Add dataset card, copyright notice, indexes and tooling

README.md

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+---
+license: other
+license_name: mixed-per-object-see-notice
+license_link: https://huggingface.co/datasets/Linzhan/Objaverse-XL-Rigged-Animated/blob/main/NOTICE.md
+pretty_name: Objaverse-XL Rigged & Animated Subset
+language:
+- en
+size_categories:
+- 1K<n<10K
+task_categories:
+- text-to-3d
+tags:
+- 3d
+- animation
+- rigging
+- skeletal-animation
+- motion
+- objaverse
+- glb
+- gltf
+configs:
+- config_name: assets
+  default: true
+  data_files: metadata.csv
+- config_name: animations
+  data_files: animations.csv
+---
+
+# Objaverse-XL Rigged & Animated Subset
+
+Every asset here carries **both a skeleton and at least one animation clip**, selected from
+[Objaverse / Objaverse-XL](https://objaverse.allenai.org/). Rigs range from 3 to 344 joints and
+span characters as well as articulated rigid objects.
+
+This is the **raw, unprocessed** Objaverse-XL source pool behind the `UniML3D` dataset used by
+**UniMate** (SIGGRAPH Asia 2026), which generates articulated motion for arbitrary skeletal
+topologies from a text prompt. UniML3D combines this pool with Truebones and Mixamo, then applies
+filtering, semantic annotation and canonicalization; none of that has been applied here, so the
+pipeline can be reproduced or replaced.
+
+| | |
+|---|---|
+| assets | 7,373 (23 GB) |
+| animation clips | 16,190 (~21.0 h) |
+| assets with both rig and animation | 7,373 (100%) |
+| single kinematic tree | 7,128 (96.7%) — 245 need pruning |
+| joints per asset | min 3 · median 44 · p95 78 · max 344 |
+| clip duration | median 2.03 s · p95 17.1 s · max 745 s |
+| near-static clips (< 0.1 s) | 803 |
+| vertices per asset | median 6,628 · p95 88,124 · max 1.52 M |
+
+## Contents
+
+```
+glb/               7,373 .glb   assets, original filenames preserved
+metadata.csv       one row per asset
+animations.csv     one row per clip
+scripts/           the glTF probe that derives both tables
+```
+
+Filenames are unchanged, so every asset maps back to its Objaverse entry:
+
+| pattern | count | meaning |
+|---|---|---|
+| `<24-hex>_{fbx,glb,gltf}.glb` | 5,305 | Objaverse-XL (GitHub); suffix is the original format |
+| `<32-hex>.glb` | 2,068 | Objaverse 1.0 / Sketchfab UID |
+
+## metadata.csv
+
+One row per asset, joined to `animations.csv` on `file`.
+
+| column | meaning |
+|---|---|
+| `file` | path, e.g. `glb/00064e6f….glb` |
+| `object_id`, `id_family` | Objaverse id and which family it came from |
+| `source_format` | original format before GLB conversion; empty for Sketchfab |
+| `num_vertices`, `num_meshes`, `num_nodes` | geometry size |
+| `num_skins`, `num_joints` | rig size |
+| `num_skeleton_roots`, `single_tree` | number of kinematic trees; `single_tree` is `false` when the asset needs single-tree pruning |
+| `num_animations`, `total_duration_sec`, `max_keyframes` | animation budget |
+| `animated_joints` | joints driven by at least one clip |
+| `generator` | exporter string (`Sketchfab-*`, `Khronos glTF Blender I/O *`, …) |
+
+## animations.csv
+
+One row per animation, since motion datasets are counted in sequences rather than assets:
+`file`, `object_id`, `clip_index`, `clip_name`, `duration_sec`, `keyframes`, `num_channels`,
+`animated_nodes`, `animated_joints`, `drives_skeleton`.
+
+`drives_skeleton` is the useful filter: **5,615 of 16,190 clips animate only non-joint nodes**
+(object-level transforms rather than a character rig). Every asset has at least one clip that
+does drive its skeleton.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+assets = load_dataset("Linzhan/Objaverse-XL-Rigged-Animated", "assets", split="train")
+clips  = load_dataset("Linzhan/Objaverse-XL-Rigged-Animated", "animations", split="train")
+
+# assets needing no single-tree pruning, with a humanoid-scale rig
+clean = assets.filter(lambda r: r["single_tree"] == "true" and 20 <= r["num_joints"] <= 100)
+
+# clips that drive a skeleton and are not near-static
+usable = clips.filter(lambda r: r["drives_skeleton"] == "true" and r["duration_sec"] >= 0.5)
+```
+
+Both tables are derived from each file's glTF JSON chunk by `scripts/build_dataset.py`, so they
+can be regenerated or extended without re-downloading anything.
+
+## Licensing and attribution
+
+The assets in `glb/` were created by third parties and **retain their individual upstream
+licences**, which are heterogeneous: various Creative Commons terms for Sketchfab objects, and
+whatever applies to the GitHub-sourced ones. No blanket licence covers the collection and none is
+asserted here — publishing them is not a licence grant. Resolve the licence for a given
+`object_id` through the Objaverse-XL annotations before using or redistributing an asset.
+
+The derived material — `metadata.csv`, `animations.csv`, `scripts/` and this card — is offered
+under **ODC-BY 1.0**, matching the upstream Objaverse metadata.
+
+Rights holders who want an asset removed can open an issue on this repository; see
+[`NOTICE.md`](NOTICE.md) for the full statement and the takedown process.
+
+## Citation
+
+```bibtex
+@inproceedings{mou2026unimate,
+  title     = {UniMate: Topology-Aware Motion Generation for Arbitrary Skeletons},
+  author    = {Mou, Linzhan},
+  booktitle = {SIGGRAPH Asia 2026 Conference Papers},
+  year      = {2026}
+}
+
+@inproceedings{deitke2023objaversexl,
+  title     = {Objaverse-XL: A Universe of 10M+ 3D Objects},
+  author    = {Deitke, Matt and Liu, Ruoshi and Wallingford, Matthew and others},
+  booktitle = {Advances in Neural Information Processing Systems},
+  pages     = {35799--35813},
+  year      = {2023}
+}
+```