(self, opt, frame_rate=30)
| 177 | |
| 178 | class JDETracker(object): |
| 179 | def __init__(self, opt, frame_rate=30): |
| 180 | self.opt = opt |
| 181 | if opt.gpus[0] >= 0: |
| 182 | opt.device = torch.device('cuda') |
| 183 | else: |
| 184 | opt.device = torch.device('cpu') |
| 185 | print('Creating model...') |
| 186 | self.model = create_model(opt.arch, opt.heads, opt.head_conv) |
| 187 | self.model = load_model(self.model, opt.load_model) |
| 188 | self.model = self.model.to(opt.device) |
| 189 | self.model.eval() |
| 190 | |
| 191 | self.tracked_stracks = [] # type: list[STrack] |
| 192 | self.lost_stracks = [] # type: list[STrack] |
| 193 | self.removed_stracks = [] # type: list[STrack] |
| 194 | |
| 195 | self.frame_id = 0 |
| 196 | #self.det_thresh = opt.conf_thres |
| 197 | self.det_thresh = opt.conf_thres + 0.1 |
| 198 | self.buffer_size = int(frame_rate / 30.0 * opt.track_buffer) |
| 199 | self.max_time_lost = self.buffer_size |
| 200 | self.max_per_image = opt.K |
| 201 | self.mean = np.array(opt.mean, dtype=np.float32).reshape(1, 1, 3) |
| 202 | self.std = np.array(opt.std, dtype=np.float32).reshape(1, 1, 3) |
| 203 | |
| 204 | self.kalman_filter = KalmanFilter() |
| 205 | |
| 206 | def post_process(self, dets, meta): |
| 207 | dets = dets.detach().cpu().numpy() |
nothing calls this directly
no test coverage detected