diff --git a/README.md b/README.md index 2fc9a1b13dc3134be78689ee0d5efd3663dfa88c..55f8ef4a7d774f496205534a9d4f62e1ab6c4db0 100644 --- a/README.md +++ b/README.md @@ -31,8 +31,16 @@ We will be using the CUDAs available from the server mathgpu1, provided by Uni-H # clone project git clone https://gitlab.rrz.uni-hamburg.de/BAT9096/deepinverse.git -# install project -Not yet ready. +# requirements +install conda environment with python=3.6, +install astra-toolbox stable version(```conda install -c astra-toolbox astra-toolbox```) +``` +conda install pytorch torchvision cudatoolkit=9.0 -c pytorch +conda install dival +``` + +Make sure to integrate it to the Jupyter kernel. + # run module (example: mnist as your main contribution) We will using the data provided by zonodo.org. LoDoPaB-CT Dataset.