docstr: Add current model predictions (usually the result of a batch) to the tracking
          
docstr_tok: ["Add","current","model","predictions","(","usually","the","result","of","a","batch",")","to","the","tracking"]
code: def track(
      self,
      model: model_interface.TrackerInterface,
      full_res=False,
      **kwargs,
  ):
      """Add current model predictions (usually the result of a batch) to the tracking"""
      super().track(model)
  
      # Set conv type
      self._conv_type = model.conv_type
  
      # Train mode or low res, nothing special to do
      if (
          not full_res
          or self._stage == "train"
          or kwargs.get("data") is None
      ):
          return
  
      self._vote(kwargs.get("data"), model.get_output())
  
file_path: torch-points3d/torch_points3d/metrics/scannet_segmentation_tracker.py
imports: import os.path
  from typing import Dict, Any
  import logging
  import numpy
  import torch
  from torch_geometric.nn.unpool import knn_interpolate
  from torch_points3d.metrics.confusion_matrix import ConfusionMatrix
  from torch_points3d.metrics.segmentation_tracker import SegmentationTracker
  from torch_points3d.datasets.segmentation import IGNORE_LABEL
  from torch_points3d.core.data_transform import SaveOriginalPosId
  from torch_points3d.models import model_interface
label_desc: Use image node_id 2 for calling the ScannetSegmentationTracker obj's underlying member method code with example usage: obj.track(model, full_res) without return types