

import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union

from .. import config
from .filelock import FileLock
from .logging import get_logger


lowerCAmelCase     :   str						     =  get_logger(__name__)
class  _A		:

  def __init__(				self ,					_SCREAMING_SNAKE_CASE = None					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     (
            os.path.join(_SCREAMING_SNAKE_CASE ,					config.EXTRACTED_DATASETS_DIR					) if cache_dir else config.EXTRACTED_DATASETS_PATH
        )
        SCREAMING_SNAKE_CASE_				:  int           =     Extractor

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        from .file_utils import hash_url_to_filename

        # Path where we extract compressed archives
        # We extract in the cache dir, and get the extracted path name by hashing the original path"
        SCREAMING_SNAKE_CASE_				:  Tuple           =     os.path.abspath(_SCREAMING_SNAKE_CASE					)
        return os.path.join(self.extract_dir ,					hash_url_to_filename(_SCREAMING_SNAKE_CASE					)					)

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        return force_extract or (
            not os.path.isfile(_SCREAMING_SNAKE_CASE					) and not (os.path.isdir(_SCREAMING_SNAKE_CASE					) and os.listdir(_SCREAMING_SNAKE_CASE					))
        )



  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE = False					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  str           =     self.extractor.infer_extractor_format(_SCREAMING_SNAKE_CASE					)
        if not extractor_format:
              return input_path
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     self._get_output_path(_SCREAMING_SNAKE_CASE					)
        if self._do_extract(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):
              self.extractor.extract(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        return output_path

class  _A		(  __magic_name__):

  @classmethod
  @abstractmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE ,					**_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        ...



  @staticmethod
  @abstractmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        ...

class  _A		(  __magic_name__   ,     __magic_name__):
  SCREAMING_SNAKE_CASE    :      List[bytes]       =  []

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        with open(_SCREAMING_SNAKE_CASE ,					'rb'					) as f:
              return f.read(_SCREAMING_SNAKE_CASE					)



  @classmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE = b""					):





        """simple docstring"""







        if not magic_number:
              SCREAMING_SNAKE_CASE_				:  Optional[int]           =     max(len(_SCREAMING_SNAKE_CASE					) for cls_magic_number in cls.magic_numbers					)
              try:
                    SCREAMING_SNAKE_CASE_				:  Dict           =     cls.read_magic_number(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
              except OSError:
                    return False
        return any(magic_number.startswith(_SCREAMING_SNAKE_CASE					) for cls_magic_number in cls.magic_numbers					)

class  _A		(  __magic_name__):

  @classmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE ,					**_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        return tarfile.is_tarfile(_SCREAMING_SNAKE_CASE					)

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        def resolved(_SCREAMING_SNAKE_CASE					) -> str:
              return os.path.realpath(os.path.abspath(_SCREAMING_SNAKE_CASE					)					)

        def badpath(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					) -> bool:
              # joinpath will ignore base if path is absolute
              return not resolved(os.path.join(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)					).startswith(_SCREAMING_SNAKE_CASE					)

        def badlink(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					) -> bool:
              # Links are interpreted relative to the directory containing the link
              SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     resolved(os.path.join(_SCREAMING_SNAKE_CASE ,					os.path.dirname(info.name					)					)					)
              return badpath(info.linkname ,					base=_SCREAMING_SNAKE_CASE					)

        SCREAMING_SNAKE_CASE_				:  Optional[int]           =     resolved(_SCREAMING_SNAKE_CASE					)

        for finfo in members:
              if badpath(finfo.name ,					_SCREAMING_SNAKE_CASE					):
                    logger.error(f"Extraction of {finfo.name} is blocked (illegal path)"					)
              elif finfo.issym() and badlink(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):
                    logger.error(f"Extraction of {finfo.name} is blocked: Symlink to {finfo.linkname}"					)
              elif finfo.islnk() and badlink(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):
                    logger.error(f"Extraction of {finfo.name} is blocked: Hard link to {finfo.linkname}"					)
              else:
                    yield finfo



  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        os.makedirs(_SCREAMING_SNAKE_CASE ,					exist_ok=_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  List[str]           =     tarfile.open(_SCREAMING_SNAKE_CASE					)
        tar_file.extractall(_SCREAMING_SNAKE_CASE ,					members=TarExtractor.safemembers(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)					)
        tar_file.close()

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      List[Any]       =  [B'''\x1F\x8B''']

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        with gzip.open(_SCREAMING_SNAKE_CASE ,					'rb'					) as gzip_file:
              with open(_SCREAMING_SNAKE_CASE ,					'wb'					) as extracted_file:
                    shutil.copyfileobj(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      int       =  [
      B'''PK\x03\x04''',
      B'''PK\x05\x06''',  # empty archive
      B'''PK\x07\x08''',  # spanned archive
  ]

