code: def test_imagelab_max_prevalence(
      self,
      image_dataset,
      pred_probs,
      features,
      capsys,
      num_datalab_issues,
      monkeypatch,
  ):
      max_prevalence = 0
      monkeypatch.setattr(
          imagelab, "IMAGELAB_ISSUES_MAX_PREVALENCE", max_prevalence
      )
      datalab = Datalab(
          data=image_dataset,
          label_name=LABEL_NAME,
          image_key=IMAGE_NAME,
      )
  
      datalab.find_issues(pred_probs=pred_probs, features=features)
      captured = capsys.readouterr()
      assert (
          "Finding dark, light, low_information, odd_aspect_ratio, odd_size, grayscale, blurry images"
          in captured.out
      )
      assert (
          f"from potential issues in the dataset as it exceeds max_prevalence={max_prevalence}"
          in captured.out
      )
  
      issue_summary = datalab.get_issue_summary()
      assert len(issue_summary) == 1 + num_datalab_issues
  
file_path: cleanlab/tests/datalab/test_cleanvision_integration.py
imports: import matplotlib.pyplot
  import numpy
  import pytest
  import pandas
  from cleanlab import Datalab
  import cleanlab.datalab.internal.adapter.imagelab
label_desc: Use image node_id 7 for calling the TestCleanvisionIntegration obj's underlying member method code with example usage: obj.test_imagelab_max_prevalence(image_dataset, pred_probs, features, capsys, num_datalab_issues, monkeypatch) without return types