Learning Dynamic Scale Awareness and Global Implicit Functions for Continuous-Scale Super-Resolution of Remote Sensing Images
by Hanlin Wu, Ning Ni, and Libao Zhang, details are in paper.
https://github.com/hanlinwu/SADN.git
- pytorch==1.10.0
- pytorch-lightning==1.5.5
- numpy
- opencv-python
- easydict
- tqdm
- Download training datset from this url.
- Change the
train.datapath
andvalid.data_path
inconfig/your_config_file.yaml
- Do training:
python train.py --config config/your_config_file.yaml
-
Download benchmark datasets Set14,B100,Urban100,Manga109, and put them on path:
load/benchmark/datset_name
-
test without self-ensemble
python test.py --checkpoint your_checkpoint_path --datasets Set14,B100,Urban100 --scales 2,3,4
-
test with self-ensemble
python test.py --checkpoint your_checkpoint_path --datasets Set14,B100,Urban100 --scales 2,3,4 --self_ensemble