The following installation steps were tested with Debian 9 (stretch), Ubuntu 18.04 (Bionic Beaver) and Ubuntu 16.04 (Xenial Xerus). Please, run all commands either as root or sudoer user.
apt update && apt install -y python3 python3-gdal python3-pip python3-dev wget
pip3 install tensorflow keras sklearn
wget https://bitbucket.org/chchrsc/rios/downloads/rios-1.4.5.tar.gz && tar -xvzf rios-1.4.5.tar.gz && cd rios-1.4.5 && python3 setup.py install --prefix=/opt/rios-1.4.5 && export PATH=$PATH:/opt/rios-1.4.5/bin/ && export PYTHONPATH=/opt/rios-1.4.5/lib/python$(python3 --version | cut -c8-10)/site-packages/ && cd .. && rm -rf rios-1.4.5 rios-1.4.5.tar.gz
First, some dataset has to be grabbed for the training to work. You can download an AVIRIS example scene issuing the following command:
wget https://www.lapig.iesa.ufg.br/drive/index.php/s/IWebcJhmreFeZYP/download -O data/example_scene.tar.gz
tar -xvzf example_scene.tar.gz
Default data directory is ./data, but you can place a custom directory in the optional [data_dir].
python3 run.py train [data_dir]
python3 run.py eval [data_dir]
python3 run.py predict [data_dir]