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Unverified Commit 864ed34f authored by Jingwei Zhang's avatar Jingwei Zhang Committed by GitHub
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[Fix] Fix invalid configs (#2477) 

* fix invalid configs

* fix metafile in nuimages

* remove breakpoint

* minor fix
parent e90e1767
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Showing with 55 additions and 167 deletions
configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn-circlenms_8xb4-flip-tta-cyclic-20e_nus-3d.py
View file @ 864ed34f
_base_ = './centerpoint_voxel0075_second_secfpn_' \ _base_ = './centerpoint_voxel0075_second_secfpn_head-dcn-circlenms_8xb4-cyclic-20e_nus-3d.py' # noqa: E501
'head-dcn-circlenms_8xb4_cyclic-20e_nus-3d.py'
point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0] point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
# Using calibration info convert the Lidar-coordinate point cloud range to the # Using calibration info convert the Lidar-coordinate point cloud range to the
......
configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-flip-tta-cyclic-20e_nus-3d.py
View file @ 864ed34f
_base_ = './centerpoint_voxel0075_second_secfpn' \ _base_ = \
'_head-dcn_8xb4-cyclic-20e_nus-3d.py' './centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-cyclic-20e_nus-3d.py'
point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0] point_cloud_range = [-54, -54, -5.0, 54, 54, 3.0]
# Using calibration info convert the Lidar-coordinate point cloud range to the # Using calibration info convert the Lidar-coordinate point cloud range to the
......
configs/centerpoint/centerpoint_voxel0075_second_secfpn_head-dcn_8xb4-tta-cyclic-20e_nus-3d.py
View file @ 864ed34f
_base_ = './centerpoint_voxel0075_second_secfpn' \ _base_ = \
'_head-dcn_8xb4-cyclic-20e_nus-3d.py' './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))) model = dict(test_cfg=dict(pts=dict(use_rotate_nms=True, max_num=500)))
......
configs/dfm/multiview-dfm_r101-dcn_centerhead_16xb2_waymoD5-3d-3class.py
View file @ 864ed34f
_base_ = ['./multiview-dfm_r101_dcn_2x16_waymoD5-3d-3class.py'] _base_ = ['./multiview-dfm_r101-dcn_16xb2_waymoD5-3d-3class.py']
model = dict( model = dict(
bbox_head=dict( bbox_head=dict(
......
configs/dynamic_voxelization/second_dv_secfpn_8xb6-80e_kitti-3d-car.py
View file @ 864ed34f
_base_ = '../second/hv_second_secfpn_6x8_80e_kitti-3d-car.py' _base_ = '../second/second_hv_secfpn_8xb6-80e_kitti-3d-car.py'
point_cloud_range = [0, -40, -3, 70.4, 40, 1] point_cloud_range = [0, -40, -3, 70.4, 40, 1]
voxel_size = [0.05, 0.05, 0.1] voxel_size = [0.05, 0.05, 0.1]
......
configs/nuimages/README.md
View file @ 864ed34f
...@@ -43,18 +43,18 @@ We report Mask R-CNN and Cascade Mask R-CNN results on nuimages. ...@@ -43,18 +43,18 @@ We report Mask R-CNN and Cascade Mask R-CNN results on nuimages.
