code: def identify_candidates(self, panoptic_seg, segments_info):
      potential_mask_ids = []
      for segment in segments_info:
          if not segment["isthing"]:
              continue
          mask = (
              (panoptic_seg == segment["id"])
              .int()
              .detach()
              .cpu()
              .numpy()
          )
          area = mask.sum().item() / np.prod(panoptic_seg.shape)
          if area >= self.max_object_area:
              continue
          potential_mask_ids.append(segment["id"])
      return potential_mask_ids
  
imports: import enum
  from copy import deepcopy
  import numpy
  from skimage import img_as_ubyte
  from skimage.transform import rescale, resize
  from .countless2d import zero_corrected_countless
label_desc: Use image node_id 4 for calling the SegmentationMask obj's underlying member method code with example usage: obj.identify_candidates(panoptic_seg, segments_info) and returns: potential_mask_ids