minor fix

README.md

@@ -19,7 +19,7 @@ We train OLN on COCO VOC categories, and test on non-VOC categories. Note our AR
 
 |     Method     |  AUC  | AR@10 | AR@30 | AR@100 | AR@300 | AR@1000 |
 |:--------------:|:-----:|:-----:|:-----:|:------:|:------:|:-------:|
-|    OLN-Box     | 24.8  | 18.1  | 26.5  |  33.5  |  39.0  |  45.0   |
+|    OLN-Box     | 24.8  | 18.0  | 26.4  |  33.4  |  39.0  |  45.0   |
 
 
 

configs/oln_box/class_agn_faster_rcnn.py

@@ -75,7 +75,7 @@ model = dict(
             nms_pre=2000,
             nms_post=2000,
             max_num=2000,
-            nms_thr=1.0,
+            nms_thr=0.7,
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(

mmdet/models/dense_heads/oln_rpn_head.py

@@ -687,13 +687,14 @@ class OlnRPNHead(RPNHead):
                 scores = scores[valid_inds]
                 ids = ids[valid_inds]
 
-        # TODO: remove the hard coded nms type
-        # nms_cfg = dict(type='nms', iou_threshold=cfg.nms_thr)
-        # dets, keep = batched_nms(proposals, scores, ids, nms_cfg)
-        # return dets[:cfg.nms_post]
+        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)
         return dets