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name: retargeting-and-motion-data description: "Prepare ProtoMotions MotionLib data, conversion pipelines, PyRoki retargeting, contact labels, FPS handling, and motion utility checks." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

ProtoMotions retargeting and motion data

Use this sub-skill for MotionLib schemas, AMASS/PHUMA/SEED/Kimodo data preparation, SMPL/SOMA/G1/H1 retargeting, PyRoki pipeline reasoning, contact-label handling, FPS/downsampling, motion filtering, and packaged-motion utilities.

Read first

• references/motion-data-formats.md: .motion, MotionLib .pt, YAML lists, contacts, FPS, and body alignment.
• references/retargeting-pipeline.md: SMPL/SOMA keypoint extraction, PyRoki retargeting, contacts, conversion, and packaging sequence.
• references/conversion-utilities.md: useful conversion/helper surfaces and when to run or skip them.
• references/troubleshooting.md: data, contact, filter, and environment failures.
• scripts/subset_motion_lib.py: CPU utility to sample every Nth motion from a packaged MotionLib.
• scripts/summarize_motion_lib.py: safe MotionLib .pt structure summary.

Decision flow

1. Identify source skeleton/data: AMASS SMPL, SMPL-X, SOMA, PHUMA, SEED G1 CSV, Kimodo-generated CSV/NPZ, or already packaged MotionLib.
2. Confirm target robot/skeleton: smpl, soma23, g1, or h1_2 are the main evidence-backed routes.
3. For robot retargeting, use separate ProtoMotions and PyRoki environments.
4. Preserve source motion contacts when retargeting whenever the pipeline provides them; re-computing contacts from imperfect retargeted output can be less reliable.
5. Package final .motion files into a MotionLib .pt before training.
6. Start with a small subset (skip_freq or subset_motion_lib.py) before full AMASS/SEED scale.

Safe utilities

python scripts/summarize_motion_lib.py <motion_lib.pt>
python scripts/subset_motion_lib.py <input.pt> <output.pt> --sample-every 200

These helpers operate on local .pt files and do not require simulator execution.

Retargeting cautions

• PyRoki optimizes trajectories and may require CUDA/JAX dependencies separate from ProtoMotions.
• The full AMASS-to-robot pipeline can be long and data-heavy; use skip/subset parameters for smoke tests.
• Contact labels must match motion length after FPS downsampling.
• Motion filters can drop invalid outputs; inspect thresholds before assuming conversion failed.
• If working from a package-only install, require user-provided conversion scripts or a source checkout because some data-prep scripts are not part of the installed package.