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Unverified Commit 06b56888 authored by Jingwei Zhang's avatar Jingwei Zhang Committed by GitHub
Browse files

[Fix] Update links of configs and restrict the version of MMCV (#2337)

* update config link in readme

* update version restriction

* update

* fix some configs error in metafile

* add pvrcnn and fcaf3d in model-index.yml
parent e943e84d
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...@@ -52,7 +52,7 @@ We also provide visualization functions to show the monocular 3D detection resul ...@@ -52,7 +52,7 @@ We also provide visualization functions to show the monocular 3D detection resul
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download | | Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download |
| :-------------------------------------------------------------------------------------: | :-----: | :------: | :------------: | :--: | :--: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | :-------------------------------------------------------------------------------------: | :-----: | :------: | :------------: | :--: | :--: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| \[ResNet101 w/ DCN\](./fcos3d_r101-caffe-dcn_fpn_head-gn_8xb2-1x_nus-mono3d.py) | 1x | 8.69 | | 29.8 | 37.7 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_20210715_235813-4bed5239.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_20210715_235813.log.json) | | [ResNet101 w/ DCN](./fcos3d_r101-caffe-dcn_fpn_head-gn_8xb2-1x_nus-mono3d.py) | 1x | 8.69 | | 29.8 | 37.7 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_20210715_235813-4bed5239.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_20210715_235813.log.json) |
| [above w/ finetune](./fcos3d_r101-caffe-dcn_fpn_head-gn_8xb2-1x_nus-mono3d_finetune.py) | 1x | 8.69 | | 32.1 | 39.5 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune_20210717_095645-8d806dc2.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune_20210717_095645.log.json) | | [above w/ finetune](./fcos3d_r101-caffe-dcn_fpn_head-gn_8xb2-1x_nus-mono3d_finetune.py) | 1x | 8.69 | | 32.1 | 39.5 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune_20210717_095645-8d806dc2.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune_20210717_095645.log.json) |
| above w/ tta | 1x | 8.69 | | 33.1 | 40.3 | | | above w/ tta | 1x | 8.69 | | 33.1 | 40.3 | |
......
...@@ -30,9 +30,9 @@ We implement PointPillars and provide the results and checkpoints on KITTI, nuSc ...@@ -30,9 +30,9 @@ We implement PointPillars and provide the results and checkpoints on KITTI, nuSc
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download | | Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download |
| :---------------------------------------------------------------------: | :-----: | :------: | :------------: | :---: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | :---------------------------------------------------------------------: | :-----: | :------: | :------------: | :---: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [SECFPN](./pointpillars_hv_secfpn_sbn-all_8xb4-2x_nus-3d.py) | 2x | 16.4 | | 34.33 | 49.1 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d_20210826_225857-f19d00a3.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d_20210826_225857.log.json) | | [SECFPN](./pointpillars_hv_secfpn_sbn-all_8xb4-2x_nus-3d.py) | 2x | 16.4 | | 34.33 | 49.1 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d_20210826_225857-f19d00a3.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d_20210826_225857.log.json) |
| [SECFPN (FP16)](./hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d.py) | 2x | 8.37 | | 35.19 | 50.27 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d_20201020_222626-c3f0483e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d_20201020_222626.log.json) | | [SECFPN (FP16)](./pointpillars_hv_secfpn_sbn-all_8xb2-amp-2x_nus-3d.py) | 2x | 8.37 | | 35.19 | 50.27 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d_20201020_222626-c3f0483e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d_20201020_222626.log.json) |
| [FPN](./pointpillars_hv_fpn_sbn-all_8xb4-2x_nus-3d.py) | 2x | 16.3 | | 39.7 | 53.2 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d_20210826_104936-fca299c1.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d_20210826_104936.log.json) | | [FPN](./pointpillars_hv_fpn_sbn-all_8xb4-2x_nus-3d.py) | 2x | 16.3 | | 39.7 | 53.2 | [model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d_20210826_104936-fca299c1.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d_20210826_104936.log.json) |
| [FPN (FP16)](./hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d.py) | 2x | 8.40 | | 39.26 | 53.26 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d_20201021_120719-269f9dd6.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d_20201021_120719.log.json) | | [FPN (FP16)](./pointpillars_hv_fpn_sbn-all_8xb2-amp-2x_nus-3d.py) | 2x | 8.40 | | 39.26 | 53.26 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d_20201021_120719-269f9dd6.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d_20201021_120719.log.json) |
### Lyft ### Lyft
......
