The napari hub is transitioning to a community-run implementation due to launch in June 2025.
Since October 1, 2024, this version is no longer actively maintained and will not be updated. New plugins and plugin updates will continue to be listed.

Loading tiffs using memory map

napari-memmap-tiff

When installed and enabled in the options, it adds an option that when enabled will make napari load tiffs via memory mapping instead of fully into RAM.

Workflow step:
Image annotation
Image segmentation

License MIT PyPI Python Version tests codecov napari hub npe2 Copier

When installed and enabled in the options, it adds an option that when enabled will make napari load tiffs via memory mapping instead of fully into RAM.

That is, .tif and .tiff files will be loaded into memory using memory mapping, which loads the data directly from disk instead of loading the file at once into RAM. This is beneficial for large files that may not fit into available RAM.


This napari plugin was generated with copier using the napari-plugin-template.

Installation

You can install napari-memmap-tiff via pip:

pip install napari-memmap-tiff

To install latest development version :

pip install git+https://github.com/matham/napari-memmap-tiff.git

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

Distributed under the terms of the MIT license, "napari-memmap-tiff" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.

Version:

  • 1.1.0

Last updated:

  • 11 June 2025

First released:

  • 10 June 2025

License:

Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 0
  • Forks: 0
  • Issues + PRs: 0

Python versions supported:

Operating system:

Requirements:

  • numpy
  • magicgui
  • qtpy
  • scikit-image
  • tifffile