clean op

.github/workflows/build.yml

@@ -50,7 +50,7 @@ jobs:
         run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}}
       - name: Install mmdet dependencies
         run: |
-          pip install mmcv
+          pip install mmcv==1.0rc0+torch${{matrix.torch}}+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
           pip install -r requirements.txt
           pip install "git+https://github.com/open-mmlab/cocoapi.git#subdirectory=pycocotools"
       - name: Lint with flake8
@@ -60,7 +60,7 @@ jobs:
       - name: Format with yapf
         run: yapf -r -d mmdet/ tools/ configs/ tests/
       - name: Check docstring
-        run: interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --exclude mmdet/ops --ignore-regex "__repr__" --fail-under 80 mmdet
+        run: interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-regex "__repr__" --fail-under 80 mmdet
       - name: Build and install
         env:
           CUDA_ARCH: ${{matrix.cuda_arch}}

.isort.cfg

@@ -3,6 +3,6 @@ line_length = 79
 multi_line_output = 0
 known_standard_library = setuptools
 known_first_party = mmdet
-known_third_party = PIL,asynctest,cityscapesscripts,cv2,matplotlib,numpy,onnx,pycocotools,pytest,robustness_eval,roi_align,roi_pool,seaborn,six,terminaltables,torch,torchvision
+known_third_party = PIL,asynctest,cityscapesscripts,cv2,matplotlib,mmcv,numpy,onnx,pycocotools,pytest,robustness_eval,seaborn,six,terminaltables,torch,torchvision
 no_lines_before = STDLIB,LOCALFOLDER
 default_section = THIRDPARTY

configs/_base_/models/cascade_mask_rcnn_r50_fpn.py

@@ -38,7 +38,7 @@
         stage_loss_weights=[1, 0.5, 0.25],
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=7, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         bbox_head=[
@@ -95,7 +95,7 @@
         ],
         mask_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=14, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         mask_head=dict(
@@ -195,6 +195,6 @@
         min_bbox_size=0),
     rcnn=dict(
         score_thr=0.05,
-        nms=dict(type='nms', iou_thr=0.5),
+        nms=dict(type='nms', iou_threshold=0.5),
         max_per_img=100,
         mask_thr_binary=0.5))

configs/_base_/models/cascade_rcnn_r50_fpn.py

@@ -38,7 +38,7 @@
         stage_loss_weights=[1, 0.5, 0.25],
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=7, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         bbox_head=[
@@ -178,4 +178,6 @@
         nms_thr=0.7,
         min_bbox_size=0),
     rcnn=dict(
-        score_thr=0.05, nms=dict(type='nms', iou_thr=0.5), max_per_img=100))
+        score_thr=0.05,
+        nms=dict(type='nms', iou_threshold=0.5),
+        max_per_img=100))

configs/_base_/models/fast_rcnn_r50_fpn.py

@@ -20,7 +20,7 @@
         type='StandardRoIHead',
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=7, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         bbox_head=dict(
@@ -57,4 +57,6 @@
         debug=False))
 test_cfg = dict(
     rcnn=dict(
-        score_thr=0.05, nms=dict(type='nms', iou_thr=0.5), max_per_img=100))
+        score_thr=0.05,
+        nms=dict(type='nms', iou_threshold=0.5),
+        max_per_img=100))

configs/_base_/models/faster_rcnn_r50_caffe_c4.py

@@ -43,7 +43,7 @@
             norm_eval=True),
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=14, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
             out_channels=1024,
             featmap_strides=[16]),
         bbox_head=dict(
@@ -111,4 +111,6 @@
         nms_thr=0.7,
         min_bbox_size=0),
     rcnn=dict(
-        score_thr=0.05, nms=dict(type='nms', iou_thr=0.5), max_per_img=100))
+        score_thr=0.05,
+        nms=dict(type='nms', iou_threshold=0.5),
+        max_per_img=100))