...@@ -147,9 +147,9 @@ Models: ...@@ -147,9 +147,9 @@ Models:
Public Score: 15.0 Public Score: 15.0
Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d_20210822_095429-0b3d6196.pth Weights: https://download.openmmlab.com/mmdetection3d/v1.0.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d_20210822_095429-0b3d6196.pth
- Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car - Name: pointpillars_hv_secfpn_sbn_2x16_2x_waymoD5-3d-car
In Collection: PointPillars In Collection: PointPillars
Config: configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car.py Config: configs/pointpillars/pointpillars_hv_secfpn_sbn_2x16_2x_waymoD5-3d-car.py
Metadata: Metadata:
Training Data: Waymo Training Data: Waymo
Training Memory (GB): 7.76 Training Memory (GB): 7.76
...@@ -164,7 +164,7 @@ Models: ...@@ -164,7 +164,7 @@ Models:
mAPH@L2: 62.1 mAPH@L2: 62.1
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car_20200901_204315-302fc3e7.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car_20200901_204315-302fc3e7.pth
- Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class - Name: pointpillars_hv_secfpn_sbn_2x16_2x_waymoD5-3d-3class
Alias: pointpillars_waymod5-3class Alias: pointpillars_waymod5-3class
In Collection: PointPillars In Collection: PointPillars
Config: configs/pointpillars/pointpillars_hv_secfpn_sbn-all_16xb2-2x_waymoD5-3d-3class.py Config: configs/pointpillars/pointpillars_hv_secfpn_sbn-all_16xb2-2x_waymoD5-3d-3class.py
...@@ -182,7 +182,7 @@ Models: ...@@ -182,7 +182,7 @@ Models:
mAPH@L2: 52.1 mAPH@L2: 52.1
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class_20200831_204144-d1a706b1.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class_20200831_204144-d1a706b1.pth
- Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-car - Name: pointpillars_hv_secfpn_sbn_2x16_2x_waymo-3d-car
In Collection: PointPillars In Collection: PointPillars
Config: configs/pointpillars/pointpillars_hv_secfpn_sbn-all_16xb2-2x_waymo-3d-car.py Config: configs/pointpillars/pointpillars_hv_secfpn_sbn-all_16xb2-2x_waymo-3d-car.py
Metadata: Metadata:
...@@ -198,7 +198,7 @@ Models: ...@@ -198,7 +198,7 @@ Models:
mAP@L2: 63.6 mAP@L2: 63.6
mAPH@L2: 63.1 mAPH@L2: 63.1
- Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-3class - Name: pointpillars_hv_secfpn_sbn_2x16_2x_waymo-3d-3class
In Collection: PointPillars In Collection: PointPillars
Config: configs/pointpillars/pointpillars_hv_secfpn_sbn-all_16xb2-2x_waymo-3d-3class.py Config: configs/pointpillars/pointpillars_hv_secfpn_sbn-all_16xb2-2x_waymo-3d-3class.py
Metadata: Metadata:
......
_base_ = 'pointpillars_hv_fpn_sbn-all_8xb4-2x_nus-3d.py' _base_ = './pointpillars_hv_fpn_sbn-all_8xb4-2x_nus-3d.py'
train_dataloader = dict(batch_size=2, num_workers=2)
# schedule settings # schedule settings
optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.) optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.)
_base_ = 'pointpillars_hv_secfpn_sbn-all_8xb4-2x_nus-3d.py' _base_ = './pointpillars_hv_secfpn_sbn-all_8xb4-2x_nus-3d.py'
train_dataloader = dict(batch_size=2, num_workers=2)
# schedule settings # schedule settings
optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.) optim_wrapper = dict(type='AmpOptimWrapper', loss_scale=512.)
...@@ -4,7 +4,7 @@ ...@@ -4,7 +4,7 @@
<!-- [ALGORITHM] --> <!-- [ALGORITHM] -->
## Introduction ## Abstract
3D object detection has been receiving increasing attention from both industry and academia thanks to its wide applications in various fields such as autonomous driving and robotics. LiDAR sensors are widely adopted in autonomous driving vehicles and robots for capturing 3D scene information as sparse and irregular point clouds, which provide vital cues for 3D scene perception and understanding. In this paper, we propose to achieve high performance 3D object detection by designing novel point-voxel integrated networks to learn better 3D features from irregular point clouds. 3D object detection has been receiving increasing attention from both industry and academia thanks to its wide applications in various fields such as autonomous driving and robotics. LiDAR sensors are widely adopted in autonomous driving vehicles and robots for capturing 3D scene information as sparse and irregular point clouds, which provide vital cues for 3D scene perception and understanding. In this paper, we propose to achieve high performance 3D object detection by designing novel point-voxel integrated networks to learn better 3D features from irregular point clouds.
