code: def prepare_image_inputs(
      self, equal_resolution=False, numpify=False, torchify=False
  ):
      return prepare_image_inputs(
          batch_size=self.batch_size,
          num_channels=self.num_channels,
          min_resolution=self.min_resolution,
          max_resolution=self.max_resolution,
          equal_resolution=equal_resolution,
          numpify=numpify,
          torchify=torchify,
      )
  
imports: import json
  import pathlib
  import unittest
  from transformers.testing_utils import require_torch, require_vision, slow
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_image_processing_common import AnnotationFormatTestMixin, ImageProcessingTestMixin, prepare_image_inputs
label_desc: Use image node_id 5 for calling the ConditionalDetrImageProcessingTester obj's underlying member method code with example usage: obj.prepare_image_inputs(equal_resolution, numpify, torchify) and returns: prepare_image_inputs