| # Training Data |
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| ## BONES-SEED |
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| [BONES-SEED](https://huggingface.co/datasets/bones-studio/seed) (Skeletal Everyday Embodiment Dataset) is an open dataset of **142,220 annotated human motion animations** for humanoid robotics, created by [Bones Studio](https://bones.studio/datasets). It provides motion capture data in SOMA and Unitree G1 formats with natural language descriptions, temporal segmentation labels, and detailed skeletal metadata. |
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| | | | |
| |---|---| |
| | **Total motions** | 142,220 (71,132 original + 71,088 mirrored) | |
| | **Total duration** | ~288 hours (@ 120 fps) | |
| | **Performers** | 522 actors (253 F / 269 M) | |
| | **Age range** | 17–71 years | |
| | **Height range** | 145–199 cm | |
| | **Weight range** | 38–145 kg | |
| | **Output formats** | SOMA Uniform · SOMA Proportional · Unitree G1 MuJoCo-compatible | |
| | **Annotations** | Up to 6 NL descriptions per motion + temporal segmentation + skeletal metadata | |
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| ### Relevance to SONIC |
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| BONES-SEED a large subset of SONIC training data: |
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| - **Unitree G1 joint trajectories** — retargeted for MuJoCo, directly usable for motion tracking training |
| - **Broad motion coverage** — locomotion, manipulation, dance, sports, communication, and everyday activities across 8 categories and 20 sub-categories |
| - **Rich language annotations** — up to 6 natural language descriptions per motion, enabling language-conditioned policy learning |
| - **Temporal segmentation** — per-motion phase labels with timestamps for structured skill decomposition |
| - **Performer diversity** — 522 actors spanning a wide range of body types, ages, and movement styles |
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| ### Motion Categories |
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| | Package | Motions | Description | |
| |---------------|---------|-------------------------------------------------------------------------| |
| | Locomotion | 74,488 | Walking, jogging, jumping, climbing, crawling, turning, and transitions | |
| | Communication | 21,493 | Gestures, pointing, looking, and communicative body language | |
| | Interactions | 14,643 | Object manipulation, pick-and-place, carrying, and tool use | |
| | Dances | 11,006 | Full-body dance performances across multiple styles | |
| | Gaming | 8,700 | Game-inspired actions and dynamic movements | |
| | Everyday | 5,816 | Household tasks, consuming, sitting, reading, and daily activities | |
| | Sport | 3,993 | Athletic movements and sports-specific actions | |
| | Other | 2,081 | Stunts, martial arts, and edge-case motions | |
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| ### Data Formats |
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| Every motion is available in three formats: |
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| - **SOMA Proportional (BVH)** — per-actor skeleton preserving original body proportions |
| - **SOMA Uniform (BVH)** — standardized skeleton shared across all motions for batch processing |
| - **Unitree G1 (CSV)** — joint-angle trajectories retargeted to the Unitree G1 humanoid |
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| ### Download |
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|
| ```bash |
| # Using the Hugging Face CLI |
| pip install huggingface_hub |
| huggingface-cli download bones-studio/seed --repo-type dataset --local-dir ./bones-seed |
| ``` |
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| ```python |
| # Using Python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="bones-studio/seed", |
| repo_type="dataset", |
| local_dir="./bones-seed" |
| ) |
| ``` |
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| After downloading, extract the motion archives: |
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