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Unverified Commit f885d28a authored by VVsssssk's avatar VVsssssk Committed by GitHub
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[Refactor] Update configs name (#1757) 

* fix cfg name

* update cfg name

* fix cfg

* fix comments

* fix comment

* fix comments
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configs/h3dnet/metafile.yml
View file @ f885d28a
......@@ -17,7 +17,7 @@ Collections:
Models:
- Name: h3dnet_3x8_scannet-3d-18class
In Collection: H3DNet
Config: configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py
Config: configs/h3dnet/h3dnet_8xb3_scannet-seg.py
Metadata:
Training Memory (GB): 7.9
Results:
......
configs/imvotenet/README.md
View file @ f885d28a
......@@ -20,15 +20,15 @@ We implement ImVoteNet and provide the result and checkpoints on SUNRGBD.
### SUNRGBD-2D (Stage 1, image branch pre-train)
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | AP@0.25 | AP@0.5 | Download |
| :---------------------------------------------------------------------: | :-----: | :------: | :------------: | :-----: | :----: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [PointNet++](./imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py) | | 2.1 | | | 62.70 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class_20210819_225618-62eba6ce.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class_20210819_225618.json) |
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | AP@0.25 | AP@0.5 | Download |
| :--------------------------------------------------------------: | :-----: | :------: | :------------: | :-----: | :----: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [PointNet++](./imvotenet_faster-rcnn-r50_fpn_4xb2_sunrgbd-3d.py) | | 2.1 | | | 62.70 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class_20210819_225618-62eba6ce.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class_20210819_225618.json) |
### SUNRGBD-3D (Stage 2)
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | AP@0.25 | AP@0.5 | Download |
| :---------------------------------------------------------: | :-----: | :------: | :------------: | :-----: | :----: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [PointNet++](./imvotenet_stage2_16x8_sunrgbd-3d-10class.py) | 3x | 9.4 | | 64.55 | | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class/imvotenet_stage2_16x8_sunrgbd-3d-10class_20210819_192851-1bcd1b97.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class/imvotenet_stage2_16x8_sunrgbd-3d-10class_20210819_192851.log.json) |
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | AP@0.25 | AP@0.5 | Download |
| :--------------------------------------------------: | :-----: | :------: | :------------: | :-----: | :----: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [PointNet++](./imvotenet_stage2_8xb16_sunrgbd-3d.py) | 3x | 9.4 | | 64.55 | | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class/imvotenet_stage2_16x8_sunrgbd-3d-10class_20210819_192851-1bcd1b97.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class/imvotenet_stage2_16x8_sunrgbd-3d-10class_20210819_192851.log.json) |
## Citation
......
configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py → configs/imvotenet/imvotenet_faster-rcnn-r50_fpn_4xb2_sunrgbd-3d.py
View file @ f885d28a
_base_ = [
'../_base_/datasets/sunrgbd-3d-10class.py', '../_base_/default_runtime.py',
'../_base_/models/imvotenet_image.py'
'../_base_/datasets/sunrgbd-3d.py', '../_base_/default_runtime.py',
'../_base_/models/imvotenet.py'
]
train_pipeline = [
......
configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py → configs/imvotenet/imvotenet_stage2_8xb16_sunrgbd-3d.py
View file @ f885d28a
_base_ = [
'../_base_/datasets/sunrgbd-3d-10class.py',
'../_base_/schedules/schedule_3x.py', '../_base_/default_runtime.py',
'../_base_/models/imvotenet_image.py'
'../_base_/datasets/sunrgbd-3d.py', '../_base_/schedules/schedule-3x.py',
'../_base_/default_runtime.py', '../_base_/models/imvotenet.py'
]
class_names = ('bed', 'table', 'sofa', 'chair', 'toilet', 'desk', 'dresser',
......
configs/imvotenet/metafile.yml
View file @ f885d28a
......@@ -20,7 +20,7 @@ Collections:
Models:
- Name: imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class
In Collection: ImVoteNet
Config: configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py
Config: configs/imvotenet/imvotenet_faster-rcnn-r50_fpn_4xb2_sunrgbd-3d.py
Metadata:
Training Memory (GB): 2.1
Results:
......@@ -32,7 +32,7 @@ Models:
- Name: imvotenet_stage2_16x8_sunrgbd-3d-10class
In Collection: ImVoteNet
Config: configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py
Config: configs/imvotenet/imvotenet_stage2_8xb16_sunrgbd-3d.py
Metadata:
Training Memory (GB): 9.4
Results:
......
configs/imvoxelnet/README.md
View file @ f885d28a
......@@ -22,9 +22,9 @@ Results for SUN RGB-D, ScanNet and nuScenes are currently available in ImVoxelNe
### KITTI
| Backbone | Class | Lr schd | Mem (GB) | Inf time (fps) | mAP | Download |
| :---------------------------------------: | :---: | :-----: | :------: | :------------: | :---: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [ResNet-50](./imvoxelnet_kitti-3d-car.py) | Car | 3x | | | 17.26 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvoxelnet/imvoxelnet_4x8_kitti-3d-car/imvoxelnet_4x8_kitti-3d-car_20210830_003014-3d0ffdf4.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvoxelnet/imvoxelnet_4x8_kitti-3d-car/imvoxelnet_4x8_kitti-3d-car_20210830_003014.log.json) |
| Backbone | Class | Lr schd | Mem (GB) | Inf time (fps) | mAP | Download |
