(self, results, public_det=None)
| 177 | self.id_count = 0 |
| 178 | |
| 179 | def step(self, results, public_det=None): |
| 180 | self.frame_id += 1 |
| 181 | activated_starcks = [] |
| 182 | refind_stracks = [] |
| 183 | lost_stracks = [] |
| 184 | removed_stracks = [] |
| 185 | detections = [] |
| 186 | detections_second = [] |
| 187 | |
| 188 | scores = np.array([item['score'] for item in results if item['class'] == 1], np.float32) |
| 189 | bboxes = np.vstack([item['bbox'] for item in results if item['class'] == 1]) # N x 4, x1y1x2y2 |
| 190 | |
| 191 | remain_inds = scores >= self.args.track_thresh |
| 192 | dets = bboxes[remain_inds] |
| 193 | scores_keep = scores[remain_inds] |
| 194 | |
| 195 | |
| 196 | inds_low = scores > self.args.out_thresh |
| 197 | inds_high = scores < self.args.track_thresh |
| 198 | inds_second = np.logical_and(inds_low, inds_high) |
| 199 | dets_second = bboxes[inds_second] |
| 200 | scores_second = scores[inds_second] |
| 201 | |
| 202 | if len(dets) > 0: |
| 203 | '''Detections''' |
| 204 | detections = [STrack(STrack.tlbr_to_tlwh(tlbr), s) for |
| 205 | (tlbr, s) in zip(dets, scores_keep)] |
| 206 | else: |
| 207 | detections = [] |
| 208 | |
| 209 | ''' Add newly detected tracklets to tracked_stracks''' |
| 210 | unconfirmed = [] |
| 211 | tracked_stracks = [] # type: list[STrack] |
| 212 | for track in self.tracked_stracks: |
| 213 | if not track.is_activated: |
| 214 | unconfirmed.append(track) |
| 215 | else: |
| 216 | tracked_stracks.append(track) |
| 217 | |
| 218 | ''' Step 2: First association, with Kalman and IOU''' |
| 219 | strack_pool = joint_stracks(tracked_stracks, self.lost_stracks) |
| 220 | # Predict the current location with KF |
| 221 | STrack.multi_predict(strack_pool) |
| 222 | dists = matching.iou_distance(strack_pool, detections) |
| 223 | #dists = matching.fuse_motion(self.kalman_filter, dists, strack_pool, detections) |
| 224 | matches, u_track, u_detection = matching.linear_assignment(dists, thresh=0.9) |
| 225 | |
| 226 | for itracked, idet in matches: |
| 227 | track = strack_pool[itracked] |
| 228 | det = detections[idet] |
| 229 | if track.state == TrackState.Tracked: |
| 230 | track.update(detections[idet], self.frame_id) |
| 231 | activated_starcks.append(track) |
| 232 | else: |
| 233 | track.re_activate(det, self.frame_id, new_id=False) |
| 234 | refind_stracks.append(track) |
| 235 | |
| 236 | ''' Step 3: Second association, association the untrack to the low score detections， with IOU''' |
nothing calls this directly
no test coverage detected