Network

Attention in Attention Network for Image Super-Resolution

A2N

This repository is an PyTorch implementation of the paper

“Attention in Attention Network for Image Super-Resolution” [arXiv]

Visual results in the paper are availble at Google Drive or Baidu Netdisk (password: 7t74).

Unofficial TensorFlow implementation: https://github.com/Anuj040/superres

Test

Dependecies: PyTorch==0.4.1 (Will be updated to support PyTorch>1.0 in the future)

You can download the test sets from Google Drive. Put the test data in ../Data/benchmark/.

python main.py  --scale 4 --data_test Set5 --pre_train ./experiment/model/aan_x4.pt --chop --test_only

If you use CPU, please add “–cpu”.

Train

Training data preparation

  1. Download DIV2K training data from DIV2K dataset or SNU_CVLab.
  2. Specify '--dir_data' in option.py based on the data path.

For more informaiton, please refer to EDSR(PyTorch).

Training

# SR x2

python main.py


 


 




 


To finish reading, please visit source site