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% S3Net: Spectral–Spatial Siamese Network for Few-Shot Hyperspectral Image Classification.
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%    This demo shows the S3Net model for hyperspectral image classification.
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%    main.py ....... A main script executing experiments upon IP, PU, and HU data sets.
%    data_read.py ....... A script implementing various data manipulation functions.
%    Function.py ....... A script implementing the precision calculation, claasificaiton map drawing, and etc.
%    model.pyd ....... A script implementing the S3Net model.
%    loss_function.py ....... A script implementing some loss functions.
%    Final_Experiment.csv ...... A csv saving the accuracy information after training
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%    /Dataset ............... The folder including data sets, we put in Salinas in it.
%    /model_results ............... The folder containing the model parameters after training.
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%   Note: Required core python libraries
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%   1. python 3.7
%   2. pytorch 1.7.1
%   3. torchvision 0.8.2

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%   Cite:
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%   [1] Z. Xue, Y. Zhou and P. Du, "S3Net: Spectral-Spatial Siamese Network for Few-Shot Hyperspectral Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, 2022, doi: 10.1109/TGRS.2022.3181501.
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%   Copyright & Disclaimer
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%
%   The programs contained in this package are granted free of charge for
%   research and education purposes only. 
%
%   Copyright (c) 2021 by Zhaohui Xue & Yiyang Zhou
%   zhaohui.xue@hhu.edu.cn & hohai_zyy@163.com
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%   For full package:
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%   https://sites.google.com/site/zhaohuixuers/