code: def __call__(self, data):
      d = dict(data)
      for key in self.keys:
          label = (
              convert_to_numpy(d[key])
              if isinstance(d[key], torch.Tensor)
              else d[key]
          )
          label = label.astype(np.uint8)
          if self.min_hole:
              label = remove_small_holes(
                  label, area_threshold=self.min_hole
              )
          label = binary_fill_holes(label).astype(np.uint8)
          if self.min_size:
              label = remove_small_objects(
                  label, min_size=self.min_size
              )
  
          d[key] = np.where(label > 0, d[key], 0)
      return d
  
imports: import logging
  import pathlib
  import numpy
  import openslide
  import torch
  from monai.config import KeysCollection
  from monai.data import MetaTensor
  from monai.transforms import MapTransform
  from monai.utils import PostFix, convert_to_numpy, ensure_tuple
  from PIL import Image
  from scipy.ndimage import binary_fill_holes
  from skimage.morphology import remove_small_holes, remove_small_objects
label_desc: Use image node_id 2 for calling the PostFilterLabeld obj's underlying member method code with example usage: obj.__call__(data) and returns: d