refactor nms config (open-mmlab#4636)

* rpn head refactor

* guided anchor

* add deprecate warning

* add more warning for set ori augs

* fix unitest

* change base

* cascade rpn

* cornernet and centri

* grid frcnn ok

* ga anchor ok

* legacy ok

* pisa ok

* tridnet ok

* fix tutorals

* use ConfigDict

configs/_base_/models/cascade_mask_rcnn_r50_fpn.py

@@ -126,11 +126,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=[
             dict(
@@ -187,11 +185,9 @@
         ]),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=1000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/cascade_rcnn_r50_fpn.py

@@ -113,11 +113,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=[
             dict(
@@ -171,11 +169,9 @@
         ]),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=1000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/faster_rcnn_r50_caffe_c4.py

@@ -80,11 +80,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=12000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(
@@ -104,11 +102,9 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=6000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/faster_rcnn_r50_caffe_dc5.py

@@ -71,11 +71,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=12000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(
@@ -95,11 +93,9 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
+            nms=dict(type='nms', iou_threshold=0.7),
             nms_pre=6000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/faster_rcnn_r50_fpn.py

@@ -72,11 +72,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(
@@ -96,11 +94,9 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=1000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/mask_rcnn_r50_caffe_c4.py

@@ -89,11 +89,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=12000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(
@@ -114,11 +112,9 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=6000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            nms=dict(type='nms', iou_threshold=0.7),
+            max_per_img=1000,
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/mask_rcnn_r50_fpn.py

@@ -86,11 +86,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(
@@ -111,11 +109,9 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=1000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.05,

configs/_base_/models/rpn_r50_caffe_c4.py

@@ -50,9 +50,7 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=12000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0)))

configs/_base_/models/rpn_r50_fpn.py

@@ -1,4 +1,5 @@
 # model settings
+
 model = dict(
     type='RPN',
     pretrained='torchvision://resnet50',
@@ -52,9 +53,7 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0)))

configs/cascade_rpn/crpn_faster_rcnn_r50_caffe_fpn_1x_coco.py

@@ -80,12 +80,13 @@
                 pos_weight=-1,
                 debug=False)
         ],
-        rpn_proposal=dict(max_num=300, nms_thr=0.8),
+        rpn_proposal=dict(max_per_img=300, nms=dict(iou_threshold=0.8)),
         rcnn=dict(
             assigner=dict(
                 pos_iou_thr=0.65, neg_iou_thr=0.65, min_pos_iou=0.65),
             sampler=dict(type='RandomSampler', num=256))),
     test_cfg=dict(
-        rpn=dict(max_num=300, nms_thr=0.8), rcnn=dict(score_thr=1e-3)))
+        rpn=dict(max_per_img=300, nms=dict(iou_threshold=0.8)),
+        rcnn=dict(score_thr=1e-3)))
 optimizer_config = dict(
     _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))

configs/cascade_rpn/crpn_r50_caffe_fpn_1x_coco.py

@@ -69,11 +69,9 @@
     ]),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.8,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.8),
             min_bbox_size=0)))
 optimizer_config = dict(
     _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))

configs/centripetalnet/centripetalnet_hourglass104_mstest_16x6_210e_coco.py

@@ -34,7 +34,7 @@
         distance_threshold=0.5,
         score_thr=0.05,
         max_per_img=100,
-        nms_cfg=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
+        nms=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
 # data settings
 img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)

configs/cornernet/cornernet_hourglass104_mstest_10x5_210e_coco.py

@@ -34,7 +34,7 @@
         distance_threshold=0.5,
         score_thr=0.05,
         max_per_img=100,
-        nms_cfg=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
+        nms=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
 # data settings
 img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)

configs/cornernet/cornernet_hourglass104_mstest_32x3_210e_coco.py

@@ -34,7 +34,7 @@
         distance_threshold=0.5,
         score_thr=0.05,
         max_per_img=100,
-        nms_cfg=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
+        nms=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
 # data settings
 img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)

configs/cornernet/cornernet_hourglass104_mstest_8x6_210e_coco.py

@@ -34,7 +34,7 @@
         distance_threshold=0.5,
         score_thr=0.05,
         max_per_img=100,
-        nms_cfg=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
+        nms=dict(type='soft_nms', iou_threshold=0.5, method='gaussian')))
 # data settings
 img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)

