support different nms methods

configs/retinanet_r50_fpn_1x.py

@@ -40,9 +40,9 @@ train_cfg = dict(
     debug=False)
 test_cfg = dict(
     nms_pre=1000,
-    nms_thr=0.5,
     min_bbox_size=0,
     score_thr=0.05,
+    nms=dict(type='nms', iou_thr=0.5),
     max_per_img=100)
 # dataset settings
 dataset_type = 'CocoDataset'

mmdet/models/single_stage_heads/retina_head.py

@@ -282,6 +282,6 @@ class RetinaHead(nn.Module):
         padding = mlvl_scores.new_zeros(mlvl_scores.shape[0], 1)
         mlvl_scores = torch.cat([padding, mlvl_scores], dim=1)
         det_bboxes, det_labels = multiclass_nms(mlvl_proposals, mlvl_scores,
-                                                cfg.score_thr, cfg.nms_thr,
+                                                cfg.score_thr, cfg.nms,
                                                 cfg.max_per_img)
         return det_bboxes, det_labels