class_docstr: Generate instance centroid using `skimage.measure.centroid`.
  
  Args:
      dtype: the data type of output centroid.
class_docstr_tok: ["Generate","instance","centroid","using","`","skimage.measure.centroid","`",".","Args",":","dtype",":","the","data","type","of","output","centroid","."]
code: def __init__(self, dtype: DtypeLike | None = int) -> None:
      self.dtype = dtype
  
imports: from __future__ import annotations
  import warnings
  from typing import Callable, Sequence
  import numpy
  import torch
  from monai.config.type_definitions import DtypeLike, NdarrayOrTensor
  from monai.transforms import Activations, AsDiscrete, BoundingRect, FillHoles, GaussianSmooth, RemoveSmallObjects, SobelGradients
  from monai.transforms.transform import Transform
  from monai.transforms.utils_pytorch_numpy_unification import max, maximum, min, sum, unique
  from monai.utils import TransformBackends, convert_to_numpy, optional_import
  from monai.utils.misc import ensure_tuple_rep
  from monai.utils.type_conversion import convert_to_dst_type, convert_to_tensor
label_desc: Use image node_id 1 to create a new GenerateInstanceCentroid object from inherited base classes: Transform with example: obj = GenerateInstanceCentroid(dtype)