| Method | Backbone | Pretraining | Lr schd | Mem (GB) | Box AP | Mask AP | Download | | Method | Backbone | Pretraining | Lr schd | Mem (GB) | Box AP | Mask AP | Download |
| :----------------: | :-----------------------------------------------------------------------------------: | :---------: | :-----: | :------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | :----------------: | :-----------------------------------------------------------------------------------: | :---------: | :-----: | :------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| Mask R-CNN | [R-50](./mask_rcnn_r50_fpn_1x_nuim.py) | IN | 1x | 7.4 | 47.8 | 38.4 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238-e99f5182.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238.log.json) | | Mask R-CNN | [R-50](./mask-rcnn_r50_fpn_1x_nuim.py) | IN | 1x | 7.4 | 47.8 | 38.4 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238-e99f5182.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238.log.json) |
| Mask R-CNN | [R-50](./mask_rcnn_r50_fpn_coco-2x_1x_nuim.py) | IN+COCO-2x | 1x | 7.4 | 49.7 | 40.5 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238-b1742a60.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238.log.json) | | Mask R-CNN | [R-50](./mask-rcnn_r50_fpn_coco-2x_1x_nuim.py) | IN+COCO-2x | 1x | 7.4 | 49.7 | 40.5 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238-b1742a60.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238.log.json) |
| 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_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_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-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 | [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 | [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_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_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) | | 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) |
| Cascade Mask R-CNN | [R-101](./cascade_mask_rcnn_r101_fpn_1x_nuim.py) | IN | 1x | 12.5 | 51.5 | 40.7 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804-45215b1e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804.log.json) | | Cascade Mask R-CNN | [R-101](./cascade-mask-rcnn_r101_fpn_1x_nuim.py) | IN | 1x | 12.5 | 51.5 | 40.7 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804-45215b1e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804.log.json) |
| Cascade Mask R-CNN | [X-101_32x4d](./cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim.py) | IN | 1x | 14.9 | 52.8 | 41.6 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135753-e0e49778.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135753.log.json) | | Cascade Mask R-CNN | [X-101_32x4d](./cascade-mask-rcnn_x101_32x4d_fpn_1x_nuim.py) | IN | 1x | 14.9 | 52.8 | 41.6 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135753-e0e49778.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135753.log.json) |
| HTC w/o semantic | [R-50](./htc_without_semantic_r50_fpn_1x_nuim.py) | IN | 1x | | [model](<>) \| [log](<>) | | | | HTC w/o semantic | [R-50](./htc_without_semantic_r50_fpn_1x_nuim.py) | IN | 1x | | [model](<>) \| [log](<>) | | |
| HTC | [R-50](./htc_r50_fpn_1x_nuim.py) | IN | 1x | | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/) | | | | HTC | [R-50](./htc_r50_fpn_1x_nuim.py) | IN | 1x | | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/) | | |
| HTC | [R-50](./htc_r50_fpn_coco-20e_1x_nuim.py) | IN+COCO-20e | 1x | 11.6 | 53.8 | 43.8 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_r50_fpn_coco-20e_1x_nuim/htc_r50_fpn_coco-20e_1x_nuim_20201010_070203-0b53a65e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_r50_fpn_coco-20e_1x_nuim/htc_r50_fpn_coco-20e_1x_nuim_20201010_070203.log.json) | | HTC | [R-50](./htc_r50_fpn_coco-20e_1x_nuim.py) | IN+COCO-20e | 1x | 11.6 | 53.8 | 43.8 | [model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_r50_fpn_coco-20e_1x_nuim/htc_r50_fpn_coco-20e_1x_nuim_20201010_070203-0b53a65e.pth) \| [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_r50_fpn_coco-20e_1x_nuim/htc_r50_fpn_coco-20e_1x_nuim_20201010_070203.log.json) |
......
configs/nuimages/cascade-mask-rcnn-r50-fpn_coco-20e_nuim.py
View file @ 864ed34f
_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py' _base_ = './cascade-mask-rcnn_r50_fpn_1x_nuim.py'
# learning policy # learning policy
lr_config = dict(step=[16, 19]) lr_config = dict(step=[16, 19])
......
configs/nuimages/cascade-mask-rcnn_r101_fpn_1x_nuim.py
View file @ 864ed34f
_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py' _base_ = './cascade-mask-rcnn_r50_fpn_1x_nuim.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
configs/nuimages/cascade-mask-rcnn_r50_fpn_1x_nuim.py
View file @ 864ed34f
_base_ = [ _base_ = [
'../_base_/models/cascade_mask_rcnn_r50_fpn.py', '../_base_/models/cascade-mask-rcnn_r50_fpn.py',
'../_base_/datasets/nuim_instance.py', '../_base_/datasets/nuim-instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py' '../_base_/schedules/mmdet-schedule-1x.py', '../_base_/default_runtime.py'
] ]
model = dict( model = dict(
roi_head=dict( roi_head=dict(
......
