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license: apache-2.0
library_name: onnx
tags:
- onnx
- depth-estimation
- image-matting
- inpainting
- android
---
# Parallax Wallpaper Studio models
ONNX exports of three open models, made to run on the phone's CPU (ONNX Runtime) inside the Android app
Parallax Wallpaper Studio. The app downloads them on demand: the depth model for depth-based parallax, and all
three for "Split into layers", which turns one photo into a layered wallpaper.
| File | Model | Used for | Licence |
|---|---|---|---|
| `depth-anything-v2-small-int8.onnx` | [Depth Anything V2 Small](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf), int8 dynamic quantisation | Depth map | Apache-2.0 |
| `vitmatte-small-512-fp16w.onnx` | [ViTMatte Small (Composition-1k)](https://huggingface.co/hustvl/vitmatte-small-composition-1k), fixed 512×512 input, fp16 weights | Refining layer edges | Apache-2.0 |
| `big-lama-512-fp16w.onnx` | [LaMa](https://github.com/advimman/lama) (big-lama), fixed 512×512 input, fp16 weights | Filling the holes behind cut-out layers | Apache-2.0 |
Notes on the exports:
- The depth model matches the full-precision model to 0.9998 correlation.
- LaMa's FFTs have no ONNX export, so they are rewritten as constant DFT matrix multiplications. That fixes the
input size at 512×512.
- "fp16 weights" means the weights are stored as float16 and the maths runs in float32.
## Credits
- **Depth Anything V2**: Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao.
*Depth Anything V2*, 2024. Only the Small model is Apache-2.0; Base and Large are not, and are not used here.
- **ViTMatte**: Jingfeng Yao, Xinggang Wang, Shusheng Yang, Baoyuan Wang. *ViTMatte: Boosting Image Matting with
Pretrained Plain Vision Transformers*, 2023 (hustvl).
- **LaMa**: Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei
Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky. *Resolution-robust Large Mask Inpainting
with Fourier Convolutions*, WACV 2022 (Samsung AI Center).
These are format conversions of the original weights. The licences and copyright of the original works apply.
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