Lightweight Stepless Super-Resolution of Remote Sensing Images via Saliency-Aware Dynamic Routing Strategy

by Hanlin Wu, Ning Ni, and Libao Zhang, details are in paper.

Usage

Clone the repository:

git clone https://github.com/hanlinwu/SalDRN.git

Requirements:

• pytorch==1.10.0
• pytorch-lightning==1.5.5
• numpy
• opencv-python
• easydict
• tqdm

Train:

1. Download the training datset from this url.
2. Unzip the downloaded dataset, and put the files on path: load/SalCSSR-339
3. Change the hr_path and sal_path in config/your_config_file.yaml
4. Do training:

   python train.py --config config/your_config_file.yaml
   

Test:

1. Unzip the benchmark dataset, and put the files on path: load/benchmark

python test.py --checkpoint logs/your_checkpoint_path