configs/nuimages/cascade-mask-rcnn_r50_fpn_coco-20e-1x_nuim.py
View file @ 864ed34f
_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py' _base_ = './cascade-mask-rcnn_r50_fpn_1x_nuim.py'
load_from = 'http://download.openmmlab.com/mmdetection/v2.0/cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco/cascade_mask_rcnn_r50_fpn_20e_coco_bbox_mAP-0.419__segm_mAP-0.365_20200504_174711-4af8e66e.pth' # noqa load_from = 'http://download.openmmlab.com/mmdetection/v2.0/cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco/cascade_mask_rcnn_r50_fpn_20e_coco_bbox_mAP-0.419__segm_mAP-0.365_20200504_174711-4af8e66e.pth' # noqa
configs/nuimages/cascade-mask-rcnn_x101_32x4d_fpn_1x_nuim.py
View file @ 864ed34f
_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py' _base_ = './cascade-mask-rcnn_r50_fpn_1x_nuim.py'
model = dict( model = dict(
pretrained='open-mmlab://resnext101_32x4d', pretrained='open-mmlab://resnext101_32x4d',
backbone=dict( backbone=dict(
......
configs/nuimages/htc_r50_fpn_1x_nuim.py
View file @ 864ed34f
_base_ = './htc_without_semantic_r50_fpn_1x_nuim.py' _base_ = './htc_r50_fpn_head-without-semantic_1x_nuim.py'
model = dict( model = dict(
roi_head=dict( roi_head=dict(
semantic_roi_extractor=dict( semantic_roi_extractor=dict(
......
configs/nuimages/mask-rcnn_r101_fpn_1x_nuim.py
View file @ 864ed34f
_base_ = './mask_rcnn_r50_fpn_1x_nuim.py' _base_ = './mask-rcnn_r50_fpn_1x_nuim.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
configs/nuimages/mask-rcnn_r50_fpn_coco-2x_1x_nus-2d.py
View file @ 864ed34f
_base_ = [ _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py', '../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/nuim_instance.py', '../_base_/datasets/nuim-instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py' '../_base_/schedules/mmdet-schedule-1x.py', '../_base_/default_runtime.py'
] ]
model = dict( model = dict(
roi_head=dict( roi_head=dict(
......
configs/nuimages/mask-rcnn_x101_32x4d_fpn_1x_nuim.py
View file @ 864ed34f
_base_ = './mask_rcnn_r50_fpn_1x_nuim.py' _base_ = './mask-rcnn_r50_fpn_1x_nuim.py'
model = dict( model = dict(
pretrained='open-mmlab://resnext101_32x4d', pretrained='open-mmlab://resnext101_32x4d',
backbone=dict( backbone=dict(
......
configs/nuimages/metafile.yml
View file @ 864ed34f
...@@ -23,9 +23,9 @@ Collections: ...@@ -23,9 +23,9 @@ Collections:
Version: v2.0.0 Version: v2.0.0
Models: Models:
- Name: mask_rcnn_r50_fpn_1x_nuim - Name: mask-rcnn_r50_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask_rcnn_r50_fpn_1x_nuim.py Config: configs/nuimages/mask-rcnn_r50_fpn_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 7.4 Training Memory (GB): 7.4
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -40,9 +40,9 @@ Models: ...@@ -40,9 +40,9 @@ Models:
Mask AP: 38.4 Mask AP: 38.4
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238-e99f5182.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238-e99f5182.pth
- Name: mask_rcnn_r50_fpn_coco-2x_1x_nuim - Name: mask-rcnn_r50_fpn_coco-2x_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask_rcnn_r50_fpn_coco-2x_1x_nuim.py Config: configs/nuimages/mask-rcnn_r50_fpn_coco-2x_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 7.4 Training Memory (GB): 7.4
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -57,9 +57,9 @@ Models: ...@@ -57,9 +57,9 @@ Models:
Mask AP: 40.5 Mask AP: 40.5
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238-b1742a60.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238-b1742a60.pth
- Name: mask_rcnn_r50_caffe_fpn_1x_nuim - Name: mask-rcnn_r50_caffe_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask_rcnn_r50_caffe_fpn_1x_nuim.py Config: configs/nuimages/mask-rcnn_r50_caffe_fpn_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 7.0 Training Memory (GB): 7.0
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -74,9 +74,9 @@ Models: ...@@ -74,9 +74,9 @@ Models:
Mask AP: 38.2 Mask AP: 38.2
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/ Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/
- Name: mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim - Name: mask-rcnn_r50_caffe_fpn_coco-3x_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py Config: configs/nuimages/mask-rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 7.0 Training Memory (GB): 7.0
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -91,9 +91,9 @@ Models: ...@@ -91,9 +91,9 @@ Models:
