def METHOD_NAME(self):
    point_cloud_filename = os.path.join(self.test_data, "infer_data", "seq08_f000000.bin")
    temp_prediction_path = os.path.join(self.temp_dir, "prediction.png")
    point_cloud = SemanticKittiDataset.load_point_cloud(point_cloud_filename)
    self.assertIsInstance(point_cloud, PointCloud)
    learner = EfficientLpsLearner(self.config_file)
    learner.load(self.model_weights)
    prediction = learner.infer(point_cloud, projected=False)[:2]
    # Make sure that no file has been written to that path yet
    if os.path.exists(temp_prediction_path):
        rmfile(temp_prediction_path)
    EfficientLpsLearner.visualize(point_cloud, prediction, show_figure=False, save_figure=True,
                                  figure_filename=temp_prediction_path)
    self.assertTrue(os.path.exists(temp_prediction_path))
    rmfile(temp_prediction_path)