......
Models: Models:
- Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d - Name: pointpillars_hv_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d
In Collection: PointPillars In Collection: PointPillars
Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_8xb4-2x_nus-3d.py Config: configs/regnet/pointpillars_hv_regnet-400mf_secfpn_sbn-all_8xb4-2x_nus-3d.py
Metadata: Metadata:
Training Data: nuScenes Training Data: nuScenes
Training Memory (GB): 16.4 Training Memory (GB): 16.4
...@@ -16,9 +16,9 @@ Models: ...@@ -16,9 +16,9 @@ Models:
NDS: 55.2 NDS: 55.2
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d_20200620_230334-53044f32.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d_20200620_230334-53044f32.pth
- Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d - Name: pointpillars_hv_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d
In Collection: PointPillars In Collection: PointPillars
Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d.py Config: configs/regnet/pointpillars_hv_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d.py
Metadata: Metadata:
Training Data: nuScenes Training Data: nuScenes
Training Memory (GB): 17.3 Training Memory (GB): 17.3
...@@ -33,9 +33,9 @@ Models: ...@@ -33,9 +33,9 @@ Models:
NDS: 56.4 NDS: 56.4
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d_20200620_230239-c694dce7.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d_20200620_230239-c694dce7.pth
- Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_8xb4-2x_nus-3d - Name: pointpillars_hv_regnet-1.6gf_fpn_sbn-all_8xb4-2x_nus-3d
In Collection: PointPillars In Collection: PointPillars
Config: configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_8xb4-2x_nus-3d.py Config: configs/regnet/pointpillars_hv_regnet-1.6gf_fpn_sbn-all_8xb4-2x_nus-3d.py
Metadata: Metadata:
Training Data: nuScenes Training Data: nuScenes
Training Memory (GB): 24.0 Training Memory (GB): 24.0
...@@ -50,9 +50,9 @@ Models: ...@@ -50,9 +50,9 @@ Models:
NDS: 59.3 NDS: 59.3
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d_20200629_050311-dcd4e090.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d_20200629_050311-dcd4e090.pth
- Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d - Name: pointpillars_hv_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d
In Collection: PointPillars In Collection: PointPillars
Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d.py Config: configs/regnet/pointpillars_hv_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d.py
Metadata: Metadata:
Training Data: Lyft Training Data: Lyft
Training Memory (GB): 15.9 Training Memory (GB): 15.9
...@@ -67,9 +67,9 @@ Models: ...@@ -67,9 +67,9 @@ Models:
Public Score: 15.1 Public Score: 15.1
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d_20210524_092151-42513826.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d_20210524_092151-42513826.pth
- Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d - Name: pointpillars_hv_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d
In Collection: PointPillars In Collection: PointPillars
Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py Config: configs/regnet/pointpillars_hv_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py
Metadata: Metadata:
Training Data: Lyft Training Data: Lyft
Training Memory (GB): 13.0 Training Memory (GB): 13.0
......
...@@ -60,7 +60,7 @@ Models: ...@@ -60,7 +60,7 @@ Models:
- Name: second_hv_secfpn_8xb6-amp-80e_kitti-3d-car - Name: second_hv_secfpn_8xb6-amp-80e_kitti-3d-car
In Collection: SECOND In Collection: SECOND
Config: configs/second/hv_second_secfpn_8xb6-amp-80e_kitti-3d-car.py Config: configs/second/second_hv_secfpn_8xb6-amp-80e_kitti-3d-car.py
Metadata: Metadata:
Training Techniques: Training Techniques:
- AdamW - AdamW
...@@ -79,7 +79,7 @@ Models: ...@@ -79,7 +79,7 @@ Models:
- Name: second_hv_secfpn_8xb6-amp-80e_kitti-3d-3class - Name: second_hv_secfpn_8xb6-amp-80e_kitti-3d-3class
In Collection: SECOND In Collection: SECOND
Config: configs/second/hv_second_secfpn_8xb6-amp-80e_kitti-3d-3class.py Config: configs/second/second_hv_secfpn_8xb6-amp-80e_kitti-3d-3class.py
Metadata: Metadata:
Training Techniques: Training Techniques:
- AdamW - AdamW
......
