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| title: Thera Arbitrary-Scale Super-Resolution | |
| emoji: π₯ | |
| colorFrom: red | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 4.44.1 | |
| app_file: app.py | |
| pinned: false | |
| # Thera Arbitrary-Scale Super-Resolution | |
| This is an interactive demo for our paper "Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields | |
| " [(arXiV link)](https://arxiv.org/pdf/2311.17643) [(code link)](https://github.com/prs-eth/thera). | |
| ## Run locally | |
| If you want to run the demo locally, 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 | |
| ``` | |
| Then, start the Gradio server like this: | |
| ```bash | |
| > python app.py | |
| ``` | |
| The server should bind to port `7860` by default. | |
| ## 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 π: | |
| ``` | |
| @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} | |
| } | |
| ``` |