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INSTALL.md

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Installation and credentials

Here we present two ways how to install the packages.

  • A) requires GDAL to be installed on the system first.
  • B) GDAL is installed with mamba/conda in the environment.

A) With pip in a virtual environment

  1. Install GDAL. For Ubuntu follow e.g. these instructions.
  2. Create a new virtual environment called gchm by running: python -m venv $HOME/venvs/gchm
  3. Activate the environment:source $HOME/venvs/gchm/bin/activate. (Check that python points to the new environment with which python3.)
  4. Install pytorch by following the instructions on pytorch.org that match your versions. Run e.g. python3 -m pip install torch torchvision torchaudio
  5. Install the GDAL python API matching the installed GDAL version: python3 -m pip install GDAL==3.5.3
  6. Install all other required packages: python3 -m pip install -r requirements.txt
  7. Install this project as an editable package called gchm. Make sure you are in the directory of the repository containing the file setup.py . Run: python3 -m pip install -e . (Note the dot . at the end.)

B) Mamba/conda installation

  1. Install mambaforge: https://github.com/conda-forge/miniforge#mambaforge
  2. Create a new environment called gchm with pytorch (or follow the instructions on pytorch.org): mamba create -n gchm python=3.10.9 pytorch torchvision torchaudio cudatoolkit=11.8 -c pytorch -c nvidia
  3. Activate the environment: mamba activate gchm. (Check that python points to the new environment: E.g. which python should print something like: ~/mambaforge/envs/gchm/bin/python)
  4. Install gdal: mamba install -c conda-forge gdal=3.6.2
  5. Install pytables: mamba install -c anaconda pytables=3.7.0
  6. Install all other required packages from conda-forge using the environment.yml file. Change directory to the repository and run: mamba env update -f environment.yml
  7. Install this project as an editable package called gchm. Make sure you are in the directory of the repository containing the file setup.py . Run: pip install -e . (Note the dot . at the end.)

Credentials for wandb

Optional. Only needed to run the training code (Not needed for deployment). Create a file called ~/.config_wandb containing your weights and biases API key:

export WANDB_API_KEY=YOUR_API_KEY

Credentials for AWS

Optional. This is only needed to download Sentinel-2 images from AWS on the fly using gchm/deploy.py. Note that there are costs per GB downloaded!

Create a file ~/.aws_configs containing your AWS credentials as environment variables.

export AWS_ACCESS_KEY_ID=PUT_YOUR_KEY_ID_HERE
export AWS_SECRET_ACCESS_KEY=PUT_YOUR_SECRET_ACCESS_KEY_HERE
export AWS_REQUEST_PAYER=requester

To create an AWS account go to: https://aws.amazon.com/console/