readme
parent
74b18e72f8
commit
644cdd4e32
|
@ -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
|
||||
|
||||
|
|
|
@ -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,
|
||||
|
|
|
@ -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
|
||||
|
||||
|
|
Loading…
Reference in New Issue