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, **kwargs):
      """Add current model predictions (usually the result of a batch) to the tracking"""
      if not self._dataset.has_labels(self._stage):
          return
  
      super().track(model)
  
      outputs = model.get_output()
      targets = model.get_labels()
      self._compute_metrics(outputs, targets)
  
file_path: torch-points3d/torch_points3d/metrics/segmentation_tracker.py
imports: from typing import Dict, Any
  import torch
  import wandb
  import numpy
  from torch_points3d.metrics.confusion_matrix import ConfusionMatrix
  from torch_points3d.metrics.base_tracker import BaseTracker, meter_value
  from torch_points3d.metrics.meters import APMeter
  from torch_points3d.datasets.segmentation import IGNORE_LABEL
  from torch_points3d.models import model_interface
label_desc: Use image node_id 5 for calling the SegmentationTracker obj's underlying member method code with example usage: obj.track(model) without return types