SSRNO

This repository contains the official implementation for Scalable Super Resolution Neural Operator in ACM MM 2024.

Installation

1. Install requirements from conda

   conda env create -f requirements.yml

2. Clone the repo

   git clone https://github.com/ZXS-Labs/SSRNO.git

3. Install the modified TorchIntegral

   pip install ./_TO

4. [optional] Install Inplace_Gelu from Tempo

    git clone https://github.com/UofT-EcoSystem/Tempo.git
    cd Tempo
    python setup.py install

Quick start

Download the pretrained model from here.

Link your data folder(s) to ./data/ and change the root_path in yaml.

#training
python inn_attention_train.py \
    --config ./configs/train_ssrno.yaml

#testing
python inn_attention_test.py \
    --config ./configs/test_ssrno.yaml \
    --model "the model pth" \
    --mcell True

Citation

If you find our work useful in your research, please consider citing:

@inproceedings{
    han2024scalable,
    title={Scalable Super-Resolution Neural Operator},
    author={Lei Han and Xuesong Zhang},
    booktitle={ACM Multimedia 2024},
    year={2024},
    url={https://openreview.net/forum?id=COlygxQAV9}
}

Acknowledgements

This code is built on TorchIntegral ,Tempo and SRNO.