  @classmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE = b""					):





        """simple docstring"""







        if super().is_extractable(_SCREAMING_SNAKE_CASE ,					magic_number=_SCREAMING_SNAKE_CASE					):
              return True
        try:
              # Alternative version of zipfile.is_zipfile that has less false positives, but misses executable zip archives.
              # From: https://github.com/python/cpython/pull/5053
              from zipfile import (
                  _CD_SIGNATURE,
                  _ECD_DISK_NUMBER,
                  _ECD_DISK_START,
                  _ECD_ENTRIES_TOTAL,
                  _ECD_OFFSET,
                  _ECD_SIZE,
                  _EndRecData,
                  sizeCentralDir,
                  stringCentralDir,
                  structCentralDir,
              )

              with open(_SCREAMING_SNAKE_CASE ,					'rb'					) as fp:
                    SCREAMING_SNAKE_CASE_				:  Dict           =     _EndRecData(_SCREAMING_SNAKE_CASE					)
                    if endrec:
                          if endrec[_ECD_ENTRIES_TOTAL] == 0 and endrec[_ECD_SIZE] == 0 and endrec[_ECD_OFFSET] == 0:
                                return True  # Empty zipfiles are still zipfiles
                          elif endrec[_ECD_DISK_NUMBER] == endrec[_ECD_DISK_START]:
                                fp.seek(endrec[_ECD_OFFSET]					)  # Central directory is on the same disk
                                if fp.tell() == endrec[_ECD_OFFSET] and endrec[_ECD_SIZE] >= sizeCentralDir:
                                      SCREAMING_SNAKE_CASE_				:  int           =     fp.read(_SCREAMING_SNAKE_CASE					)  # CD is where we expect it to be
                                      if len(_SCREAMING_SNAKE_CASE					) == sizeCentralDir:
                                            SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     struct.unpack(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)  # CD is the right size
                                            if centdir[_CD_SIGNATURE] == stringCentralDir:
                                                  return True  # First central directory entry  has correct magic number
              return False
        except Exception:  # catch all errors in case future python versions change the zipfile internals
              return False



  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        os.makedirs(_SCREAMING_SNAKE_CASE ,					exist_ok=_SCREAMING_SNAKE_CASE					)
        with zipfile.ZipFile(_SCREAMING_SNAKE_CASE ,					'r'					) as zip_file:
              zip_file.extractall(_SCREAMING_SNAKE_CASE					)
              zip_file.close()

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Any       =  [B'''\xFD\x37\x7A\x58\x5A\x00''']

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        with lzma.open(_SCREAMING_SNAKE_CASE					) as compressed_file:
              with open(_SCREAMING_SNAKE_CASE ,					'wb'					) as extracted_file:
                    shutil.copyfileobj(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Any       =  [B'''Rar!\x1a\x07\x00''', B'''Rar!\x1a\x07\x01\x00''']  # RAR_ID  # RAR5_ID

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        if not config.RARFILE_AVAILABLE:
              raise ImportError('Please pip install rarfile'					)
        import rarfile

        os.makedirs(_SCREAMING_SNAKE_CASE ,					exist_ok=_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  str           =     rarfile.RarFile(_SCREAMING_SNAKE_CASE					)
        rf.extractall(_SCREAMING_SNAKE_CASE					)
        rf.close()

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Optional[Any]       =  [B'''\x28\xb5\x2F\xFD''']

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        if not config.ZSTANDARD_AVAILABLE:
              raise ImportError('Please pip install zstandard'					)
        import zstandard as zstd

        SCREAMING_SNAKE_CASE_				:  Any           =     zstd.ZstdDecompressor()
        with open(_SCREAMING_SNAKE_CASE ,					'rb'					) as ifh, open(_SCREAMING_SNAKE_CASE ,					'wb'					) as ofh:
              dctx.copy_stream(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Union[str, Any]       =  [B'''\x42\x5A\x68''']

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        with bza.open(_SCREAMING_SNAKE_CASE ,					'rb'					) as compressed_file:
              with open(_SCREAMING_SNAKE_CASE ,					'wb'					) as extracted_file:
                    shutil.copyfileobj(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      Optional[Any]       =  [B'''\x37\x7A\xBC\xAF\x27\x1C''']

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        if not config.PY7ZR_AVAILABLE:
              raise ImportError('Please pip install py7zr'					)
        import pyazr

        os.makedirs(_SCREAMING_SNAKE_CASE ,					exist_ok=_SCREAMING_SNAKE_CASE					)
        with pyazr.SevenZipFile(_SCREAMING_SNAKE_CASE ,					'r'					) as archive:
              archive.extractall(_SCREAMING_SNAKE_CASE					)

class  _A		(  __magic_name__):
  SCREAMING_SNAKE_CASE    :      int       =  [B'''\x04\x22\x4D\x18''']

