def update(self, detections, classes):
        """Perform measurement update and track management.
        Parameters
        ----------
        detections : List[deep_sort.detection.Detection]
            A list of detections at the current time step.
        """
        # Run matching cascade.
        matches, unmatched_tracks, unmatched_detections = \
            self._match(detections)

        # Update track set.
        for track_idx, detection_idx in matches:
            self.tracks[track_idx].update(
                self.kf, detections[detection_idx])
        for track_idx in unmatched_tracks:
            self.tracks[track_idx].mark_missed()
        for detection_idx in unmatched_detections:
            self._initiate_track(detections[detection_idx], classes[detection_idx].item())
        self.tracks = [t for t in self.tracks if not t.is_deleted()]

        # Update distance metric.
        active_targets = [t.track_id for t in self.tracks if t.is_confirmed()]
        features, targets = [], []
        for track in self.tracks:
            if not track.is_confirmed():
                continue
            features += track.features
            targets += [track.track_id for _ in track.features]
            track.features = []
        self.metric.partial_fit(
            np.asarray(features), np.asarray(targets), active_targets)
Perform measurement update and track management.
        Parameters
        ----------
        detections : List[deep_sort.detection.Detection]
            A list of detections at the current time step.
        
trackers/deepsort_tracker/deepsort.py