configs/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x.py

@@ -17,12 +17,12 @@
                 type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
             loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))),
     train_cfg=dict(
-        rpn_proposal=dict(nms_thr=0.85),
+        rpn_proposal=dict(nms=dict(iou_threshold=0.85)),
         rcnn=dict(
             dynamic_rcnn=dict(
                 iou_topk=75,
                 beta_topk=10,
                 update_iter_interval=100,
                 initial_iou=0.4,
                 initial_beta=1.0))),
-    test_cfg=dict(rpn=dict(nms_thr=0.85)))
+    test_cfg=dict(rpn=dict(nms=dict(iou_threshold=0.85))))

configs/grid_rcnn/grid_rcnn_r50_fpn_gn-head_1x_coco.py

@@ -1,4 +1,4 @@
-_base_ = ['../grid_rcnn/grid_rcnn_r50_fpn_gn-head_2x_coco.py']
+_base_ = ['grid_rcnn_r50_fpn_gn-head_2x_coco.py']
 # learning policy
 lr_config = dict(
     policy='step',

configs/grid_rcnn/grid_rcnn_r50_fpn_gn-head_2x_coco.py

@@ -87,11 +87,9 @@
             pos_weight=-1,
             debug=False),
         rpn_proposal=dict(
-            nms_across_levels=False,
             nms_pre=2000,
-            nms_post=2000,
-            max_num=2000,
-            nms_thr=0.7,
+            max_per_img=2000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             assigner=dict(
@@ -112,11 +110,9 @@
             debug=False)),
     test_cfg=dict(
         rpn=dict(
-            nms_across_levels=False,
             nms_pre=1000,
-            nms_post=1000,
-            max_num=1000,
-            nms_thr=0.7,
+            max_per_img=1000,
+            nms=dict(type='nms', iou_threshold=0.7),
             min_bbox_size=0),
         rcnn=dict(
             score_thr=0.03,

configs/guided_anchoring/ga_faster_r50_caffe_fpn_1x_coco.py

@@ -55,10 +55,11 @@
             allowed_border=-1,
             center_ratio=0.2,
             ignore_ratio=0.5),
-        rpn_proposal=dict(max_num=300),
+        rpn_proposal=dict(nms_post=1000, max_per_img=300),
         rcnn=dict(
             assigner=dict(pos_iou_thr=0.6, neg_iou_thr=0.6, min_pos_iou=0.6),
             sampler=dict(type='RandomSampler', num=256))),
-    test_cfg=dict(rpn=dict(max_num=300), rcnn=dict(score_thr=1e-3)))
+    test_cfg=dict(
+        rpn=dict(nms_post=1000, max_per_img=300), rcnn=dict(score_thr=1e-3)))
 optimizer_config = dict(
     _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))

configs/guided_anchoring/ga_faster_r50_fpn_1x_coco.py

@@ -55,10 +55,11 @@
             allowed_border=-1,
             center_ratio=0.2,
             ignore_ratio=0.5),
-        rpn_proposal=dict(max_num=300),
+        rpn_proposal=dict(nms_post=1000, max_per_img=300),
         rcnn=dict(
             assigner=dict(pos_iou_thr=0.6, neg_iou_thr=0.6, min_pos_iou=0.6),
             sampler=dict(type='RandomSampler', num=256))),
-    test_cfg=dict(rpn=dict(max_num=300), rcnn=dict(score_thr=1e-3)))
+    test_cfg=dict(
+        rpn=dict(nms_post=1000, max_per_img=300), rcnn=dict(score_thr=1e-3)))
 optimizer_config = dict(
     _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))

configs/guided_anchoring/ga_rpn_r50_caffe_fpn_1x_coco.py

@@ -52,6 +52,7 @@
                 add_gt_as_proposals=False),
             allowed_border=-1,
             center_ratio=0.2,
-            ignore_ratio=0.5)))
+            ignore_ratio=0.5)),
+    test_cfg=dict(rpn=dict(nms_post=1000)))
 optimizer_config = dict(
     _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))

configs/guided_anchoring/ga_rpn_r50_fpn_1x_coco.py

@@ -52,6 +52,7 @@
                 add_gt_as_proposals=False),
             allowed_border=-1,
             center_ratio=0.2,
-            ignore_ratio=0.5)))
+            ignore_ratio=0.5)),
+    test_cfg=dict(rpn=dict(nms_post=1000)))
 optimizer_config = dict(
     _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))