First, download and checkout the latest release
# from a directory of your choice
git clone https://github.com/weberlab-hhu/Helixer.git
cd Helixer
# git checkout dev # v0.2.0
Ubuntu (& co.)
sudo apt install python3-dev
Fedora (& co.)
sudo dnf install python3-devel
We recommend installing all the python packages in a virtual environment: https://docs.python-guide.org/dev/virtualenvs/
For example, create and activate an environment called 'env':
python3 -m venv env
source env/bin/activate
The steps below assume you are working in the same environment.
And to run on a GPU (highly recommended for realistically sized datasets), everything for tensorflow-gpu is required, see: https://www.tensorflow.org/install/gpu
The following has been most recently tested.
python packages:
- tensorflow-gpu==2.7.0
system packages:
- cuda-11-2
- libcudnn8
- libcudnn8-dev
- nvidia-driver-495
A GPU with 11GB Memory (e.g. GTX 1080 Ti) can run the largest configurations described below, for smaller GPUs you might have to reduce the network or batch size.
https://github.com/TonyBolger/HelixerPost
Setup according to included instructions and
further add the compiled helixer_post_bin
to
your system PATH.
# from the Helixer directory
pip install -r requirements.txt
# from the Helixer directory
pip install . # or `pip install -e .`, if you will be changing the code