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Follow the instruction in https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html for downloading and installing Miniconda
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Open a terminal in the code directory
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Create an environment using the .yml file:
conda env create -f deepsatmodels_env.yml
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Activate the environment:
source activate deepsatmodels
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Install required version of torch:
conda install pytorch torchvision torchaudio cudatoolkit=10.1 -c pytorch-nightly
- Add the base directory and paths to train and evaluation path files in "data/datasets.yaml".
- For each experiment we use a separate ".yaml" configuration file. Examples files are provided in "configs". The default values filled in these files correspond to parameters used in the experiments presented in respective studies.
- Modify .yaml config files accordingly to train with your own data.