Requirements#

cellfinder should run on most machines, but for routine use on large datasets, you will need a fairly high-powered computer (see the guide to Speeding up cellfinder for details).

Using an NVIDIA GPU will speed up cell classification considerably. See setting up your GPU for details.

cellfinder uses brainreg for atlas registration, and the hardware requirements for brainreg depend on the atlas (and in particular, the resolution) you want to use. Most machines (including laptops) will be able to use most of the atlases, but some atlases (such as the 10μm mouse atlases) may need up to 50GB of RAM.

Installation#

Installing the napari plugin

Installing the cellfinder-core Python package

Installing Python

Your machine may already have Python installed, but we recommend installing miniconda. See Using conda for details.

Installing cellfinder

Hint

Remember to activate your conda environment before doing anything

pip install cellfinder-core

Installing the command line tool

Hint

If you know what you’re doing (and your GPU is set up), just run pip install cellfinder

Installing Python

cellfinder is written in Python, and so needs a functional Python installation. Your machine may already have Python installed, but we recommend installing miniconda. See Using conda for details.

Caution

cellfinder should run on any type of Python installation, but if you don’t use conda, we may be limited in the support we can offer.

Installing cellfinder

Hint

Remember to activate your conda environment before doing anything

Using pip

pip install cellfinder[napari]

To only install the command line tool with no GUI (e.g., to run cellfinder on an HPC cluster), just run:

pip install cellfinder

Installing the command line tool using docker

Please see the guide to using cellfinder with docker

To install download BrainGlobe atlases in advance, please see the guide to the BrainGlobe Atlas API command-line interface for details.