[Refactor] Update configs name (#1757)

* fix cfg name

* update cfg name

* fix cfg

* fix comments

* fix comment

* fix comments

configs/centerpoint/centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 # If point cloud range is changed, the models should also change their point
 # cloud range accordingly

configs/centerpoint/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 model = dict(test_cfg=dict(pts=dict(nms_type='circle')))

configs/centerpoint/centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn-circlenms_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 model = dict(
     pts_bbox_head=dict(

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_flip-tta_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn-circlenms_8xb4-flip-tta-cyclic-20e_nus-3d.py

-_base_ = './centerpoint_0075voxel_second_secfpn_dcn_' \
-         'circlenms_4x8_cyclic_20e_nus.py'
+_base_ = './centerpoint_voxel0075_second_secfpn_' \
+         'head-dcn-circlenms_8xb4_cyclic-20e_nus-3d.py'
 
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
 file_client_args = dict(backend='disk')

configs/centerpoint/centerpoint_01voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 model = dict(
     pts_bbox_head=dict(

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_flip-tta_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-flip-tta-cyclic-20e_nus-3d.py

-_base_ = './centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py'
+_base_ = './centerpoint_voxel0075_second_secfpn' \
+         '_head-dcn_8xb4-cyclic-20e_nus-3d.py'
 
 point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
 file_client_args = dict(backend='disk')

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_tta_20e_nus.py → configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-tta-cyclic-20e_nus-3d.py

-_base_ = './centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py'
+_base_ = './centerpoint_voxel0075_second_secfpn' \
+         '_head-dcn_8xb4-cyclic-20e_nus-3d.py'
 
 model = dict(test_cfg=dict(pts=dict(use_rotate_nms=True, max_num=500)))
 

configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py

 _base_ = [
     '../_base_/datasets/nus-3d.py',
-    '../_base_/models/centerpoint_01voxel_second_secfpn_nus.py',
-    '../_base_/schedules/cyclic_20e.py', '../_base_/default_runtime.py'
+    '../_base_/models/centerpoint_voxel01_second_secfpn_nus.py',
+    '../_base_/schedules/cyclic-20e.py', '../_base_/default_runtime.py'
 ]
 
 # If point cloud range is changed, the models should also change their point

configs/centerpoint/centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel01_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 model = dict(test_cfg=dict(pts=dict(nms_type='circle')))

configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel01_second_secfpn_head-dcn-circlenms_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 model = dict(
     pts_bbox_head=dict(

configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py → configs/centerpoint/centerpoint_voxel01_second_secfpn_head-dcn_8xb4-cyclic-20e_nus-3d.py

-_base_ = ['./centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py']
+_base_ = ['./centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py']
 
 model = dict(
     pts_bbox_head=dict(

configs/centerpoint/metafile.yml

@@ -18,7 +18,7 @@ Collections:
 Models:
   - Name: centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus
     In Collection: CenterPoint
-    Config: configs/centerpoint/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
+    Config: configs/centerpoint/centerpoint_voxel01_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
     Metadata:
       Training Memory (GB): 4.9
     Results:
@@ -31,7 +31,7 @@ Models:
 
   - Name: centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus
     In Collection: CenterPoint
-    Config: configs/centerpoint/centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
+    Config: configs/centerpoint/centerpoint_voxel01_second_secfpn_head-dcn-circlenms_8xb4-cyclic-20e_nus-3d.py
     Metadata:
       Training Memory (GB): 5.2
     Results:
@@ -44,7 +44,7 @@ Models:
 
   - Name: centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus
     In Collection: CenterPoint
-    Config: configs/centerpoint/centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
+    Config: configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
     Metadata:
       Training Memory (GB): 7.8
     Results:
@@ -57,7 +57,7 @@ Models:
 
   - Name: centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus
     In Collection: CenterPoint
-    Config: configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
+    Config: configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn-circlenms_8xb4-cyclic-20e_nus-3d.py
     Metadata:
       Training Memory (GB): 8.5
     Results:
@@ -70,7 +70,7 @@ Models:
 
   - Name: centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus
     In Collection: CenterPoint
-    Config: configs/centerpoint/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
+    Config: configs/centerpoint/centerpoint_pillar02_second_secfpn_head-circlenms_8xb4-cyclic-20e_nus-3d.py
     Metadata:
       Training Memory (GB): 4.4
     Results:
@@ -83,7 +83,7 @@ Models:
 
   - Name: centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus
     In Collection: CenterPoint
-    Config: configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus.py
+    Config: configs/centerpoint/centerpoint_pillar02_second_secfpn_head-dcn_8xb4-cyclic-20e_nus-3d.py
     Metadata:
       Training Memory (GB): 4.6
     Results:

configs/dgcnn/README.md

@@ -22,15 +22,15 @@ We implement DGCNN and provide the results and checkpoints on S3DIS dataset.
 
