---
license: cc-by-nc-4.0
pipeline_tag: image-to-3d
base_model: yyfz233/Pi3X
tags:
- lux3d
- rust
- candle
- safetensors
- canonical-weights
- 3d
- image-to-3d
- point-cloud
- multiview
- pi3x
---

# Lux3D Pi3X Canonical Weights

This repository contains the canonicalized `safetensors` export of the Pi3X checkpoint used by the Lux3D runtime.

## Model Details

- Model family: `pi3x`
- Canonical file: `model.safetensors`
- Tensor count: `1873`
- Primary runtime target: Lux3D runtime
- Typical output: 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> pi3x
cargo run -p lux3d-cli -- run --repo-root <runtime-root> pi3x --source <input-sequence> --conditions <conditions-file> --output <output-file.ply>
cargo run -p lux3d-cli -- run --repo-root <runtime-root> pi3x --source <input-video> --vo --chunk-size 8 --overlap 4 --conf-threshold 0.05 --inject-condition pose,depth,ray --output <output-file.ply>
```

## Provenance

- Upstream source model: [`yyfz233/Pi3X`](https://huggingface.co/yyfz233/Pi3X)
- Canonicalization flow: `tools/python_baseline/normalize_weights.py`

The exact source checksum set is recorded in `manifest.json`. The integrity of the uploaded package is recorded in `checksums.json`.

## Intended Use

- Pi3X reconstruction workflows with Lux3D
- multiview point cloud generation
- VO-assisted Pi3X inference
- reproducible runtime validation

## Limitations

- Verified Lux3D runtime inference currently assumes CUDA.
- This package contains canonical runtime artifacts only.
- The upstream Pi3X weights are non-commercial.

## License

- Upstream model page: [`yyfz233/Pi3X`](https://huggingface.co/yyfz233/Pi3X)
- License file in this repository: [LICENSE](LICENSE)

Review upstream terms before redistribution or commercial use.

## Citation

```bibtex
@article{wang2025pi,
  title={$\pi^3$: 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}
}
```