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        if not config.LZ4_AVAILABLE:
              raise ImportError('Please pip install lz4'					)
        import lza.frame

        with lza.frame.open(_SCREAMING_SNAKE_CASE ,					'rb'					) as compressed_file:
              with open(_SCREAMING_SNAKE_CASE ,					'wb'					) as extracted_file:
                    shutil.copyfileobj(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

class  _A		:
  #  Put zip file to the last, b/c it is possible wrongly detected as zip (I guess it means: as tar or gzip)
  SCREAMING_SNAKE_CASE    :      Dict[str, Type[BaseExtractor]]       =  {
      "tar": TarExtractor,
      "gzip": GzipExtractor,
      "zip": ZipExtractor,
      "xz": XzExtractor,
      "rar": RarExtractor,
      "zstd": ZstdExtractor,
      "bz2": BzipaExtractor,
      "7z": SevenZipExtractor,  # <Added version="2.4.0"/>
      "lz4": LzaExtractor,  # <Added version="2.4.0"/>
  }

  @classmethod
  def  UpperCAmelCase    (				cls					):





        """simple docstring"""







        return max(
            len(_SCREAMING_SNAKE_CASE					)
            for extractor in cls.extractors.values()
            if issubclass(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
            for extractor_magic_number in extractor.magic_numbers					)

  @staticmethod
  def  UpperCAmelCase    (				_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        try:
              return MagicNumberBaseExtractor.read_magic_number(_SCREAMING_SNAKE_CASE ,					magic_number_length=_SCREAMING_SNAKE_CASE					)
        except OSError:
              return b""

  @classmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE = False					):





        """simple docstring"""







        warnings.warn(
            'Method \'is_extractable\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '
            'Use \'infer_extractor_format\' instead.' ,					category=_SCREAMING_SNAKE_CASE ,					)
        SCREAMING_SNAKE_CASE_				:  str           =     cls.infer_extractor_format(_SCREAMING_SNAKE_CASE					)
        if extractor_format:
              return True if not return_extractor else (True, cls.extractors[extractor_format])
        return False if not return_extractor else (False, None)

  @classmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE					):  # <Added version="2.4.0"/>





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Tuple           =     cls._get_magic_number_max_length()
        SCREAMING_SNAKE_CASE_				:  List[str]           =     cls._read_magic_number(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        for extractor_format, extractor in cls.extractors.items():
              if extractor.is_extractable(_SCREAMING_SNAKE_CASE ,					magic_number=_SCREAMING_SNAKE_CASE					):
                    return extractor_format



  @classmethod
  def  UpperCAmelCase    (				cls ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE = None ,					_SCREAMING_SNAKE_CASE = "deprecated" ,					):





        """simple docstring"""







        os.makedirs(os.path.dirname(_SCREAMING_SNAKE_CASE					) ,					exist_ok=_SCREAMING_SNAKE_CASE					)
        # Prevent parallel extractions
        SCREAMING_SNAKE_CASE_				:  int           =     str(Path(_SCREAMING_SNAKE_CASE					).with_suffix('.lock'					)					)
        with FileLock(_SCREAMING_SNAKE_CASE					):
              shutil.rmtree(_SCREAMING_SNAKE_CASE ,					ignore_errors=_SCREAMING_SNAKE_CASE					)
              if extractor_format or extractor != "deprecated":
                    if extractor != "deprecated" or not isinstance(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					):  # passed as positional arg
                          warnings.warn(
                              'Parameter \'extractor\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '
                              'Use \'extractor_format\' instead.' ,					category=_SCREAMING_SNAKE_CASE ,					)
                          SCREAMING_SNAKE_CASE_				:  List[str]           =     extractor if extractor != 'deprecated' else extractor_format
                    else:
                          SCREAMING_SNAKE_CASE_				:  List[str]           =     cls.extractors[extractor_format]
                    return extractor.extract(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
              else:
                    warnings.warn(
                        'Parameter \'extractor_format\' was made required in version 2.4.0 and not passing it will raise an '
                        'exception in 3.0.0.' ,					category=_SCREAMING_SNAKE_CASE ,					)
                    for extractor in cls.extractors.values():
                          if extractor.is_extractable(_SCREAMING_SNAKE_CASE					):
                                return extractor.extract(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)









from typing import Any, Dict, List, Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
    from ..image_utils import load_image


if is_torch_available():
    import torch

    from ..models.auto.modeling_auto import MODEL_FOR_OBJECT_DETECTION_MAPPING, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING

lowerCAmelCase     :   Optional[int]						     =  logging.get_logger(__name__)


lowerCAmelCase     :   Optional[int]						     =  Dict[str, Any]
lowerCAmelCase     :   Any						     =  List[Prediction]
@add_end_docstrings(__magic_name__)
class  _A		(  __magic_name__):

