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TemplateFlow Archive

The TemplateFlow Archive aggregates all the templates for redistribution. The archive uses DataLad to maintain all templates under version control.

Accessing the Archive via the Python client

The recommended way to use TemplateFlow is via the Python Client

Accessing the Archive via DataLad

First, make sure you have a functional installation of DataLad. The archive has a top-level data structure to maintain all templates. This is the super-dataset , and it is maintained on GitHub . The latest stable super-dataset can be referenced with ///templateflow :

$ datalad install -r ///templateflow

The -r switch ensures all available templates are also installed .

Once the super-dataset and its siblings are installed, metadata will be already accessible. However, the different imaging data resources (NIfTI, GIFTI and transforms files) have to be pulled down.

For example, to download the complete tpl-MNI152NLin2009cAsym :

$ cd templateflow
$ datalad get -r tpl-MNI152NLin2009cAsym

TemplateFlow's data structure

Browse the archive