Installation with docker

Prerequisites
Linux machine (most common distributions are supported)
Recent NVIDIA GPU (compute capability >=3)
​NVIDIA driver >= 418.81.07
​Docker version >= 19.03
Setup
Install NVIDIA Container Toolkit
Full instructions are here, but e.g. for Ubuntu:
Setup repository and GPG key:
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
   
Install NVIDIA docker package:
sudo apt-get update
sudo apt-get install -y nvidia-docker2
Restart docker daemon:
sudo systemctl restart docker
Running cellfinder
To run with GPU support, and mount the current working directory at /data:
docker container run --mount type=bind,source=${PWD},target=/data --gpus all -it ghcr.io/brainglobe/cellfinder
This will open up a bash prompt, and you can use cellfinder (or brainreg etc.) to analyse your data (mounted at /data) as normal, e.g.:
cellfinder -s /data/brain1/channel0 -b /data/brain1/channel1 -v 5 2 2 --orientation psl -o /data/analysis/brain1 --trained-model /data/models/retrained.h5
To leave the docker container when done, just exit.The data will be saved onto the host system, at your current working directory (you can mount different directories, or multiple directories, see the docker documentation).

Last modified 1yr ago