Skip to content

Installation

Installing from scratch

The following command will create a new environment called easymode and install easymode and all dependencies into it.

conda create -n easymode python=3.9 cudatoolkit=11.8 pip -c conda-forge -y && \
conda activate easymode && \
pip install tensorflow==2.8.0 easymode
Should that fail and if you have a CUDA 11.8 module available on your cluster, try:
conda create -n easymode python=3.9
conda activate easymode
pip install tensorflow==2.8.0 easymode

Installing into existing environments

WarpTools

WarpTools and easymode share the same CUDA and Python versions.

conda activate warp
pip install easymode

Membrain-seg

Membrain and easymode share the same Python version.

conda activate membrain
pip install easymode 

Ais

easymode was built on Ais, so if you have a working Ais environment, easymode should work fine in there as well.

conda activate ais
pip install easymode

Environment settings

AreTomo3

In case you want to use easymode reconstruct, you need to set the path to the AreTomo3 binary and define the required AreTomo3 environment initialization command. For example:

easymode set --aretomo3-path /public/EM/AreTomo/AreTomo3 --aretomo3-env "module load AreTomo/3.1.0"

Cache directory

When using easymode segment <feature> for the first time, the required model weights will be downloaded and saved to a local cache directory (~500 MB per model). The default location is ~/easymode/, but you can change it (for example if you want a central cache for all your users) as follows:

easymode set --cache-directory /public/easymode/cache/