...@@ -17,9 +17,9 @@ Collections: ...@@ -17,9 +17,9 @@ Collections:
Version: v1.0.0 Version: v1.0.0
Models: Models:
- Name: smoke_dla34_pytorch_dlaneck_gn-all_4xb8-6x_kitti-mono3d - Name: smoke_dla34_dlaneck_gn-all_4xb8-6x_kitti-mono3d
In Collection: SMOKE In Collection: SMOKE
Config: configs/smoke/smoke_dla34_pytorch_dlaneck_gn-all_4xb8-6x_kitti-mono3d.py Config: configs/smoke/smoke_dla34_dlaneck_gn-all_4xb8-6x_kitti-mono3d.py
Metadata: Metadata:
Training Memory (GB): 9.6 Training Memory (GB): 9.6
Results: Results:
......
...@@ -11,8 +11,8 @@ We list some potential troubles encountered by users and developers, along with ...@@ -11,8 +11,8 @@ We list some potential troubles encountered by users and developers, along with
| MMDetection3D version | MMEngine version | MMCV version | MMDetection version | | MMDetection3D version | MMEngine version | MMCV version | MMDetection version |
| --------------------- | :----------------------: | :---------------------: | :----------------------: | | --------------------- | :----------------------: | :---------------------: | :----------------------: |
| dev-1.x | mmengine>=0.6.0, \<1.0.0 | mmcv>=2.0.0rc4, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | | dev-1.x | mmengine>=0.6.0, \<1.0.0 | mmcv>=2.0.0rc4, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
| v1.1.0rc3 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | | v1.1.0rc3 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc3, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
| v1.1.0rc2 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | | v1.1.0rc2 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc3, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
| v1.1.0rc1 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | | v1.1.0rc1 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
| v1.1.0rc0 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | | v1.1.0rc0 | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
......
...@@ -44,7 +44,7 @@ conda install pytorch torchvision cpuonly -c pytorch ...@@ -44,7 +44,7 @@ conda install pytorch torchvision cpuonly -c pytorch
```shell ```shell
pip install -U openmim pip install -U openmim
mim install mmengine mim install mmengine
mim install 'mmcv>=2.0.0rc0' mim install 'mmcv>=2.0.0rc4'
mim install 'mmdet>=3.0.0rc0' mim install 'mmdet>=3.0.0rc0'
``` ```
......
...@@ -23,3 +23,5 @@ Import: ...@@ -23,3 +23,5 @@ Import:
- configs/smoke/metafile.yml - configs/smoke/metafile.yml
- configs/ssn/metafile.yml - configs/ssn/metafile.yml
- configs/votenet/metafile.yml - configs/votenet/metafile.yml
- configs/pv_rcnn/metafile.yml
- configs/fcaf3d/metafile.yml
...@@ -34,9 +34,9 @@ python tools/test.py projects/PETR/config/petr/petr_vovnet_gridmask_p4_800x320.p ...@@ -34,9 +34,9 @@ python tools/test.py projects/PETR/config/petr/petr_vovnet_gridmask_p4_800x320.p
This Result is trained by petr_vovnet_gridmask_p4_800x320.py and use [weights](https://drive.google.com/file/d/1ABI5BoQCkCkP4B0pO5KBJ3Ni0tei0gZi/view?usp=sharing) as pretrain weight. This Result is trained by petr_vovnet_gridmask_p4_800x320.py and use [weights](https://drive.google.com/file/d/1ABI5BoQCkCkP4B0pO5KBJ3Ni0tei0gZi/view?usp=sharing) as pretrain weight.
| Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download | | Backbone | Lr schd | Mem (GB) | Inf time (fps) | mAP | NDS | Download |
| :----------------------------------------------------------------------------------------------: | :-----: | :------: | :------------: | :--: | :--: | :----------------------: | | :---------------------------------------------------------------------------: | :-----: | :------: | :------------: | :--: | :--: | :----------------------: |
| [petr_vovnet_gridmask_p4_800x320](projects/PETR/configs/petr/petr_vovnet_gridmask_p4_800x320.py) | 1x | 7.62 | 18.7 | 38.3 | 43.5 | [model](<>) \| [log](<>) | | [petr_vovnet_gridmask_p4_800x320](configs/petr_vovnet_gridmask_p4_800x320.py) | 1x | 7.62 | 18.7 | 38.3 | 43.5 | [model](<>) \| [log](<>) |
``` ```
mAP: 0.3830 mAP: 0.3830
......
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