code: def test_layoutlm(self):
      model_id = "Narsil/layoutlmv3-finetuned-funsd"
      threshold = 0.9993
  
      object_detector = pipeline(
          "object-detection", model=model_id, threshold=threshold
      )
  
      outputs = object_detector(
          "https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png"
      )
      self.assertEqual(
          nested_simplify(outputs, decimals=4),
          [
              {
                  "score": 0.9993,
                  "label": "I-ANSWER",
                  "box": {
                      "xmin": 294,
                      "ymin": 254,
                      "xmax": 343,
                      "ymax": 264,
                  },
              },
              {
                  "score": 0.9993,
                  "label": "I-ANSWER",
                  "box": {
                      "xmin": 294,
                      "ymin": 254,
                      "xmax": 343,
                      "ymax": 264,
                  },
              },
          ],
      )
  
file_path: 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 is_pipeline_test, nested_simplify, require_pytesseract, require_tf, require_timm, require_torch, require_vision, slow
  from .test_pipelines_common import ANY
label_desc: Use image node_id 8 for calling the ObjectDetectionPipelineTests obj's underlying member method code with example usage: obj.test_layoutlm() without return types