code: def run_pipeline_test(self, object_detector, examples):
      outputs = object_detector(
          "./tests/fixtures/tests_samples/COCO/000000039769.png",
          threshold=0.0,
      )
  
      self.assertGreater(len(outputs), 0)
      for detected_object in outputs:
          self.assertEqual(
              detected_object,
              {
                  "score": ANY(float),
                  "label": ANY(str),
                  "box": {
                      "xmin": ANY(int),
                      "ymin": ANY(int),
                      "xmax": ANY(int),
                      "ymax": ANY(int),
                  },
              },
          )
  
      import datasets
  
      dataset = datasets.load_dataset(
          "hf-internal-testing/fixtures_image_utils",
          "image",
          split="test",
      )
  
      batch = [
          Image.open(
              "./tests/fixtures/tests_samples/COCO/000000039769.png"
          ),
          "http://images.cocodataset.org/val2017/000000039769.jpg",
          # RGBA
          dataset[0]["file"],
          # LA
          dataset[1]["file"],
          # L
          dataset[2]["file"],
      ]
      batch_outputs = object_detector(batch, threshold=0.0)
  
      self.assertEqual(len(batch), len(batch_outputs))
      for outputs in batch_outputs:
          self.assertGreater(len(outputs), 0)
          for detected_object in outputs:
              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_object_detection.py
imports: import unittest
  from transformers import MODEL_FOR_OBJECT_DETECTION_MAPPING, AutoFeatureExtractor, AutoModelForObjectDetection, ObjectDetectionPipeline, is_vision_available, pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_timm, require_torch, require_vision, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 2 for calling the ObjectDetectionPipelineTests obj's underlying member method code with example usage: obj.run_pipeline_test(object_detector, examples) without return types