# MAP-Bench training split

**35,454 trajectories · 7,184,098 RGB frames · 15 Hz**

This split supplies forward RGB videos, base navigation commands, target-object
boxes, image-plane Manipulation Anchor Pose annotations, and task instructions.
It is the training data for the UniWAM-Base navigation preset. The 15,000
closed-loop evaluation episodes are provided separately under `evaluation/`.

From the [UniWAM repository](https://github.com/Fysics-AI/UniWAM):

```bash
python scripts/download_assets.py --training
```

The helper downloads the indices, normalization, and text features and verifies
and extracts eight archives to `MAP-Bench/training/episodes/`. All paths in the
indices are relative to the index directory. Each episode contains `rgb.mp4`
and `frame_annotations.jsonl`; navigation commands are stored either in
`actions_vx_vyaw.npy` or the annotations, as indicated by the index.

Use `MAP-Bench/training` as `UNIWAM_DATA_ROOT` in the
[training guide](https://github.com/Fysics-AI/UniWAM/blob/main/training/README.md).
The HM3D-derived data are subject to the benchmark [license notes](../LICENSE.md).