| :--------------------------------------------: | :---: | :-----: | :------: | :------------: | :---: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [ResNet-50](./imvoxelnet_8xb4_kitti-3d-car.py) | Car | 3x | | | 17.26 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvoxelnet/imvoxelnet_4x8_kitti-3d-car/imvoxelnet_4x8_kitti-3d-car_20210830_003014-3d0ffdf4.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvoxelnet/imvoxelnet_4x8_kitti-3d-car/imvoxelnet_4x8_kitti-3d-car_20210830_003014.log.json) |
## Citation
......
configs/imvoxelnet/metafile.yml
View file @ f885d28a
......@@ -18,7 +18,7 @@ Collections:
Models:
- Name: imvoxelnet_kitti-3d-car
In Collection: ImVoxelNet
Config: configs/imvoxelnet/imvoxelnet_kitti-3d-car.py
Config: configs/imvoxelnet/imvoxelnet_8xb4_kitti-3d-car.py
Metadata:
Training Memory (GB): 15.0
Results:
......
configs/mvxnet/README.md
View file @ f885d28a
......@@ -20,9 +20,9 @@ We implement MVX-Net and provide its results and models on KITTI dataset.
### KITTI
| Backbone | Class | Lr schd | Mem (GB) | Inf time (fps) | mAP | Download |
| :-------------------------------------------------------------------: | :-----: | :--------: | :------: | :------------: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [SECFPN](./dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py) | 3 Class | cosine 80e | 6.7 | | 63.22 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class_20210831_060805-83442923.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class_20210831_060805.log.json) |
| Backbone | Class | Lr schd | Mem (GB) | Inf time (fps) | mAP | Download |
| :-----------------------------------------------------------------: | :-----: | :--------: | :------: | :------------: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [SECFPN](./mvxnet_fpn_dv_second_secfpn_8xb2-80e_kitti-3d-3class.py) | 3 Class | cosine 80e | 6.7 | | 63.22 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class_20210831_060805-83442923.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class_20210831_060805.log.json) |
## Citation
......
configs/mvxnet/metafile.yml
View file @ f885d28a
......@@ -19,7 +19,7 @@ Collections:
Models:
- Name: dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class
In Collection: MVX-Net
Config: configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py
Config: configs/mvxnet/mvxnet_fpn_dv_second_secfpn_8xb2-80e_kitti-3d-3class.py
Metadata:
Training Memory (GB): 6.7
Results:
......
configs/nuimages/README.md
View file @ f885d28a
......@@ -38,8 +38,8 @@ We report Mask R-CNN and Cascade Mask R-CNN results on nuimages.
| Mask R-CNN | [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_1x_nuim.py) | IN | 1x | 7.0 | 47.7 | 38.2 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/) |
| Mask R-CNN | [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py) | IN+COCO-3x | 1x | 7.0 | 49.9 | 40.8 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim_20201008_195305-661a992e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim_20201008_195305.log.json) |
| Mask R-CNN | [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py) | IN+COCO-3x | 20e | 7.0 | 50.6 | 41.3 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002-5529442c.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002.log.json) |
| Mask R-CNN | [R-101](./mask_rcnn_r101_fpn_1x_nuim.py) | IN | 1x | 10.9 | 48.9 | 39.1 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803-65c7623a.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803.log.json) |
| Mask R-CNN | [X-101_32x4d](./mask_rcnn_x101_32x4d_fpn_1x_nuim.py) | IN | 1x | 13.3 | 50.4 | 40.5 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741-b699ab37.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741.log.json) |
| Mask R-CNN | [R-101](./mask-rcnn_r101_fpn_1x_nuim.py) | IN | 1x | 10.9 | 48.9 | 39.1 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803-65c7623a.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803.log.json) |
| Mask R-CNN | [X-101_32x4d](./mask-rcnn_x101_32x4d_fpn_1x_nuim.py) | IN | 1x | 13.3 | 50.4 | 40.5 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741-b699ab37.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741.log.json) |
| Cascade Mask R-CNN | [R-50](./cascade_mask_rcnn_r50_fpn_1x_nuim.py) | IN | 1x | 8.9 | 50.8 | 40.4 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_1x_nuim/cascade_mask_rcnn_r50_fpn_1x_nuim_20201008_195342-1147c036.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_1x_nuim/cascade_mask_rcnn_r50_fpn_1x_nuim_20201008_195342.log.json) |
| Cascade Mask R-CNN | [R-50](./cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim.py) | IN+COCO-20e | 1x | 8.9 | 52.8 | 42.2 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim_20201009_124158-ad0540e3.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim_20201009_124158.log.json) |
| Cascade Mask R-CNN | [R-50](./cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim.py) | IN+COCO-20e | 20e | 8.9 | 52.8 | 42.2 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim_20201009_124951-40963960.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim_20201009_124951.log.json) |
......
configs/nuimages/htc_r50_fpn_coco-20e_20e_nuim.py → configs/nuimages/htc_r50_fpn_coco-20e_nuim.py
View file @ f885d28a
_base_ = './htc_r50_fpn_coco-20e_1x_nuim.py'
_base_ = './htc_r50_fpn_coco-20e-1x_nuim.py'
# learning policy
lr_config = dict(step=[16, 19])
runner = dict(max_epochs=20)
configs/nuimages/htc_without_semantic_r50_fpn_1x_nuim.py → configs/nuimages/htc_r50_fpn_head-without-semantic_1x_nuim.py
View file @ f885d28a
_base_ = [
'../_base_/datasets/nuim_instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py'
'../_base_/datasets/nuim-instance.py',
'../_base_/schedules/mmdet-schedule-1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
......
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