(self, opt, frame_rate=30)
| 155 | |
| 156 | class BYTETracker(object): |
| 157 | def __init__(self, opt, frame_rate=30): |
| 158 | self.opt = opt |
| 159 | if opt.gpus[0] >= 0: |
| 160 | opt.device = torch.device('cuda') |
| 161 | else: |
| 162 | opt.device = torch.device('cpu') |
| 163 | print('Creating model...') |
| 164 | self.model = create_model(opt.arch, opt.heads, opt.head_conv) |
| 165 | self.model = load_model(self.model, opt.load_model) |
| 166 | self.model = self.model.to(opt.device) |
| 167 | self.model.eval() |
| 168 | |
| 169 | self.tracked_stracks = [] # type: list[STrack] |
| 170 | self.lost_stracks = [] # type: list[STrack] |
| 171 | self.removed_stracks = [] # type: list[STrack] |
| 172 | |
| 173 | self.frame_id = 0 |
| 174 | #self.det_thresh = opt.conf_thres |
| 175 | self.det_thresh = opt.conf_thres + 0.1 |
| 176 | self.buffer_size = int(frame_rate / 30.0 * opt.track_buffer) |
| 177 | self.max_time_lost = self.buffer_size |
| 178 | self.max_per_image = opt.K |
| 179 | self.mean = np.array(opt.mean, dtype=np.float32).reshape(1, 1, 3) |
| 180 | self.std = np.array(opt.std, dtype=np.float32).reshape(1, 1, 3) |
| 181 | |
| 182 | self.kalman_filter = KalmanFilter() |
| 183 | |
| 184 | def post_process(self, dets, meta): |
| 185 | dets = dets.detach().cpu().numpy() |
nothing calls this directly
no test coverage detected