• Here I provide Tensorflow implementations for GAL, BGAC, and GAC.

• I was inspired to an extent by the two nice repositories
  https://github.com/KonstantinosF/Classification-of-Hyperspectral-Image
  and https://github.com/zhenxuan00/graphical-gan.
  I feel grateful to the authors for providing them.

CentOS Linux release 7.2.1511 (Core)
Tesla K80 Graphic Processing Units
python 2.7.15
TensorFlow 1.14.0

• Download hyperspectral data and add them to ./dataset.
  
• All the hyperparameters are in ./tflib/config.py.
  Set them to what you want when running a code.
  
• Run
  python GAL.py -GPU 0
  to see GAL in the local mode on the Salinas dataset.

@ARTICLE{Wang20GAL,
author={G. {Wang} and P. {Ren}},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title={Delving into Classifying Hyperspectral Images via Graphical Adversarial Learning},
year={2020},
volume={13},
number={},
pages={2019-2031}
}