| --- |
| license: bsd-2-clause |
| pipeline_tag: image-to-3d |
| base_model: yyfz233/Pi3 |
| tags: |
| - lux3d |
| - rust |
| - candle |
| - safetensors |
| - canonical-weights |
| - 3d |
| - image-to-3d |
| - point-cloud |
| - pi3 |
| --- |
| |
| # Lux3D Pi3 Canonical Weights |
|
|
| This repository contains the canonicalized `safetensors` export of the Pi3 checkpoint used by the Lux3D runtime. |
|
|
| ## Model Details |
|
|
| - Model family: `pi3` |
| - Canonical file: `model.safetensors` |
| - Tensor count: `1210` |
| - Primary runtime target: Lux3D runtime |
| - Typical output: affine-invariant point cloud export (`.ply`) |
|
|
| ## Included Files |
|
|
| - `model.safetensors` |
| - `resolved_config.json` |
| - `manifest.json` |
| - `checksums.json` |
|
|
| ## Usage With Lux3D |
|
|
| The Lux3D CLI can validate and use the package once it is installed into your local model asset layout. |
|
|
| ```powershell |
| cargo run -p lux3d-cli -- inspect --repo-root <runtime-root> pi3 |
| cargo run -p lux3d-cli -- run --repo-root <runtime-root> pi3 --source <input-sequence> --output <output-file.ply> |
| ``` |
|
|
| ## Provenance |
|
|
| - Upstream source model: [`yyfz233/Pi3`](https://huggingface.co/yyfz233/Pi3) |
| - Canonicalization flow: `tools/python_baseline/normalize_weights.py` |
|
|
| The exact source checksum and canonical checksum set are recorded in `manifest.json` and `checksums.json`. |
|
|
| ## Intended Use |
|
|
| - image or video to 3D reconstruction with Lux3D |
| - point cloud export workflows based on the Pi3 contract |
| - reproducible runtime validation |
|
|
| ## Limitations |
|
|
| - Verified Lux3D runtime inference currently assumes CUDA. |
| - This package is for the base `pi3` family, not `pi3x`. |
| - The repository contains canonicalized runtime artifacts, not the full upstream training or demo stack. |
|
|
| ## License |
|
|
| - Upstream model page: [`yyfz233/Pi3`](https://huggingface.co/yyfz233/Pi3) |
| - License file in this repository: [LICENSE](LICENSE) |
|
|
| Review upstream terms before redistribution or commercial use. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{wang2025pi, |
| title={$\pi^3$: Scalable Permutation-Equivariant Visual Geometry Learning}, |
| author={Wang, Yifan and Zhou, Jianjun and Zhu, Haoyi and Chang, Wenzheng and Zhou, Yang and Li, Zizun and Chen, Junyi and Pang, Jiangmiao and Shen, Chunhua and He, Tong}, |
| journal={arXiv preprint arXiv:2507.13347}, |
| year={2025} |
| } |
| ``` |
|
|
