text: from ssd.data.datasets import VOCDataset, COCODataset, MyDataset
  from .coco import coco_evaluation
  from .voc import voc_evaluation
  from .my_dataset import my_evaluation
  
  
  def evaluate(dataset, predictions, output_dir, **kwargs):
      """evaluate dataset using different methods based on dataset type.
      Args:
          dataset: Dataset object
          predictions(list[(boxes, labels, scores)]): Each item in the list represents the
              prediction results for one image. And the index should match the dataset index.
          output_dir: output folder, to save evaluation files or results.
      Returns:
          evaluation result
      """
      args = dict(
          dataset=dataset, predictions=predictions, output_dir=output_dir, **kwargs,
      )
      if isinstance(dataset, VOCDataset):
          return voc_evaluation(**args)
      elif isinstance(dataset, COCODataset):
          return coco_evaluation(**args)
      elif isinstance(dataset, MyDataset):
          return my_evaluation(**args)
      else:
          raise NotImplementedError
  