For now we only support offline benchmark with a single reconstructed point clound for each scene. Online benchmark for single RGB-D frame detection can be supported in the future. The utils directory is used unchanged from ARKitScenes, except fixing a single issue.
- Download data from the official ARKitScenes. From their repo you may run:
python download_data.py 3dod --video-id-csv threedod/3dod_train_val_splits.csv
After this step you have the following file structure here:
3dod
├── metadata.csv
├── Training
│ ├── xxxxxxxx
│ │ ├── xxxxxxxx_3dod_annotation.json
│ │ ├── xxxxxxxx_3dod_mesh.ply
│ │ ├── xxxxxxxx_frames
├── Validation
│ ├── xxxxxxxx
│ │ ├── xxxxxxxx_3dod_annotation.json
│ │ ├── xxxxxxxx_3dod_mesh.ply
│ │ ├── xxxxxxxx_frames
- Preprocess data for offline benchmark with our adapted script:
python data_prepare_offline.py
After this step you have the following file structure here:
offline_prepared_data
├── xxxxxxxx_point.npy
├── xxxxxxxx_bbox.npy
├── xxxxxxxx_label.npy
- Enter the project root directory, generate training and validation data by running:
python tools/create_data.py arkitscenes --root-path ./data/arkitscenes --out-dir ./data/arkitscenes --extra-tag arkitscenes-offline
Overall you achieve the following file structure in data directory:
arkitscenes
├── offline_prepared_data
│ ├── xxxxxxxx_point.bin
├── arkitscenes_offline_train_infos.pkl
├── arkitscenes_offline_val_infos.pkl