  def __init__(				self ,					*_SCREAMING_SNAKE_CASE ,					**_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        super().__init__(*_SCREAMING_SNAKE_CASE ,					**_SCREAMING_SNAKE_CASE					)

        if self.framework == "tf":
              raise ValueError(f"The {self.__class__} is only available in PyTorch."					)

        requires_backends(self ,					'vision'					)
        self.check_model_type(
            dict(MODEL_FOR_OBJECT_DETECTION_MAPPING.items() + MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING.items()					)					)

  def  UpperCAmelCase    (				self ,					**_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Any           =     {}
        if "threshold" in kwargs:
              SCREAMING_SNAKE_CASE_				:  List[str]           =     kwargs['threshold']
        return {}, {}, postprocess_kwargs

  def __call__(				self ,					*_SCREAMING_SNAKE_CASE ,					**_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        return super().__call__(*_SCREAMING_SNAKE_CASE ,					**_SCREAMING_SNAKE_CASE					)

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Dict           =     load_image(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     torch.IntTensor([[image.height, image.width]]					)
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     self.image_processor(images=[image] ,					return_tensors='pt'					)
        if self.tokenizer is not None:
              SCREAMING_SNAKE_CASE_				:  Tuple           =     self.tokenizer(text=inputs['words'] ,					boxes=inputs['boxes'] ,					return_tensors='pt'					)
        SCREAMING_SNAKE_CASE_				:  Optional[int]           =     target_size
        return inputs

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Dict           =     model_inputs.pop('target_size'					)
        SCREAMING_SNAKE_CASE_				:  List[str]           =     self.model(**_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Dict           =     outputs.__class__({'target_size': target_size, **outputs}					)
        if self.tokenizer is not None:
              SCREAMING_SNAKE_CASE_				:  str           =     model_inputs['bbox']
        return model_outputs

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE=0.9					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  List[Any]           =     model_outputs['target_size']
        if self.tokenizer is not None:
              # This is a LayoutLMForTokenClassification variant.
              # The OCR got the boxes and the model classified the words.
              SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_				:  Any           =     target_size[0].tolist()

              def unnormalize(_SCREAMING_SNAKE_CASE					):
                    return self._get_bounding_box(
                        torch.Tensor(
                            [
                                (width * bbox[0] / 1000),
                                (height * bbox[1] / 1000),
                                (width * bbox[2] / 1000),
                                (height * bbox[3] / 1000),
                            ]					)					)

              SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     model_outputs['logits'].squeeze(0					).softmax(dim=-1					).max(dim=-1					)
              SCREAMING_SNAKE_CASE_				:  str           =     [self.model.config.idalabel[prediction] for prediction in classes.tolist()]
              SCREAMING_SNAKE_CASE_				:  List[Any]           =     [unnormalize(_SCREAMING_SNAKE_CASE					) for bbox in model_outputs['bbox'].squeeze(0					)]
              SCREAMING_SNAKE_CASE_				:  Optional[int]           =     ['score', 'label', 'box']
              SCREAMING_SNAKE_CASE_				:  Tuple           =     [dict(zip(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)					) for vals in zip(scores.tolist() ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					) if vals[0] > threshold]
        else:
              # This is a regular ForObjectDetectionModel
              SCREAMING_SNAKE_CASE_				:  Dict           =     self.image_processor.post_process_object_detection(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
              SCREAMING_SNAKE_CASE_				:  int           =     raw_annotations[0]
              SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     raw_annotation['scores']
              SCREAMING_SNAKE_CASE_				:  Any           =     raw_annotation['labels']
              SCREAMING_SNAKE_CASE_				:  Tuple           =     raw_annotation['boxes']

              SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     scores.tolist()
              SCREAMING_SNAKE_CASE_				:  Any           =     [self.model.config.idalabel[label.item()] for label in labels]
              SCREAMING_SNAKE_CASE_				:  Optional[int]           =     [self._get_bounding_box(_SCREAMING_SNAKE_CASE					) for box in boxes]

              # {"scores": [...], ...} --> [{"score":x, ...}, ...]
              SCREAMING_SNAKE_CASE_				:  str           =     ['score', 'label', 'box']
              SCREAMING_SNAKE_CASE_				:  Optional[int]           =     [
                  dict(zip(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)					)
                  for vals in zip(raw_annotation['scores'] ,					raw_annotation['labels'] ,					raw_annotation['boxes']					)
              ]

        return annotation



  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        if self.framework != "pt":
              raise ValueError('The ObjectDetectionPipeline is only available in PyTorch.'					)
        SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_				:  List[Any]           =     box.int().tolist()
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     {
            'xmin': xmin,
            'ymin': ymin,
            'xmax': xmax,
            'ymax': ymax,
        }
        return bbox