Mask AP: 40.8 Mask AP: 40.8
Weights: 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 Weights: 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
- Name: mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim - Name: mask-rcnn_r50_caffe_fpn_coco-3x_20e_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py Config: configs/nuimages/mask-rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py
Metadata: Metadata:
Training Memory (GB): 7.0 Training Memory (GB): 7.0
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -108,7 +108,7 @@ Models: ...@@ -108,7 +108,7 @@ Models:
Mask AP: 41.3 Mask AP: 41.3
Weights: 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 Weights: 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
- Name: mask_rcnn_r101_fpn_1x_nuim - Name: mask-rcnn_r101_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask-rcnn_r101_fpn_1x_nuim.py Config: configs/nuimages/mask-rcnn_r101_fpn_1x_nuim.py
Metadata: Metadata:
...@@ -125,7 +125,7 @@ Models: ...@@ -125,7 +125,7 @@ Models:
Mask AP: 39.1 Mask AP: 39.1
Weights: 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 Weights: 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
- Name: mask_rcnn_x101_32x4d_fpn_1x_nuim - Name: mask-rcnn_x101_32x4d_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/mask-rcnn_x101_32x4d_fpn_1x_nuim.py Config: configs/nuimages/mask-rcnn_x101_32x4d_fpn_1x_nuim.py
Metadata: Metadata:
...@@ -142,9 +142,9 @@ Models: ...@@ -142,9 +142,9 @@ Models:
Mask AP: 40.5 Mask AP: 40.5
Weights: 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 Weights: 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
- Name: cascade_mask_rcnn_r50_fpn_1x_nuim - Name: cascade-mask-rcnn_r50_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/cascade_mask_rcnn_r50_fpn_1x_nuim.py Config: configs/nuimages/cascade-mask-rcnn_r50_fpn_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 8.9 Training Memory (GB): 8.9
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -159,9 +159,9 @@ Models: ...@@ -159,9 +159,9 @@ Models:
Mask AP: 40.4 Mask AP: 40.4
Weights: 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 Weights: 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
- Name: cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim - Name: cascade-mask-rcnn_r50_fpn_coco-20e_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim.py Config: configs/nuimages/cascade-mask-rcnn_r50_fpn_coco-20e_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 8.9 Training Memory (GB): 8.9
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -176,9 +176,9 @@ Models: ...@@ -176,9 +176,9 @@ Models:
Mask AP: 42.2 Mask AP: 42.2
Weights: 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 Weights: 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
- Name: cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim - Name: cascade-mask-rcnn_r50_fpn_coco-20e_20e_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim.py Config: configs/nuimages/cascade-mask-rcnn_r50_fpn_coco-20e_20e_nuim.py
Metadata: Metadata:
Training Memory (GB): 8.9 Training Memory (GB): 8.9
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -193,9 +193,9 @@ Models: ...@@ -193,9 +193,9 @@ Models:
Mask AP: 42.2 Mask AP: 42.2
Weights: 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 Weights: 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
- Name: cascade_mask_rcnn_r101_fpn_1x_nuim - Name: cascade-mask-rcnn_r101_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/cascade_mask_rcnn_r101_fpn_1x_nuim.py Config: configs/nuimages/cascade-mask-rcnn_r101_fpn_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 12.5 Training Memory (GB): 12.5
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
...@@ -210,9 +210,9 @@ Models: ...@@ -210,9 +210,9 @@ Models:
Mask AP: 40.7 Mask AP: 40.7
Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804-45215b1e.pth Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804-45215b1e.pth
- Name: cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim - Name: cascade-mask-rcnn_x101_32x4d_fpn_1x_nuim
In Collection: Mask R-CNN In Collection: Mask R-CNN
Config: configs/nuimages/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim.py Config: configs/nuimages/cascade-mask-rcnn_x101_32x4d_fpn_1x_nuim.py
Metadata: Metadata:
Training Memory (GB): 14.9 Training Memory (GB): 14.9
Training Resources: 8x TITAN Xp Training Resources: 8x TITAN Xp
......
