code: def fridge_ds(
      samples_source, fridge_class_map
  ) -> Tuple[Dataset, Dataset]:
      IMG_SIZE = 384
  
      parser = parsers.VOCBBoxParser(
          annotations_dir=samples_source
          / "fridge/odFridgeObjects/annotations",
          images_dir=samples_source / "fridge/odFridgeObjects/images",
          class_map=fridge_class_map,
      )
  
      data_splitter = RandomSplitter([0.5, 0.5], seed=42)
      train_records, valid_records = parser.parse(data_splitter)
  
      tfms_ = tfms.A.Adapter(
          [A.Resize(IMG_SIZE, IMG_SIZE), A.Normalize()]
      )
  
      train_ds = Dataset(train_records, tfms_)
      valid_ds = Dataset(valid_records, tfms_)
  
      return train_ds, valid_ds
  
imports: import pytest
  from icevision import *
  from icevision.imports import *
  from icevision.models.torchvision import faster_rcnn, keypoint_rcnn
  from icevision.models.ross import efficientdet
  from icevision.models.ross.efficientdet.backbones import *
  import albumentations
label_desc: Use image node_id 8 for calling a global function with example usage: fridge_ds(samples_source, fridge_class_map) and returns: train_ds,  valid_ds