class_docstr: This provides Inference Engine for pre-trained model over Multi Atlas Labeling Beyond The Cranial Vault (BTCV)
  dataset.
code: def post_transforms(self, data=None) -> Sequence[Callable]:
      return [
          EnsureTyped(
              keys="pred", device=data.get("device") if data else None
          ),
          Activationsd(keys="pred", softmax=True),
          AsDiscreted(keys="pred", argmax=True),
          SqueezeDimd(keys="pred", dim=0),
          ToNumpyd(keys="pred"),
          Restored(
              keys="pred",
              ref_image="image",
              config_labels=self.labels
              if data.get("restore_label_idx", False)
              else None,
          ),
          GetCentroidsd(keys="pred", centroids_key="centroids"),
      ]
  
file_path: MONAILabel/sample-apps/radiology/lib/infers/deepedit.py
imports: import logging
  from typing import Callable, Sequence, Union
  from lib.transforms.transforms import GetCentroidsd
  from monai.apps.deepedit.transforms import AddGuidanceFromPointsDeepEditd, AddGuidanceSignalDeepEditd, DiscardAddGuidanced, ResizeGuidanceMultipleLabelDeepEditd
  from monai.inferers import Inferer, SimpleInferer
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, EnsureTyped, LoadImaged, Orientationd, Resized, ScaleIntensityRanged, SqueezeDimd, ToNumpyd
  from monailabel.interfaces.tasks.infer_v2 import InferType
  from monailabel.tasks.infer.basic_infer import BasicInferTask
  from monailabel.transform.post import Restored
label_desc: Use image node_id 5 for calling the DeepEdit obj's underlying member method code with example usage: obj.post_transforms(data) and returns: list