---
license: apache-2.0
tags:
- image-super-resolution
- image-to-image
- mlx
- apple-silicon
- super-resolution
- neural-heat-fields
base_model:
- prs-eth/thera-rdn-air
- prs-eth/thera-rdn-pro
library_name: mlx
language:
- en
pipeline_tag: image-to-image
---
# ✨ thera-mlx
**Aliasing-Free Arbitrary-Scale Super-Resolution for Apple Silicon**
*An [MLX](https://github.com/ml-explore/mlx) port of [Thera](https://therasr.github.io) — running natively on M1/M2/M3/M4*
[](https://github.com/madeleinelmuller/thera-mlx)
[](https://github.com/madeleinelmuller/thera-mlx/blob/main/LICENSE)
[](https://arxiv.org/abs/2311.17643)
**128×128 → 512×512 in ~1.5 seconds on M1** · Arbitrary scale factors · Web UI + CLI · Video support
---
## Model Description
**thera-mlx** contains MLX-format weights for the [Thera](https://therasr.github.io) super-resolution model, converted from the original JAX/Flax checkpoints released by [PRS-ETH](https://prs.igp.ethz.ch/) (ETH Zurich).
Thera uses **neural heat fields** to perform aliasing-free image super-resolution at *any* scale factor — not just 2× or 4×. This repo provides two variants:
| File | Model | Speed | Quality |
|------|-------|-------|---------|
| `weights-air.safetensors` | Air | ~1.5s for 128→512px on M1 | Great |
| `weights-pro.safetensors` | Pro (+ SwinIR refinement) | ~5s for 128→512px on M1 | Best |
## Usage
```bash
git clone https://github.com/madeleinelmuller/thera-mlx
cd thera-mlx
pip install -r requirements.txt
# Download weights (pulls from this repo automatically)
python run.py convert --model air
python run.py convert --model pro
# Launch web UI
python run.py
# Or use CLI
python run.py run input.png output.png --scale 4 --model air
```
See the full [GitHub repository](https://github.com/madeleinelmuller/thera-mlx) for complete documentation.
## Original Weights
The weights in this repository are converted from:
- [`prs-eth/thera-rdn-air`](https://huggingface.co/prs-eth/thera-rdn-air)
- [`prs-eth/thera-rdn-pro`](https://huggingface.co/prs-eth/thera-rdn-pro)
## Citation
If you use this in your work, please cite the original Thera paper:
```bibtex
@article{becker2023thera,
title = {Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields},
author = {Becker, Alexander and Caye Daudt, Rodrigo and Narnhofer, Dominik and
Peters, Torben and Metzger, Nando and Wegner, Jan Dirk and Schindler, Konrad},
journal = {arXiv preprint arXiv:2311.17643},
year = {2023}
}
```
**Original resources:**
- Paper: [arxiv.org/abs/2311.17643](https://arxiv.org/abs/2311.17643)
- Project page: [therasr.github.io](https://therasr.github.io)
- Original HF weights: [huggingface.co/prs-eth](https://huggingface.co/prs-eth)