code: def test_should_raise_if_annotation_format_invalid(self):
      image_processor_dict = (
          self.image_processor_tester.prepare_image_processor_dict()
      )
  
      with open(
          "./tests/fixtures/tests_samples/COCO/coco_annotations.txt",
          "r",
      ) as f:
          detection_target = json.loads(f.read())
  
      annotations = {"image_id": 39769, "annotations": detection_target}
  
      params = {
          "images": Image.open(
              "./tests/fixtures/tests_samples/COCO/000000039769.png"
          ),
          "annotations": annotations,
          "return_tensors": "pt",
      }
  
      image_processor_params = {
          **image_processor_dict,
          **{"format": "_INVALID_FORMAT_"},
      }
      image_processor = self.image_processing_class(
          **image_processor_params
      )
  
      with self.assertRaises(ValueError) as e:
          image_processor(**params)
  
      self.assertTrue(
          str(e.exception).startswith(
              "_INVALID_FORMAT_ is not a valid AnnotationFormat"
          )
      )
  
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 DetrImageProcessingTest obj's underlying member method code with example usage: obj.test_should_raise_if_annotation_format_invalid() without return types