(self, dets, meta)
| 182 | self.kalman_filter = KalmanFilter() |
| 183 | |
| 184 | def post_process(self, dets, meta): |
| 185 | dets = dets.detach().cpu().numpy() |
| 186 | dets = dets.reshape(1, -1, dets.shape[2]) |
| 187 | dets = ctdet_post_process( |
| 188 | dets.copy(), [meta['c']], [meta['s']], |
| 189 | meta['out_height'], meta['out_width'], self.opt.num_classes) |
| 190 | for j in range(1, self.opt.num_classes + 1): |
| 191 | dets[0][j] = np.array(dets[0][j], dtype=np.float32).reshape(-1, 5) |
| 192 | return dets[0] |
| 193 | |
| 194 | def merge_outputs(self, detections): |
| 195 | results = {} |