pull/3/head
Dahun Kim 2021-08-31 19:18:31 +09:00
parent 74b18e72f8
commit 644cdd4e32
3 changed files with 8 additions and 17 deletions

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@ -22,14 +22,6 @@ Humans can recognize novel objects in this image despite having never seen them
<img src="./images/epic.png" width="500"> <img src="./images/oln_overview.png" width="500"> <br/>
## Cross-category generalization on COCO
We train OLN on COCO VOC categories, and test on non-VOC categories. Note our AR@k evaluation does not count those proposals on the 'seen' classes into the budget (k), to avoid evaluating recall on see-class objects.
| Method | AUC | AR@10 | AR@30 | AR@100 | AR@300 | AR@1000 | Download |
|:--------------:|:-----:|:-----:|:-----:|:------:|:------:|:-------:|:--------:|
| OLN-Box | 24.8 | 18.0 | 26.4 | 33.4 | 39.0 | 45.0 | [model](https://drive.google.com/uc?id=1uL6TRhpSILvWeR6DZ0x9K9VywrQXQvq9) |
## Disclaimer

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@ -105,7 +105,7 @@ model = dict(
nms_pre=2000,
nms_post=2000,
max_num=2000,
nms_thr=1.0, # nms is not used.
nms_thr=0.7,
min_bbox_size=0),
rcnn=dict(
assigner=dict(
@ -129,7 +129,7 @@ model = dict(
nms_pre=2000,
nms_post=2000,
max_num=2000,
nms_thr=1.0, # nms is not used.
nms_thr=0.7,
min_bbox_size=0),
rcnn=dict(
score_thr=0.0,

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@ -688,13 +688,12 @@ class OlnRPNHead(RPNHead):
ids = ids[valid_inds]
nms_cfg = dict(type='nms', iou_threshold=cfg.nms_thr)
if nms_cfg in [0.0, 1.0]:
# No NMS:
dets = torch.cat([proposals, scores.unsqueeze(1)], 1)
else:
dets, keep = batched_nms(proposals, scores, ids, nms_cfg)
return dets[:cfg.nms_post]
# No NMS:
dets = torch.cat([proposals, scores.unsqueeze(1)], 1)
# else:
# dets, keep = batched_nms(proposals, scores, ids, nms_cfg)
# return dets[:cfg.nms_post]
return dets