class_docstr: Constructs an OWL-ViT processor which wraps [`OwlViTImageProcessor`] and [`CLIPTokenizer`]/[`CLIPTokenizerFast`]
  into a single processor that interits both the image processor and tokenizer functionalities. See the
  [`~OwlViTProcessor.__call__`] and [`~OwlViTProcessor.decode`] for more information.
  
  Args:
      image_processor ([`OwlViTImageProcessor`], *optional*):
          The image processor is a required input.
      tokenizer ([`CLIPTokenizer`, `CLIPTokenizerFast`], *optional*):
          The tokenizer is a required input.
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code: def __init__(self, image_processor=None, tokenizer=None, **kwargs):
      feature_extractor = None
      if "feature_extractor" in kwargs:
          warnings.warn(
              "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
              " instead.",
              FutureWarning,
          )
          feature_extractor = kwargs.pop("feature_extractor")
  
      image_processor = (
          image_processor
          if image_processor is not None
          else feature_extractor
      )
      if image_processor is None:
          raise ValueError("You need to specify an `image_processor`.")
      if tokenizer is None:
          raise ValueError("You need to specify a `tokenizer`.")
  
      super().__init__(image_processor, tokenizer)
  
file_path: transformers/src/transformers/models/owlvit/processing_owlvit.py
imports: import warnings
  from typing import List
  import numpy
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
  from ...utils import is_flax_available, is_tf_available, is_torch_available
label_desc: Use image node_id 1 to create a new OwlViTProcessor object from inherited base classes: ProcessorMixin with example: obj = OwlViTProcessor(image_processor, tokenizer)