prepare_dataset.md

SemanticKITTI

To prepare for SemanticKITTI dataset, please download the KITTI Odometry Dataset (including color, velodyne laser data, and calibration files) and the annotations for Semantic Scene Completion from SemanticKITTI. Put all .zip files under SparseOcc/data/SemanticKITTI and unzip these files. Then you should get the following dataset structure:

SparseOcc
├── data/
│   ├── SemanticKITTI/
│   │   ├── dataset/
│   │   │   ├── sequences
│   │   │   │   ├── 00
│   │   │   │   │   ├── calib.txt
│   │   │   │   │   ├── image_2/
│   │   │   │   │   ├── image_3/
│   │   │   │   │   ├── voxels/
│   │   │   │   ├── 01
│   │   │   │   ├── 02
│   │   │   │   ├── ...
│   │   │   │   ├── 21

Preprocess the annotations for semantic scene completion:

python projects/mmdet3d_plugin/tools/kitti_process/semantic_kitti_preprocess.py --kitti_root data/SemanticKITTI --kitti_preprocess_root data/SemanticKITTI --data_info_path projects/mmdet3d_plugin/tools/kitti_process/semantic-kitti.yaml

OpenOccupancy

Please refer to OpenOccupancy for dataset download and preparation. The final folder structure should be

SparseOcc
├── data/
│   ├── nuscenes/
│   │   ├── maps/
│   │   ├── samples/
│   │   ├── sweeps/
│   │   ├── lidarseg/
│   │   ├── v1.0-test/
│   │   ├── v1.0-trainval/
│   │   ├── nuscenes_occ_infos_train.pkl/
│   │   ├── nuscenes_occ_infos_val.pkl/
│   ├── depth_gt/
│   ├── nuScenes-Occupancy/