Skip to content
/ RRCGAN Public

RRCGAN:A Radiometric Resolution Compression Method for Optical Remote Sensing Images Using Contrastive Learning

Notifications You must be signed in to change notification settings

ZzzTD/RRCGAN

Repository files navigation

RRCGAN:A Radiometric Resolution Compression Method for Optical Remote Sensing Images Using Contrastive Learning

rrcgan

Prerequisites

  • Linux or macOS
  • Python 3
  • CPU or NVIDIA GPU + CUDA CuDNN

Update log

  • 5/5/2024: Added related codes.
  • 12/24/2024: Added GF2 dataset.

RRCGAN Train and Test

  • Train the RRCGAN model:
python train.py --dataroot XXX --name XXX
  • Test the RRCGAN model:
python test.py --dataroot XXX --name XXX

Datesets

All the data mentioned in the article, eg. JL1,GF7,GF2, has been uploaded to Baidu Cloud, link is: https://pan.baidu.com/s/1VOeaoqv50KVqbpiXJs5WwQ(thkn) .The dataset example is as follows: 新建 Microsoft Visio Drawing

Acknowledgments

Our code is developed based on contrastive-unpaired-translation and Hneg_SRC . We also thank pytorch-fid for FID computation.

About

RRCGAN:A Radiometric Resolution Compression Method for Optical Remote Sensing Images Using Contrastive Learning

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages