Please organize the dataset and the necessary files according to the following directory structure.
step 1: Download nuScenes V1.0 full dataset data from HERE on ./data/nuscenes.
step 2: Download nuScenes-lidarseg data from HERE.
step 3: Download (only) the 'gts' from Occ3D-nuScenes.
step 4: Download the pkl files from Huggingface.
step 5: Download pre-trained model weights from Huggingface.
step 6 Download pkl files preprocessed by admlp and occworld from Huggingface, which is consistent with PreWorld.
SparseWorld
├── mmdet3d/
├── tools/
├── env/
├── configs/
├── ckpts/
│ ├── epoch_56.pth
| ├── cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim_20201009_124951-40963960.pth
├── data/
│ ├── nuscenes/
│ │ ├── gts/ # ln -s occupancy gts to this location
│ │ ├── maps/
│ │ ├── samples/
│ │ ├── sweeps/
│ │ ├── v1.0-trainval/
| | ├── bevdetv2-nuscenes_infos_val.pkl
| | ├── bevdetv2-nuscenes_infos_train.pkl
├── occworld/
│ ├── nuscenes_infos_train_temporal_v3_scene.pkl
│ └── nuscenes_infos_val_temporal_v3_scene.pkl
├── admlp/
│ ├── fengze_nuscenes_infos_val.pkl
│ ├── fengze_nuscenes_infos_train.pkl
│ └── stp3_val
│ ├── data_nuscene.pkl
│ ├── filter_token.pkl
│ ├── stp3_occupancy.pkl
│ └── stp3_traj_gt.pkl
Then, create a symbolic link for the planning evaluation.
cd AD-MLP/pytorch/admlp
ln -s ../../../admlp/stp3_val stp3_val
cd ../../..