 ### S3DIS
 
-|                          Method                           | Split  |   Lr schd   | Mem (GB) | Inf time (fps) | mIoU (Val set) |                                                                                                                                                                                                 Download                                                                                                                                                                                                 |
-| :-------------------------------------------------------: | :----: | :---------: | :------: | :------------: | :------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | Area_1 | cosine 100e |   13.1   |                |     68.33      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area1/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_000734-39658f14.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area1/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_000734.log.json) |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | Area_2 | cosine 100e |   13.1   |                |     40.68      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area2/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_144648-aea9ecb6.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area2/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_144648.log.json) |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | Area_3 | cosine 100e |   13.1   |                |     69.38      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area3/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210801_154629-2ff50ee0.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area3/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210801_154629.log.json) |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | Area_4 | cosine 100e |   13.1   |                |     50.07      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area4/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_073551-dffab9cd.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area4/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_073551.log.json) |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | Area_5 | cosine 100e |   13.1   |                |     50.59      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area5/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210730_235824-f277e0c5.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area5/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210730_235824.log.json) |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | Area_6 | cosine 100e |   13.1   |                |     77.94      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area6/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_154317-e3511b32.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area6/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_154317.log.json) |
-| [DGCNN](./dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py) | 6-fold |             |          |                |     59.43      |                                                                                                                                                                                                                                                                                                                                                                                                          |
+|                     Method                      | Split  |   Lr schd   | Mem (GB) | Inf time (fps) | mIoU (Val set) |                                                                                                                                                                                                 Download                                                                                                                                                                                                 |
+| :---------------------------------------------: | :----: | :---------: | :------: | :------------: | :------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | Area_1 | cosine 100e |   13.1   |                |     68.33      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area1/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_000734-39658f14.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area1/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_000734.log.json) |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | Area_2 | cosine 100e |   13.1   |                |     40.68      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area2/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_144648-aea9ecb6.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area2/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210731_144648.log.json) |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | Area_3 | cosine 100e |   13.1   |                |     69.38      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area3/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210801_154629-2ff50ee0.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area3/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210801_154629.log.json) |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | Area_4 | cosine 100e |   13.1   |                |     50.07      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area4/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_073551-dffab9cd.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area4/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_073551.log.json) |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | Area_5 | cosine 100e |   13.1   |                |     50.59      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area5/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210730_235824-f277e0c5.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area5/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210730_235824.log.json) |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | Area_6 | cosine 100e |   13.1   |                |     77.94      | [model](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area6/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_154317-e3511b32.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.17.0_models/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class/area6/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class_20210802_154317.log.json) |
+| [DGCNN](./dgcnn_4xb32-cosine-100e_s3dis-seg.py) | 6-fold |             |          |                |     59.43      |                                                                                                                                                                                                                                                                                                                                                                                                          |
 
 **Notes:**
 

configs/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py → configs/dgcnn/dgcnn_4xb32-cosine-100e_s3dis-seg.py

 _base_ = [
-    '../_base_/datasets/s3dis_seg-3d-13class.py', '../_base_/models/dgcnn.py',
-    '../_base_/schedules/seg_cosine_100e.py', '../_base_/default_runtime.py'
+    '../_base_/datasets/s3dis-seg.py', '../_base_/models/dgcnn.py',
+    '../_base_/schedules/seg-cosine-100e.py', '../_base_/default_runtime.py'
 ]
 
 # model settings

configs/dgcnn/metafile.yml

@@ -10,9 +10,9 @@ Collections:
     README: configs/dgcnn/README.md
 
 Models:
-  - Name: dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py
+  - Name: dgcnn_4xb32-cosine-100e_s3dis-seg.py
     In Collection: DGCNN
-    Config: configs/dgcnn/dgcnn_32x4_cosine_100e_s3dis_seg-3d-13class.py
+    Config: configs/dgcnn/dgcnn_4xb32-cosine-100e_s3dis-seg.py
     Metadata:
       Training Data: S3DIS
       Training Memory (GB): 13.3

configs/dynamic_voxelization/README.md

@@ -20,11 +20,11 @@ We implement Dynamic Voxelization proposed in  and provide its results and model
 
