              Contains the batch that is currently being passed through the plugin process
  
          Returns
          -------
          dict
              The batch with input processed
          """
          if not self._additional_keys:
              existing_keys = list(batch.keys())
  
 
</s> remove         batch: dict
 </s> add         batch: :class:`AlignerBatch` </s> remove         batch : dict
 </s> add         batch : :class:`AlignerBatch` </s> remove         if not self._additional_keys:
            existing_keys = list(batch.keys())

 </s> add  </s> remove             subbatch = {key: val
                        for key, val in batch.items()
                        if key not in ["feed", "prediction"] + self._additional_keys}
            subbatch["prediction"] = batch["prediction"][idx]
            for key in self._additional_keys:
                subbatch[key] = batch[key][idx]
 </s> add             # Create a pseudo object that only populates the data, feed and prediction slots with
            # the current re-feed iteration
            subbatch = AlignerBatch(image=batch.image,
                                    detected_faces=batch.detected_faces,
                                    filename=batch.filename,
                                    feed=[batch.feed[idx]],
                                    prediction=batch.prediction[idx],
                                    data=[batch.data[idx]])
        :class:`AlignerBatch`
              Contains the batch that is currently being passed through the plugin process
  
          Returns
          -------
        :class:`AlignerBatch`
              The batch with input processed
          """
          if not self._additional_keys:
              existing_keys = list(batch.keys())
  
keep keep keep keep replace keep keep keep keep keep
 Extract updates:
  - Default CPU detector to MTCNN
  - add basic Aligner false positive filters
  - Typing: align + plugins
  - Use specific AlignerBatch class for alignment
  - 
plugins/extract/align/_base.py