class_docstr: This provides Inference Engine for pre-trained spine localization (UNet) model.
code: def inferer(self, data=None) -> Inferer:
      return SlidingWindowInferer(
          roi_size=self.roi_size,
          sw_batch_size=2,
          overlap=0.4,
          padding_mode="replicate",
          mode="gaussian",
      )
  
file_path: MONAILabel/sample-apps/radiology/lib/infers/localization_spine.py
imports: from typing import Callable, Sequence
  from lib.transforms.transforms import BinaryMaskd, CacheObjectd
  from monai.inferers import Inferer, SlidingWindowInferer
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, EnsureTyped, GaussianSmoothd, KeepLargestConnectedComponentd, LoadImaged, ScaleIntensityd, ScaleIntensityRanged, Spacingd
  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 3 for calling the LocalizationSpine obj's underlying member method code with example usage: obj.inferer(data) and returns: SlidingWindowInferer