Requirements：

numpy >= 1.16.5
PyTorch >= 1.3.1
sklearn >= 0.20.4

Datasets:

You can download the hyperspectral datasets in mat format at: http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes, and move the files to ./datasets folder.

Usage:

1. Set the percentage of training and validation samples by the load_dataset function in the file ./global_module/generate_pic.py.
2. Taking the DBDA framework as an example, run ./DBDA/main.py and type the name of dataset.
3. The classfication maps are obtained in ./DBDA/classification_maps folder, and accuracy result is generated in ./DBDA/records folder.