Method update

tutorials/motr/byte_tracker.py:164–286

(self, output_results)

        self.kalman_filter = KalmanFilter()

    def update(self, output_results):
        self.frame_id += 1
        activated_starcks = []
        refind_stracks = []
        lost_stracks = []
        removed_stracks = []

        
        scores = output_results[:, 4]
        bboxes = output_results[:, :4]  # x1y1x2y2
        
        remain_inds = scores > self.track_thresh
        dets = bboxes[remain_inds]
        scores_keep = scores[remain_inds]
        
        
        inds_low = scores > self.low_thresh
        inds_high = scores < self.track_thresh
        inds_second = np.logical_and(inds_low, inds_high)
        dets_second = bboxes[inds_second]
        scores_second = scores[inds_second]

        
        if len(dets) > 0:
            '''Detections'''
            detections = [STrack(STrack.tlbr_to_tlwh(tlbr), s) for
                          (tlbr, s) in zip(dets, scores_keep)]
        else:
            detections = []

        ''' Add newly detected tracklets to tracked_stracks'''
        unconfirmed = []
        tracked_stracks = []  # type: list[STrack]
        for track in self.tracked_stracks:
            if not track.is_activated:
                unconfirmed.append(track)
            else:
                tracked_stracks.append(track)

        ''' Step 2: First association, with Kalman and IOU'''
        strack_pool = joint_stracks(tracked_stracks, self.lost_stracks)
        # Predict the current location with KF
        STrack.multi_predict(strack_pool)
        dists = matching.iou_distance(strack_pool, detections)
        matches, u_track, u_detection = matching.linear_assignment(dists, thresh=0.8)

        for itracked, idet in matches:
            track = strack_pool[itracked]
            det = detections[idet]
            if track.state == TrackState.Tracked:
                track.update(detections[idet], self.frame_id)
                activated_starcks.append(track)
            else:
                track.re_activate(det, self.frame_id, new_id=False)
                refind_stracks.append(track)

        ''' Step 3: Second association, with IOU'''
        # association the untrack to the low score detections