Quickstart

nidl

Nidl is a Python library to perform distributed training and evaluation of deep learning models on large-scale neuroimaging data (anatomical volumes and surfaces, fMRI).

It follows the PyTorch design for the training logic and the scikit-learn API for the models (in particular fit, predict and transform).

Supervised, self-supervised and unsupervised models are available (with pre-trained weights) along with open datasets.

Important links

• Official source code repo: https://github.com/neurospin-deepinsight/nidl

• HTML documentation (stable release): https://neurospin-deepinsight.github.io/nidl

Install

Latest release

1. Setup a virtual environment

We recommend that you install nidl in a virtual Python environment, either managed with the standard library venv or with conda. Either way, create and activate a new python environment.

With venv:

python3 -m venv /<path_to_new_env>
source /<path_to_new_env>/bin/activate

Windows users should change the last line to \<path_to_new_env>\Scripts\activate.bat in order to activate their virtual environment.

With conda:

conda create -n nidl python=3.12
conda activate nidl

2. Install nidl with pip

Execute the following command in the command prompt / terminal in the proper python environment:

python3 -m pip install -U nidl

Check installation

Try importing nidl in a python / iPython session:

import nidl

If no error is raised, you have installed nidl correctly.

Where to start

Examples are available in the gallery.

Dependencies

The required dependencies to use the software are listed in the file pyproject.toml.