)
											SCREAMING_SNAKE_CASE__								=   pa.StructArray.from_arrays([bytes_array, storage]				,					["""bytes""", """path"""]				,					mask=storage.is_null()		)
									elif pa.types.is_binary(storage.type		):
											SCREAMING_SNAKE_CASE__								=   pa.array([None] * len(__A		)				,					type=pa.string()		)
											SCREAMING_SNAKE_CASE__								=   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:
													SCREAMING_SNAKE_CASE__								=   storage.field("""bytes"""		)
											else:
													SCREAMING_SNAKE_CASE__								=   pa.array([None] * len(__A		)				,					type=pa.binary()		)
											if storage.type.get_field_index("""path"""		) >= 0:
													SCREAMING_SNAKE_CASE__								=   storage.field("""path"""		)
											else:
													SCREAMING_SNAKE_CASE__								=   pa.array([None] * len(__A		)				,					type=pa.string()		)
											SCREAMING_SNAKE_CASE__								=   pa.StructArray.from_arrays([bytes_array, path_array]				,					["""bytes""", """path"""]				,					mask=storage.is_null()		)
									elif pa.types.is_list(storage.type		):
											SCREAMING_SNAKE_CASE__								=   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()				,					)
											SCREAMING_SNAKE_CASE__								=   pa.array([None] * len(__A		)				,					type=pa.string()		)
											SCREAMING_SNAKE_CASE__								=   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	(				self     :Tuple				,					__A     :pa.StructArray		) -> pa.StructArray:



									"""simple docstring"""



									@no_op_if_value_is_null
									def path_to_bytes(__A     :Tuple		):
											with xopen(__A				,					"""rb"""		) as f:
													SCREAMING_SNAKE_CASE__								=   f.read()
											return bytes_

									SCREAMING_SNAKE_CASE__								=   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()				,					)
									SCREAMING_SNAKE_CASE__								=   pa.array(
									    [os.path.basename(__A		) if path is not None else None for path in storage.field("""path"""		).to_pylist()]				,					type=pa.string()				,					)
									SCREAMING_SNAKE_CASE__								=   pa.StructArray.from_arrays([bytes_array, path_array]				,					["""bytes""", """path"""]				,					mask=bytes_array.is_null()		)
									return array_cast(__A				,					self.pa_type		)






def 					SCREAMING_SNAKE_CASE__				(							):
		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()
				SCREAMING_SNAKE_CASE__								=   list(set(PIL.Image.OPEN.keys()     ) & set(PIL.Image.SAVE.keys()     )     )
		return _IMAGE_COMPRESSION_FORMATS






def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				"PIL.Image.Image"     ):
		SCREAMING_SNAKE_CASE__								=   BytesIO()
		if image.format in list_image_compression_formats():
				SCREAMING_SNAKE_CASE__								=   image.format
		else:
				SCREAMING_SNAKE_CASE__								=   """PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
		image.save(UpperCamelCase__       , format=UpperCamelCase__     )
		return buffer.getvalue()






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






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

		SCREAMING_SNAKE_CASE__								=   array.dtype
		SCREAMING_SNAKE_CASE__								=   dtype.byteorder if dtype.byteorder != """=""" else _NATIVE_BYTEORDER
		SCREAMING_SNAKE_CASE__								=   dtype.kind
		SCREAMING_SNAKE_CASE__								=   dtype.itemsize

		SCREAMING_SNAKE_CASE__								=   None

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






def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]     ):
		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError("""To support encoding images, please install 'Pillow'."""     )

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






def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				List[str]     ):
		SCREAMING_SNAKE_CASE__								=   len(UpperCamelCase__     )
		SCREAMING_SNAKE_CASE__								=   sum(UpperCamelCase__     )

		SCREAMING_SNAKE_CASE__								=   [[False for x in range(s + 1     )] for y in range(n + 1     )]

		for i in range(1       , n + 1     ):
				SCREAMING_SNAKE_CASE__								=   True

		for i in range(1       , s + 1     ):
				SCREAMING_SNAKE_CASE__								=   False

		for i in range(1       , n + 1     ):
				for j in range(1       , s + 1     ):
						SCREAMING_SNAKE_CASE__								=   dp[i][j - 1]

						if arr[i - 1] <= j:
								SCREAMING_SNAKE_CASE__								=   dp[i][j] or dp[i - 1][j - arr[i - 1]]

		for j in range(int(s / 2     )       , -1       , -1     ):
				if dp[n][j] is True:
						SCREAMING_SNAKE_CASE__								=   s - 2 * j
						break

		return diff