metadata
license: other
license_name: sample-data
license_details: >-
Small demo sample for research use; source assets retain their original
licenses.
task_categories:
- video-classification
tags:
- motion-capture
- animation
- bvh
- animals
- demo
pretty_name: MoCapAnything V2 Demo Data
size_categories:
- n<1K
MoCapAnything V2 — Demo Data (sample)
The mini dataset that powers the MoCapAnything V2 demo: example input videos, per-species 1-frame reference features, character meshes with skinning for rendering, and reference outputs to compare against. Download it into ./demo/data of the code repo and the bundled examples run out of the box.
- 💻 Code: github.com/phongdaot/MocapAnything
- 🏋️ Weights: kehong/MoCapAnythingV2-weights
Contents
| Folder | What's inside |
|---|---|
inputs/ |
Example videos: in-the-wild animals, rendered zoo clips, objects, dance clips (with audio) |
zoo1030/ |
Mini animal subset: 1-frame reference features (bvh_pose/, npz_train_image_only/), reference BVHs, character meshes + skinning (characters_fix_facezplus/), reference images (front & side views) |
obj1k/ |
Mini object subset with the same layout (characters/) |
expected_results/ |
Reference *_final.mp4 outputs for the wild / zoo / obj examples — what a successful run should look like |
The reference features ship only frame 0 of each reference sequence (all the demo needs at inference — verified bit-identical to using the full features), which keeps this download small.
Usage
git clone https://github.com/phongdaot/MocapAnything.git && cd MocapAnything
hf download kehong/MoCapAnythingV2-data-sample --repo-type dataset --local-dir ./demo/data
hf download kehong/MoCapAnythingV2-weights --local-dir ./checkpoints
python inference/video2pose2rot.py --config demo/configs/demo_wild.yaml # then compare with expected_results/
python demo/app.py # interactive demo
Notes
- This is a small demo sample intended to make the code runnable end-to-end; the full training datasets are a separate (future) release.
- Wild examples whose species has no reference in this mini subset are skipped with a warning — they unlock with the full dataset.