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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