class_docstr: Extracts a single label from all the given classes, the single label is defined by mask_value, the remaining
  labels are kept in others
  
  Args:
      label: key of the label source
      others: other labels storage key, defaults to ``"others"``
      mask_value: the mask_value that will be kept for binarization of the label, defaults to ``"mask_value"``
      min_area: The smallest allowable object size.
      others_value: Value/class for other nuclei;  Use this to separate core nuclei vs others.
      to_binary_mask: Convert mask to binary;  Set it false to restore original class values
class_docstr_tok: ["Extracts","a","single","label","from","all","the","given","classes",",","the","single","label","is","defined","by","mask_value",",","the","remaining","labels","are","kept","in","others","Args",":","label",":","key","of","the","label","source","others",":","other","labels","storage","key",",","defaults","to","``","``","others","''","``","mask_value",":","the","mask_value","that","will","be","kept","for","binarization","of","the","label",",","defaults","to","``","``","mask_value","''","``","min_area",":","The","smallest","allowable","object","size",".","others_value",":","Value\/class","for","other","nuclei",";","Use","this","to","separate","core","nuclei","vs","others",".","to_binary_mask",":","Convert","mask","to","binary",";","Set","it","false","to","restore","original","class","values"]
code: def __init__(
      self,
      keys: KeysCollection,
      others: str = NuclickKeys.OTHERS,
      mask_value: str | None = NuclickKeys.MASK_VALUE,
      min_area: int = 5,
      others_value: int = 0,
      to_binary_mask: bool = True,
  ):
      super().__init__(keys, allow_missing_keys=False)
      self.others = others
      self.mask_value = mask_value
      self.min_area = min_area
      self.others_value = others_value
      self.to_binary_mask = to_binary_mask
  
imports: from __future__ import annotations
  import math
  from typing import Any
  import numpy
  import torch
  from monai.config import KeysCollection, NdarrayOrTensor
  from monai.networks.layers import GaussianFilter
  from monai.transforms import MapTransform, Randomizable, SpatialPad
  from monai.utils import StrEnum, convert_to_numpy, optional_import
label_desc: Use image node_id 1 to create a new SplitLabeld object from inherited base classes: MapTransform with example: obj = SplitLabeld(keys, others, mask_value, min_area, others_value, to_binary_mask)