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Installation

Setting up a software environment is a painful experience. Thunderseg provides several methods to get the environment ready.

The installation process will take roughly 5-10 minutes and may vary depends on the network condition and computer resource.

Via Conda

Don't know how to install Conda?

Check Miniconda install guide

OR

Simply do 
  mkdir -p ~/miniconda3
  wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
  bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
  rm ~/miniconda3/miniconda.sh

conda env create -f https://raw.githubusercontent.com/jldz9/thunderseg/refs/heads/master/environment.yml
pip install thunderseg

Via Container

Don't know how to install Docker?

Check Docker install guide

Warning

If you want to activate GPU processing while using docker, using NVIDIA GPUs with CUDA support is necessary.

Additionally, you will need to install NVIDIA Container Toolkit

> Use dockerfile

wget https://raw.githubusercontent.com/jldz9/thunderseg/refs/heads/master/.devcontainer/Dockerfile 
docker build -t thunderseg:1.0.0.dev25 .
After running above code block, you should be able to find image in docker desktop image tab docker image docker image or in command line: 
user:~$ docker images
REPOSITORY   TAG       IMAGE ID       CREATED             SIZE
thunderseg   1.0.0.dev25     ba968b128eda   About an hour ago   20.5GB

> Use image from Docker Hub

docker pull jldz9/thunderseg:1.0.0.dev25

> Use apptainer

Don't know how to install Apptainer?

Check Apptainer install guide

Apptainer is a docker alternative in order to run images on HPC environment, normally you don't need to install it locally.

You can load apptainer by using module load apptainer under HPC environment that runs SLURM workload manager

To pull image from docker hub using apptainer: 

apptainer pull thunderseg_100dev.sif docker://jldz9/thunderseg:1.0.0.dev25

Via Source code

If you would like to contribute to this project, thanks in advance! 😄

You can pull the source code from GitHub by: 

git clone https://github.com/jldz9/thunderseg.git
and then set up the environment by: 
conda env create -f thunderseg/environment.yml
we also provide devcontainer.json for vscode under .devcontainer directory