Datasetpublic

Joocjun/GR1-Tabletop-Merged-300x24

GR1 Tabletop Merged LeRobot Datasets Merged and subsampled versions of the GR1 tabletop manipulation datasets from the NVIDIA PhysicalAI-Robotics-GR00T-X-Embodiment-Sim collection, formatted in LeRobot v2.0 format. Dataset Variants Variant Demos/Task Tasks Total Episodes Total Frames Approx Size 1000x24/ 1000 24 folders, 186 unique tasks 24,000 6,020,058 ~40 GB 300x24/ 300 24 folders, 186 unique tasks 7,200 1,803,236 ~12 GB 100x24/ 100 24 folders… See the full description on the dataset page: https://huggingface.co/datasets/Joocjun/GR1-Tabletop-Merged-300x24.

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face

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Dataset Card

GR1 Tabletop Merged LeRobot Datasets

Merged and subsampled versions of the GR1 tabletop manipulation datasets from the NVIDIA PhysicalAI-Robotics-GR00T-X-Embodiment-Sim collection, formatted in LeRobot v2.0 format.

Dataset Variants

Variant	Demos/Task	Tasks	Total Episodes	Total Frames	Approx Size
`1000x24/`	1000	24 folders, 186 unique tasks	24,000	6,020,058	~40 GB
`300x24/`	300	24 folders, 186 unique tasks	7,200	1,803,236	~12 GB
`100x24/`	100	24 folders, 185 unique tasks	2,400	602,846	~4 GB

Source Dataset

The original per-task datasets were downloaded from: [nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim](https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim)

To download the original dataset:

bash

# Install huggingface_hub
pip install huggingface_hub

# Download specific task datasets
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim",
    repo_type="dataset",
    allow_patterns="gr1_unified.PnP*",  # or specific task patterns
    local_dir="./original_data"
)

The 24 source task folders used (each with 1000 demos):

—6 PnP tasks: Bottle→Cabinet, Can→Drawer, Cup→Drawer, Milk→Microwave, Potato→Microwave, Wine→Cabinet
—18 PosttrainPnPNovel tasks: Various object transfers between surfaces (Cuttingboard→{Basket,Cardboardbox,Pan,Pot,Tieredbasket}, Placemat→{Basket,Bowl,Plate,Tieredshelf}, Plate→{Bowl,Cardboardbox,Pan,Plate}, Tray→{Cardboardbox,Plate,Pot,Tieredbasket,Tieredshelf})

Processing

Each merged dataset was created by:

1.Subsampling: Randomly sampling N episodes (with seed=42) from each of the 24 task folders
2.Merging: Combining all sampled episodes into a single dataset with:
3.Re-indexed episode IDs (0 to total-1)
4.Globally re-indexed task IDs across all source folders
5.Updated parquet files with corrected episode_index, task_index, and index columns
6.Consolidated meta/ files (info.json, episodes.jsonl, tasks.jsonl, modality.json)

Note on task counts

The 100x24 variant has 185 unique tasks instead of 186. This is because some task folders contain multiple task variants (e.g., the PosttrainPnPNovelFromTrayToTieredbasket folder has 10 different object variants like eggplant, tomato, etc.). The "eggplant" variant only appears in 58 out of 1000 source episodes, so when randomly sampling only 100 episodes, none of the eggplant episodes were selected. This is expected behavior with random subsampling.

Dataset Structure (LeRobot v2.0)

<variant>/
├── data/
│   └── chunk-000/
│       ├── episode_000000.parquet
│       ├── episode_000001.parquet
│       └── ...
├── videos/
│   └── chunk-000/
│       └── observation.images.ego_view/
│           ├── episode_000000.mp4
│           ├── episode_000001.mp4
│           └── ...
└── meta/
    ├── info.json
    ├── episodes.jsonl
    ├── tasks.jsonl
    ├── modality.json
    ├── stats.json
    └── relative_stats.json

Features

Feature	Type	Shape
`observation.images.ego_view`	video (h264)	[256, 256, 3] @ 20fps
`observation.state`	float64	[44]
`action`	float64	[44]
`timestamp`	float64	[1]
`next.reward`	float64	[1]
`next.done`	bool	[1]
`task_index`	int64	[1]
`episode_index`	int64	[1]
`annotation.human.coarse_action`	int64	[1]

Robot: GR1ArmsAndWaistFourierHands (44-DOF: arms, hands, legs, neck, waist)

Usage

python

# Download a specific variant
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="Joocjun/GR1-Tabletop-Merged-LeRobot",
    repo_type="dataset",
    allow_patterns="100x24/**",  # or "300x24/**" or "1000x24/**"
    local_dir="./gr1_merged"
)

License

Apache 2.0 (following the original NVIDIA dataset license)