https://github.com/prs-eth/thera
Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields
https://github.com/prs-eth/thera
Last synced: about 1 year ago
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Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields
- Host: GitHub
- URL: https://github.com/prs-eth/thera
- Owner: prs-eth
- License: apache-2.0
- Created: 2023-12-28T11:27:48.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-04-01T08:09:06.000Z (over 1 year ago)
- Last Synced: 2025-04-01T09:24:11.344Z (over 1 year ago)
- Language: Python
- Homepage: https://therasr.github.io
- Size: 1.26 MB
- Stars: 718
- Watchers: 10
- Forks: 49
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields
**Alexander Becker❄️🔥, Rodrigo Daudt❄️🔥, Dominik Narnhofer🔥, Torben Peters🔥, Nando Metzger🔥, Jan Dirk Wegner🌶️, Konrad Schindler🔥**
❄️ Equal contribution
🔥 Photogrammetry and Remote Sensing, ETH Zurich
🌶️ Department of Mathematical Modeling and Machine Learning, University of Zurich
[](https://arxiv.org/abs/2311.17643)
[](https://therasr.github.io)
[](https://huggingface.co/spaces/prs-eth/thera)
[](https://www.apache.org/licenses/LICENSE-2.0)
Thera is the first arbitrary-scale super-resolution method with a built-in physical observation model.
## News
**2025-03-15**: We are #1 on Hacker News 🎉
**2025-03-14**: Interactive Hugging Face Space is online
**2025-03-12**: Pre-trained checkpoints are released
## Setup environment
You need a Python 3.10 environment (e.g., installed via conda) on Linux as well as an NVIDIA GPU. Then install packages via pip:
```bash
> pip install --upgrade pip
> pip install -r requirements.txt
```
## Use with pre-trained models
Download checkpoints:
Backbone
Variant
Download
EDSR-baseline
Air
🤗 Hugging Face | Google Drive
Plus
🤗 Hugging Face | Google Drive
Pro
🤗 Hugging Face | Google Drive
RDN
Air
🤗 Hugging Face | Google Drive
Plus
🤗 Hugging Face | Google Drive
Pro
🤗 Hugging Face | Google Drive
Super-resolve any image with:
```bash
> ./super_resolve.py IN_FILE OUT_FILE --scale 3.14 --checkpoint thera-rdn-pro.pkl
```
You can evaluate the models on datasets using the `run_eval.py` script, e.g.:
```bash
> python run_eval.py --checkpoint thera-rdn-pro.pkl --data-dir path_to_data_parent_folder --eval-sets data_folder_1 data_folder_2 ...
```
You can run `python run_eval.py -h` to display all testing options.
## Use with interactive Gradio app
You can also host a local version of our [Hugging Face demo](https://huggingface.co/spaces/prs-eth/thera). To do so, clone the dedicated demo repo:
```bash
> git clone https://huggingface.co/spaces/prs-eth/thera thera-demo
```
Instructions for running the demo locally can be found in [the repo's README.md](https://huggingface.co/spaces/prs-eth/thera/blob/main/README.md).
## Training
> Training code will be released soon.
## Useful XLA flags
* Disable pre-allocation of entire VRAM: `XLA_PYTHON_CLIENT_PREALLOCATE=false`
* Disable jitting for debugging: `JAX_DISABLE_JIT=1`
## Citation
If you found our work helpful, consider citing our paper 😊:
```
@article{becker2025thera,
title={Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields},
author={Becker, Alexander and Daudt, Rodrigo Caye and Narnhofer, Dominik and Peters, Torben and Metzger, Nando and Wegner, Jan Dirk and Schindler, Konrad},
journal={arXiv preprint arXiv:2311.17643},
year={2025}
}
```