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--- |
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title: Thera Arbitrary-Scale Super-Resolution |
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emoji: 🔥 |
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colorFrom: red |
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colorTo: green |
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sdk: gradio |
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sdk_version: 4.44.1 |
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app_file: app.py |
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pinned: false |
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--- |
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# Thera Arbitrary-Scale Super-Resolution |
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This is an interactive demo for our paper "Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields |
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" [(arXiV link)](https://arxiv.org/pdf/2311.17643) [(code link)](https://github.com/prs-eth/thera). |
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## Run locally |
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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: |
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```bash |
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> pip install --upgrade pip |
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> pip install -r requirements.txt |
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``` |
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Then, start the Gradio server like this: |
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```bash |
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> python app.py |
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``` |
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The server should bind to port `7860` by default. |
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## Useful XLA flags |
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* Disable pre-allocation of entire VRAM: `XLA_PYTHON_CLIENT_PREALLOCATE=false` |
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* Disable jitting for debugging: `JAX_DISABLE_JIT=1` |
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## Citation |
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If you found our work helpful, consider citing our paper 😊: |
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``` |
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@article{becker2025thera, |
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title={Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields}, |
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author={Becker, Alexander and Daudt, Rodrigo Caye and Narnhofer, Dominik and Peters, Torben and Metzger, Nando and Wegner, Jan Dirk and Schindler, Konrad}, |
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journal={arXiv preprint arXiv:2311.17643}, |
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year={2025} |
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} |
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``` |