code: def run_pipeline_test(self, object_detector, examples):
      batch_outputs = object_detector(examples, threshold=0.0)
  
      self.assertEqual(len(examples), len(batch_outputs))
      for outputs in batch_outputs:
          for output_per_image in outputs:
              self.assertGreater(len(output_per_image), 0)
              for detected_object in output_per_image:
                  self.assertEqual(
                      detected_object,
                      {
                          "score": ANY(float),
                          "label": ANY(str),
                          "box": {
                              "xmin": ANY(int),
                              "ymin": ANY(int),
                              "xmax": ANY(int),
                              "ymax": ANY(int),
                          },
                      },
                  )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_zero_shot_object_detection.py
imports: import unittest
  from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_torch, require_vision, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 2 for calling the ZeroShotObjectDetectionPipelineTests obj's underlying member method code with example usage: obj.run_pipeline_test(object_detector, examples) without return types