(keep: torch.Tensor, masks_result)
| 209 | return pad |
| 210 | |
| 211 | def filter(keep: torch.Tensor, masks_result) -> None: |
| 212 | keep = keep.int().cpu().numpy() |
| 213 | result_keep = [] |
| 214 | for i, m in enumerate(masks_result): |
| 215 | if i in keep: result_keep.append(m) |
| 216 | return result_keep |
| 217 | |
| 218 | def mask_nms(masks, scores, iou_thr=0.7, score_thr=0.1, inner_thr=0.2, **kwargs): |
| 219 | """ |