code: def convert_raw_predictions(
      batch,
      raw_preds,
      records: Sequence[BaseRecord],
      detection_threshold: float,
      keep_images: bool = False,
  ):
      return [
          convert_raw_prediction(
              sample=sample,
              raw_pred=raw_pred,
              record=record,
              detection_threshold=detection_threshold,
              keep_image=keep_images,
          )
          for sample, raw_pred, record in zip(
              zip(*batch), raw_preds, records
          )
      ]
  
file_path: icevision/icevision/models/torchvision/retinanet/prediction.py
imports: from icevision.imports import *
  from icevision.utils import *
  from icevision.core import *
  from icevision.models.utils import _predict_from_dl
  from icevision.data import *
  from icevision.models.torchvision.dataloaders import *
  from icevision.models.inference import *
label_desc: Use image node_id 4 for calling a global function with example usage: convert_raw_predictions(batch, raw_preds, records, detection_threshold, keep_images) and returns: unknown