 ### KITTI
 
-|                               Model                               |  Class  |  Lr schd   | Mem (GB) | Inf time (fps) |  mAP  |                                                                                                                                                                                                                 Download                                                                                                                                                                                                                 |
-| :---------------------------------------------------------------: | :-----: | :--------: | :------: | :------------: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
-|       [SECOND](./dv_second_secfpn_6x8_80e_kitti-3d-car.py)        |   Car   | cyclic 80e |   5.5    |                | 78.83 |                     [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car/dv_second_secfpn_6x8_80e_kitti-3d-car_20200620_235228-ac2c1c0c.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car/dv_second_secfpn_6x8_80e_kitti-3d-car_20200620_235228.log.json)                     |
-|  [SECOND](./dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py)   | 3 Class | cosine 80e |   5.5    |                | 65.27 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class_20210831_054106-e742d163.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class_20210831_054106.log.json) |
-| [PointPillars](./dv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py) |   Car   | cyclic 80e |   4.7    |                | 77.76 |       [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car_20200620_230844-ee7b75c9.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car_20200620_230844.log.json)       |
+|                               Model                                |  Class  |  Lr schd   | Mem (GB) | Inf time (fps) |  mAP  |                                                                                                                                                                                                                 Download                                                                                                                                                                                                                 |
+| :----------------------------------------------------------------: | :-----: | :--------: | :------: | :------------: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+|       [SECOND](./second_dv_secfpn_8xb6-80e_kitti-3d-car.py)        |   Car   | cyclic 80e |   5.5    |                | 78.83 |                     [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car/dv_second_secfpn_6x8_80e_kitti-3d-car_20200620_235228-ac2c1c0c.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car/dv_second_secfpn_6x8_80e_kitti-3d-car_20200620_235228.log.json)                     |
+|  [SECOND](./second_dv_secfpn_8xb2-cosine-80e_kitti-3d-3class.py)   | 3 Class | cosine 80e |   5.5    |                | 65.27 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class_20210831_054106-e742d163.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class_20210831_054106.log.json) |
+| [PointPillars](./pointpillars_dv_secfpn_8xb6-160e_kitti-3d-car.py) |   Car   | cyclic 80e |   4.7    |                | 77.76 |       [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car_20200620_230844-ee7b75c9.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car_20200620_230844.log.json)       |
 
 ## Citation
 

configs/dynamic_voxelization/metafile.yml

@@ -18,7 +18,7 @@ Collections:
 Models:
   - Name: dv_second_secfpn_6x8_80e_kitti-3d-car
     In Collection: Dynamic Voxelization
-    Config: configs/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car.py
+    Config: configs/dynamic_voxelization/second_dv_secfpn_8xb6-80e_kitti-3d-car.py
     Metadata:
       Training Memory (GB): 5.5
     Results:
@@ -30,7 +30,7 @@ Models:
 
   - Name: dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class
     In Collection: Dynamic Voxelization
-    Config: configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py
+    Config: configs/dynamic_voxelization/second_dv_secfpn_8xb2-cosine-80e_kitti-3d-3class.py
     Metadata:
       Training Memory (GB): 5.5
     Results:
@@ -42,7 +42,7 @@ Models:
 
   - Name: dv_pointpillars_secfpn_6x8_160e_kitti-3d-car
     In Collection: Dynamic Voxelization
-    Config: configs/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py
+    Config: configs/dynamic_voxelization/pointpillars_dv_secfpn_8xb6-160e_kitti-3d-car.py
     Metadata:
       Training Memory (GB): 4.7
     Results:

configs/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py → configs/dynamic_voxelization/pointpillars_dv_secfpn_8xb6-160e_kitti-3d-car.py

-_base_ = '../pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py'
+_base_ = '../pointpillars/pointpillars_hv_secfpn_8xb6-160e_kitti-3d-car.py'
 
 voxel_size = [0.16, 0.16, 4]
 point_cloud_range = [0, -39.68, -3, 69.12, 39.68, 1]

configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py → configs/dynamic_voxelization/second_dv_secfpn_8xb2-cosine-80e_kitti-3d-3class.py

 _base_ = [
-    '../_base_/models/hv_second_secfpn_kitti.py',
+    '../_base_/models/second_hv_secfpn_kitti.py',
     '../_base_/datasets/kitti-3d-3class.py', '../_base_/schedules/cosine.py',
     '../_base_/default_runtime.py'
 ]