configs/_base_/models/faster_rcnn_r50_fpn.py

@@ -35,7 +35,7 @@
         type='StandardRoIHead',
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=7, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         bbox_head=dict(
@@ -103,7 +103,9 @@
         nms_thr=0.7,
         min_bbox_size=0),
     rcnn=dict(
-        score_thr=0.05, nms=dict(type='nms', iou_thr=0.5), max_per_img=100)
+        score_thr=0.05,
+        nms=dict(type='nms', iou_threshold=0.5),
+        max_per_img=100)
     # soft-nms is also supported for rcnn testing
-    # e.g., nms=dict(type='soft_nms', iou_thr=0.5, min_score=0.05)
+    # e.g., nms=dict(type='soft_nms', iou_threshold=0.5, min_score=0.05)
 )

configs/_base_/models/mask_rcnn_r50_caffe_c4.py

@@ -43,7 +43,7 @@
             norm_eval=True),
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=14, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
             out_channels=1024,
             featmap_strides=[16]),
         bbox_head=dict(
@@ -122,6 +122,6 @@
         min_bbox_size=0),
     rcnn=dict(
         score_thr=0.05,
-        nms=dict(type='nms', iou_thr=0.5),
+        nms=dict(type='nms', iou_threshold=0.5),
         max_per_img=100,
         mask_thr_binary=0.5))

configs/_base_/models/mask_rcnn_r50_fpn.py

@@ -36,7 +36,7 @@
         type='StandardRoIHead',
         bbox_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=7, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=7, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         bbox_head=dict(
@@ -55,7 +55,7 @@
             loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
         mask_roi_extractor=dict(
             type='SingleRoIExtractor',
-            roi_layer=dict(type='RoIAlign', out_size=14, sample_num=0),
+            roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32]),
         mask_head=dict(
@@ -119,6 +119,6 @@
         min_bbox_size=0),
     rcnn=dict(
         score_thr=0.05,
-        nms=dict(type='nms', iou_thr=0.5),
+        nms=dict(type='nms', iou_threshold=0.5),
         max_per_img=100,
         mask_thr_binary=0.5))

configs/_base_/models/retinanet_r50_fpn.py

@@ -56,5 +56,5 @@
     nms_pre=1000,
     min_bbox_size=0,
     score_thr=0.05,
-    nms=dict(type='nms', iou_thr=0.5),
+    nms=dict(type='nms', iou_threshold=0.5),
     max_per_img=100)

configs/_base_/models/ssd300.py

@@ -43,7 +43,7 @@
     neg_pos_ratio=3,
     debug=False)
 test_cfg = dict(
-    nms=dict(type='nms', iou_thr=0.45),
+    nms=dict(type='nms', iou_threshold=0.45),
     min_bbox_size=0,
     score_thr=0.02,
     max_per_img=200)

configs/atss/atss_r50_fpn_1x_coco.py

@@ -56,7 +56,7 @@
     nms_pre=1000,
     min_bbox_size=0,
     score_thr=0.05,
-    nms=dict(type='nms', iou_thr=0.6),
+    nms=dict(type='nms', iou_threshold=0.6),
     max_per_img=100)
 # optimizer
 optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)

configs/dcn/cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/faster_rcnn_r50_fpn_dpool_1x_coco.py

@@ -5,11 +5,8 @@
             type='SingleRoIExtractor',
             roi_layer=dict(
                 _delete_=True,
-                type='DeformRoIPoolingPack',
-                out_size=7,
-                out_channels=256,
-                no_trans=False,
-                group_size=1,
-                trans_std=0.1),
+                type='DeformRoIPoolPack',
+                output_size=7,
+                output_channels=256),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32])))

configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCNv2', deformable_groups=4, fallback_on_stride=False),
+        dcn=dict(type='DCNv2', deform_groups=4, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco.py

