Add dataset card describing Vi2Act LeRobot splits

README.md

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+---
+license: apache-2.0
+task_categories:
+  - robotics
+  - video-classification
+language:
+  - en
+tags:
+  - robotics
+  - humanoid
+  - GR1
+  - LeRobot
+  - video-to-action
+  - synthetic-data
+  - cosmos-predict2
+  - dreamgen
+pretty_name: Vi2Act
+size_categories:
+  - n<1K
+---
+
+# Vi2Act
+
+**Vi2Act** is a small synthetic video-to-action dataset for the Fourier **GR1** humanoid.
+Videos are generated by a Cosmos-Predict2 14B Video2World model (GR00T-Dreams-GR1 checkpoint), then converted into [LeRobot](https://github.com/huggingface/lerobot) format.
+
+Source pipeline: [NVIDIA GR00T-Dreams / DreamGen](https://github.com/NVIDIA/GR00T-Dreams) using the [EVAL-175](https://huggingface.co/datasets/nvidia/EVAL-175) DreamGen Bench prompts and first-frame images.
+
+## What's in this repo
+
+Three LeRobot subsets (5 episodes each):
+
+| Folder | Split (EVAL-175) | Episodes | Frames | FPS | Tasks |
+|--------|------------------|----------|--------|-----|-------|
+| `gr1_env_lerobot.data/` | environment generalization | 5 | 465 | 8 | 5 |
+| `gr1_object_lerobot.data/` | object generalization | 5 | 465 | 8 | 5 |
+| `gr1_behavior_lerobot.data/` | behavior / skill generalization | 5 | 465 | 8 | 5 |
+
+**Totals:** 15 episodes, 1,395 frames, 15 language tasks, 1 ego-view camera.
+
+This is a **pilot / smoke-test** dump (`NUM_SAMPLES=5` per subset), not the full EVAL-175 benchmark.
+
+## Embodiment
+
+- Robot: Fourier GR1 (`robot_type: dream` in `meta/info.json`)
+- Action / state dim: **44** joints
+- Camera: `observation.images.ego_view`
+
+Joint layout (`meta/modality.json`):
+
+| Group | Indices |
+|-------|---------|
+| left_arm | 0–6 |
+| left_hand | 7–12 |
+| left_leg | 13–18 |
+| neck | 19–21 |
+| right_arm | 22–28 |
+| right_hand | 29–34 |
+| right_leg | 35–40 |
+| waist | 41–43 |
+
+## Directory layout (per subset)
+
+```
+{subset}_lerobot.data/
+├── data/chunk-000/episode_XXXXXX.parquet
+├── videos/chunk-000/observation.images.ego_view/episode_XXXXXX.mp4
+└── meta/
+    ├── info.json
+    ├── episodes.jsonl
+    ├── tasks.jsonl
+    ├── modality.json
+    └── stats.json
+```
+
+Each parquet row stores:
+
+- `observation.state` — `float32[44]`
+- `action` — `float32[44]`
+- `annotation.human.coarse_action` — language-task index
+- video frames referenced via LeRobot video paths
+
+> **Note on actions.** Videos and language labels come from Cosmos generation. The 44-D `action` / `state` columns follow the GR1 LeRobot schema. Inverse-dynamics (IDM) action labels (`seonghyeonye/IDM_gr1`) are intended as a follow-up upload under `*_lerobot.data_idm/`. Until that dump is published, treat action columns as schema placeholders unless you re-run IDM locally.
+
+## Language tasks
+
+### `gr1_env`
+
+1. Use the right hand to pick up chip with green packaging to white bag
+2. Use the right hand to pick up orange to metal platform
+3. Use the right hand to pick up plastic pitcher and pour water onto green plant
+4. Use the right hand to pick up the spoon from the bowl and serve the contents onto the plate
+5. Use the right hand to knock over the green Pocky box
+
+### `gr1_object`
+
+1. Use the left hand to pick up dark green cucumber from on circular gray mat to above beige bowl.
+2. Use the right hand to pick up red bell pepper from center of tan countertop to brown bottom rack.
+3. Use the left hand to pick up green pepper from tan table, below the bright blue plate to pale turquoise plate.
+4. Use the right hand to pick up milk carton from pale turquoise plate in the center of the table to second level of wooden shelf.
+5. Use the right hand to pick up green bok choy from top tier of two tier black and white shelf to brown paper bag.
+
+### `gr1_behavior`
+
+1. Use the right hand to close lunch box
+2. Use the right hand to pick up blue scoop and scoop powder from container
+3. Use the right hand to pick up glass and bring it close to the camera as if drinking
+4. Use knife to cut the object on the cutting board
+5. Use the right hand to press calculator
+
+## How the data was produced
+
+1. **World-model videos** — Cosmos-Predict2-14B Sample GR00T-Dreams-GR1, image + text conditioning, `--disable_guardrail`, 480p / 16 fps generation then resampled to 8 fps / 93 frames for Cosmos-Predict2 LeRobot packing.
+2. **Directory conversion** — DreamGen Bench filenames → per-task folders.
+3. **LeRobot export** — `IDM_dump/raw_to_lerobot.py --cosmos_predict2`.
+
+## Load with Hugging Face Hub
+
+```python
+from huggingface_hub import snapshot_download
+
+local_dir = snapshot_download(
+    repo_id="hk239/Vi2Act",
+    repo_type="dataset",
+)
+# e.g. local_dir/gr1_env_lerobot.data/
+```
+
+## Load as a LeRobot dataset
+
+```python
+from gr00t.data.dataset import LeRobotSingleDataset
+
+dataset = LeRobotSingleDataset(
+    dataset_path="gr1_env_lerobot.data",  # after download
+    embodiment_tag="gr1",
+)
+```
+
+## Citation
+
+If you use this data, please cite DreamGen / GR00T-Dreams:
+
+```bibtex
+@article{jang2025dreamgen,
+  title={DreamGen: Unlocking Generalization in Robot Learning through Video World Models},
+  author={Jang, Joel and Ye, Seonghyeon and Lin, Zongyu and Xiang, Jiannan and Bjorck, Johan and Fang, Yu and Hu, Fengyuan and Huang, Spencer and Kundalia, Kaushil and Lin, Yen-Chen and others},
+  journal={arXiv preprint arXiv:2505.12705v2},
+  year={2025}
+}
+```
+
+## Acknowledgements
+
+- [nvidia/EVAL-175](https://huggingface.co/datasets/nvidia/EVAL-175) — prompt / first-frame images
+- [nvidia/Cosmos-Predict2-14B-Sample-GR00T-Dreams-GR1](https://huggingface.co/nvidia/Cosmos-Predict2-14B-Sample-GR00T-Dreams-GR1) — video world model
+- [seonghyeonye/IDM_gr1](https://huggingface.co/seonghyeonye/IDM_gr1) — inverse dynamics model (for action extraction)