class_docstr: This provides Inference Engine for Deepgrow 2D/3D pre-trained model.
  For More Details, Refer https://github.com/Project-MONAI/tutorials/tree/master/deepgrow/ignite
class_docstr_tok: ["This","provides","Inference","Engine","for","Deepgrow","2D\/3D","pre-trained","model",".","For","More","Details",",","Refer","https",":","\/\/github.com\/Project-MONAI\/tutorials\/tree\/master\/deepgrow\/ignite"]
code: def __init__(
      self,
      path,
      network=None,
      type=InferType.DEEPEDIT,
      labels=None,
      dimension=2,
      description="A pre-trained DeepEdit model based on UNET for Endoscopy",
      **kwargs,
  ):
      super().__init__(
          path=path,
          network=network,
          type=type,
          labels=labels,
          dimension=dimension,
          description=description,
          load_strict=False,
          **kwargs,
      )
  
file_path: MONAILabel/sample-apps/endoscopy/lib/infers/deepedit.py
imports: from typing import Callable, Sequence
  import numpy
  from monai.inferers import Inferer, SimpleInferer
  from monai.transforms import Activationsd, AsDiscreted, EnsureChannelFirstd, EnsureTyped, Resized, ScaleIntensityRangeD, SqueezeDimd, ToNumpyd
  from monailabel.deepedit.transforms import AddClickGuidanced, AddGuidanceSignald, ResizeGuidanced
  from monailabel.interfaces.tasks.infer_v2 import InferType
  from monailabel.tasks.infer.basic_infer import BasicInferTask
  from monailabel.transform.post import FindContoursd, Restored
  from monailabel.transform.pre import LoadImageExd
  from monailabel.transform.writer import PolygonWriter
label_desc: Use image node_id 1 to create a new DeepEdit object from inherited base classes: BasicInferTask with example: obj = DeepEdit(path, network, type, labels, dimension, description)