code: def test_threshold(self):
      model_id = "facebook/sam-vit-huge"
      image_segmenter = pipeline("mask-generation", model=model_id)
  
      outputs = image_segmenter(
          "http://images.cocodataset.org/val2017/000000039769.jpg",
          pred_iou_thresh=1,
          points_per_batch=256,
      )
  
      # Shortening by hashing
      new_outupt = []
      for i, o in enumerate(outputs["masks"]):
          new_outupt += [
              {
                  "mask": mask_to_test_readable(o),
                  "scores": outputs["scores"][i],
              }
          ]
  
      self.assertEqual(
          nested_simplify(new_outupt, decimals=4),
          [
              {
                  "mask": {"hash": "115ad19f5f", "shape": (480, 640)},
                  "scores": 1.0444,
              },
              {
                  "mask": {"hash": "6affa964c6", "shape": (480, 640)},
                  "scores": 1.0210,
              },
              {
                  "mask": {"hash": "dfe28a0388", "shape": (480, 640)},
                  "scores": 1.0167,
              },
              {
                  "mask": {"hash": "c0a5f4a318", "shape": (480, 640)},
                  "scores": 1.0132,
              },
              {
                  "mask": {"hash": "fe8065c197", "shape": (480, 640)},
                  "scores": 1.0053,
              },
          ],
      )
  
file_path: transformers/tests/pipelines/test_pipelines_mask_generation.py
imports: import unittest
  from typing import Dict
  import numpy
  from huggingface_hub.utils import insecure_hashlib
  from transformers import MODEL_FOR_MASK_GENERATION_MAPPING, TF_MODEL_FOR_MASK_GENERATION_MAPPING, is_vision_available, pipeline
  from transformers.pipelines import MaskGenerationPipeline
  from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, require_vision, slow
label_desc: Use image node_id 5 for calling the MaskGenerationPipelineTests obj's underlying member method code with example usage: obj.test_threshold() without return types