| 33 | |
| 34 | @staticmethod |
| 35 | def multi_predict(stracks): |
| 36 | if len(stracks) > 0: |
| 37 | multi_mean = np.asarray([st.mean.copy() for st in stracks]) |
| 38 | multi_covariance = np.asarray([st.covariance for st in stracks]) |
| 39 | for i, st in enumerate(stracks): |
| 40 | if st.state != TrackState.Tracked: |
| 41 | multi_mean[i][7] = 0 |
| 42 | multi_mean, multi_covariance = STrack.shared_kalman.multi_predict(multi_mean, multi_covariance) |
| 43 | for i, (mean, cov) in enumerate(zip(multi_mean, multi_covariance)): |
| 44 | stracks[i].mean = mean |
| 45 | stracks[i].covariance = cov |
| 46 | |
| 47 | def activate(self, kalman_filter, frame_id): |
| 48 | """Start a new tracklet""" |