NLSAN

Non-Local Self-Attention Network for Image Super-Resolution

Environment

• PyTorch >= 1.7
• BasicSR == 1.3.4.9

Installation

pip install -r requirements.txt
python setup.py develop

How To Test

• Refer to ./options/test for the configuration file of the model to be tested, and prepare the testing data and pretrained model.
• The pretrained models are available at Google Drive and Baidu Netdisk (access code: gykc).

sh demo.sh

The testing results will be saved in the ./results folder.

Acknowledgements

This code is built on BasicSR and HAT. We thank the authors for sharing their codes.