Follow https://github.com/fundamentalvision/BEVFormer/blob/master/docs/install.md to prepare the environment.
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Download the gts and annotations.json we provided. You can download our imgs.tar.gz or using the original sample files of the nuScenes dataset.
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Download the CAN bus expansion data and maps HERE.
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Organize your folder structure as below:
Occupancy3D
├── projects/
├── tools/
├── ckpts/
│ ├── r101_dcn_fcos3d_pretrain.pth
├── data/
│ ├── can_bus/
│ ├── occ3d-nus/
│ │ ├── maps/
│ │ ├── samples/ # You can download our imgs.tar.gz or using the original sample files of the nuScenes dataset
│ │ ├── v1.0-trainval/
│ │ ├── gts/
│ │ │── annotations.json
- Generate the info files for training and validation:
python tools/create_data.py occ --root-path ./data/occ3d-nus --out-dir ./data/occ3d-nus --extra-tag occ --version v1.0-trainval --canbus ./data --occ-path ./data/occ3d-nus
./tools/dist_train.sh projects/configs/bevformer/bevformer_base_occ.py 8
./tools/dist_test.sh projects/configs/bevformer/bevformer_base_occ.py work_dirs/bevformer_base_occ/epoch_24.pth 8
You can evaluate the F-score at the same time by adding --eval_fscore
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model name | weight | mIoU | others | barrier | bicycle | bus | car | construction_vehicle | motorcycle | pedestrian | traffic_cone | trailer | truck | driveable_surface | other_flat | sidewalk | terrain | manmade | vegetation |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bevformer_base_occ | Google Drive | 23.67 | 5.03 | 38.79 | 9.98 | 34.41 | 41.09 | 13.24 | 16.50 | 18.15 | 17.83 | 18.66 | 27.7 | 48.95 | 27.73 | 29.08 | 25.38 | 15.41 | 14.46 |