@@ -5,11 +5,8 @@
             type='SingleRoIExtractor',
             roi_layer=dict(
                 _delete_=True,
-                type='ModulatedDeformRoIPoolingPack',
-                out_size=7,
-                out_channels=256,
-                no_trans=False,
-                group_size=1,
-                trans_std=0.1),
+                type='ModulatedDeformRoIPoolPack',
+                output_size=7,
+                output_channels=256),
             out_channels=256,
             featmap_strides=[4, 8, 16, 32])))

configs/dcn/faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py

@@ -11,5 +11,5 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         style='pytorch',
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py

@@ -1,5 +1,5 @@
 _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
 model = dict(
     backbone=dict(
-        dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py

@@ -12,5 +12,5 @@
                 stages=(False, False, True, True),
                 position='after_conv2')
         ],
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py

@@ -12,5 +12,5 @@
                 stages=(False, False, True, True),
                 position='after_conv2')
         ],
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)))

configs/faster_rcnn/faster_rcnn_r50_fpn_soft_nms_1x_coco.py

@@ -7,5 +7,5 @@
 test_cfg = dict(
     rcnn=dict(
         score_thr=0.05,
-        nms=dict(type='soft_nms', iou_thr=0.5),
+        nms=dict(type='soft_nms', iou_threshold=0.5),
         max_per_img=100))

configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_4x4_1x_coco.py

@@ -10,7 +10,7 @@
         conv_bias=True,
         loss_bbox=dict(type='GIoULoss', loss_weight=1.0)))
 # training and testing settings
-test_cfg = dict(nms=dict(type='nms', iou_thr=0.6))
+test_cfg = dict(nms=dict(type='nms', iou_threshold=0.6))
 
 # dataset settings
 img_norm_cfg = dict(

configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_coco.py

@@ -3,7 +3,7 @@
 model = dict(
     pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
-        dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True)),
     bbox_head=dict(
         norm_on_bbox=True,
@@ -13,7 +13,7 @@
         conv_bias=True,
         loss_bbox=dict(type='GIoULoss', loss_weight=1.0)))
 # training and testing settings
-test_cfg = dict(nms=dict(type='nms', iou_thr=0.6))
+test_cfg = dict(nms=dict(type='nms', iou_threshold=0.6))
 
 # dataset settings
 img_norm_cfg = dict(

configs/fcos/fcos_r50_caffe_fpn_4x4_1x_coco.py

@@ -56,7 +56,7 @@
     nms_pre=1000,
     min_bbox_size=0,
     score_thr=0.05,
-    nms=dict(type='nms', iou_thr=0.5),
+    nms=dict(type='nms', iou_threshold=0.5),
     max_per_img=100)
 img_norm_cfg = dict(
     mean=[102.9801, 115.9465, 122.7717], std=[1.0, 1.0, 1.0], to_rgb=False)

configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py

@@ -55,7 +55,7 @@
     nms_pre=1000,
     min_bbox_size=0,
     score_thr=0.05,
-    nms=dict(type='nms', iou_thr=0.5),
+    nms=dict(type='nms', iou_threshold=0.5),
     max_per_img=100)
 img_norm_cfg = dict(
     mean=[102.9801, 115.9465, 122.7717], std=[1.0, 1.0, 1.0], to_rgb=False)

configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py

@@ -45,7 +45,7 @@
 test_cfg = dict(
     nms_pre=1000,
     score_thr=0.05,
-    nms=dict(type='nms', iou_thr=0.5),
+    nms=dict(type='nms', iou_threshold=0.5),
     max_per_img=100)
 data = dict(samples_per_gpu=4, workers_per_gpu=4)
 # optimizer

configs/gfl/gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco.py

@@ -8,7 +8,7 @@
         out_indices=(0, 1, 2, 3),
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
-        dcn=dict(type='DCN', deformable_groups=1, fallback_on_stride=False),
+        dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
         stage_with_dcn=(False, True, True, True),
         norm_eval=True,
         style='pytorch'))