configs/pgd/pgd_r101_fpn-head_dcn_16xb3_waymoD5-mono3d.py deleted 100644 → 0
View file @ e90e1767
_base_ = [
'../_base_/datasets/waymoD5-mono3d-3class.py', '../_base_/models/pgd.py',
'../_base_/schedules/mmdet-schedule-1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
backbone=dict(
type='mmdet.ResNet',
depth=101,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet101'),
dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, False, True, True)),
neck=dict(num_outs=3),
bbox_head=dict(
num_classes=3,
bbox_code_size=7,
pred_attrs=False,
pred_velo=False,
pred_bbox2d=True,
use_onlyreg_proj=True,
strides=(8, 16, 32),
regress_ranges=((-1, 128), (128, 256), (256, 1e8)),
group_reg_dims=(2, 1, 3, 1, 16,
4), # offset, depth, size, rot, kpts, bbox2d
reg_branch=(
(256, ), # offset
(256, ), # depth
(256, ), # size
(256, ), # rot
(256, ), # kpts
(256, ) # bbox2d
),
centerness_branch=(256, ),
loss_cls=dict(
type='mmdet.FocalLoss',
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
loss_weight=1.0),
loss_bbox=dict(
type='mmdet.SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0),
loss_dir=dict(
type='mmdet.CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
loss_centerness=dict(
type='mmdet.CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
use_depth_classifier=True,
depth_branch=(256, ),
depth_range=(0, 50),
depth_unit=10,
division='uniform',
depth_bins=6,
pred_keypoints=True,
weight_dim=1,
loss_depth=dict(
type='UncertainSmoothL1Loss', alpha=1.0, beta=3.0,
loss_weight=1.0),
loss_bbox2d=dict(
type='mmdet.SmoothL1Loss', beta=1.0 / 9.0, loss_weight=0.0),
loss_consistency=dict(type='mmdet.GIoULoss', loss_weight=0.0),
bbox_coder=dict(
type='PGDBBoxCoder',
base_depths=((41.01, 18.44), ),
base_dims=(
(4.73, 1.77, 2.08),
(0.91, 1.74, 0.84),
(1.81, 1.77, 0.84),
),
code_size=7)),
# set weight 1.0 for base 7 dims (offset, depth, size, rot)
# 0.2 for 16-dim keypoint offsets and 1.0 for 4-dim 2D distance targets
train_cfg=dict(code_weight=[
1.0, 1.0, 0.2, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 1.0, 1.0, 1.0, 1.0
]),
test_cfg=dict(nms_pre=100, nms_thr=0.05, score_thr=0.001, max_per_img=20))
# optimizer
optim_wrapper = dict(
optimizer=dict(
type='SGD',
lr=0.008,
),
paramwise_cfg=dict(bias_lr_mult=2., bias_decay_mult=0.),
clip_grad=dict(max_norm=35, norm_type=2))
param_scheduler = [
dict(
type='LinearLR',
start_factor=1.0 / 3,
by_epoch=False,
begin=0,
end=500),
dict(
type='MultiStepLR',
begin=0,
end=24,
by_epoch=True,
milestones=[16, 22],
gamma=0.1)
]
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=24, val_interval=24)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
auto_scale_lr = dict(base_batch_size=48)
configs/regnet/pointpillars_hv_regnet-400mf_secfpn_sbn-all_8xb2-2x_lyft-3d.py
View file @ 864ed34f
_base_ = './hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py' _base_ = './pointpillars_hv_regnet-400mf_fpn_sbn-all_8xb2-2x_lyft-3d.py'
# model settings # model settings
model = dict( model = dict(
pts_neck=dict( pts_neck=dict(
......
configs/regnet/pointpillars_hv_regnet-400mf_secfpn_sbn-all_8xb4-2x_nus-3d.py
View file @ 864ed34f
_base_ = './hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py' _base_ = './pointpillars_hv_regnet-400mf_fpn_sbn-all_8xb4-2x_nus-3d.py'
# model settings # model settings
model = dict( model = dict(
pts_neck=dict( pts_neck=dict(
......
configs/regnet/pointpillars_hv_regnet-400mf_secfpn_sbn-all_range100_8xb2-2x_lyft-3d.py
View file @ 864ed34f
_base_ = \ _base_ = \
'./hv_pointpillars_regnet-400mf_fpn_sbn-all_range100_2x8_2x_lyft-3d.py' './pointpillars_hv_regnet-400mf_fpn_sbn-all_range100_8xb2-2x_lyft-3d.py'
# model settings # model settings
model = dict( model = dict(
pts_neck=dict( pts_neck=dict(
......
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