code: def test_predict(wrapper, data_format, tmp_path):
      image = create_image(
          grayscale=False, data_format=data_format, tmp_path=tmp_path
      )
  
      result = wrapper.predict(image)
      assert "predicted_class" in result
      assert "probabilities" in result
      print(result)
  
      assert isinstance(result["predicted_class"], int)
      assert isinstance(result["probabilities"], np.ndarray)
      assert result["probabilities"].ndim == 1
  
file_path: traintool/tests/image_classification/test_sklearn_models.py
imports: import comet_ml
  import pytest
  import numpy
  from sklearn.ensemble import RandomForestClassifier
  from tensorboardX import SummaryWriter
  from conftest import create_dataset, create_image
  from traintool.image_classification import SklearnImageClassificationWrapper
  from traintool.utils import DummyExperiment
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict(wrapper, data_format, tmp_path) without return types