DenoiSeg

napari-denoiseg

A napari plugin performing joint denoising and segmentation of microscopy images using DenoiSeg.


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    A napari plugin performing joint denoising and segmentation of microscopy images using DenoiSeg.

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    Installation

    Check out the documentation for more detailed installation instructions.

    Quick demo

    You can try out a demo by loading the DenoiSeg Demo prediction plugin and directly clicking on Predict.

    Documentation

    Documentation is available on the project website.

    Contributing and feedback

    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. You can also help us improve by filing an issue along with a detailed description or contact us through the image.sc forum (tag @jdeschamps).

    Cite us

    Tim-Oliver Buchholz, Mangal Prakash, Alexander Krull and Florian Jug, "DenoiSeg: Joint Denoising and Segmentation" arxiv (2020)

    Acknowledgements

    This plugin was developed thanks to the support of the Silicon Valley Community Foundation (SCVF) and the Chan-Zuckerberg Initiative (CZI) with the napari Plugin Accelerator grant 2021-239867.

    Distributed under the terms of the BSD-3 license, "napari-denoiseg" is a free and open source software.

    Version:

    • 0.0.1rc2

    Release date:

    • 01 November 2022

    First released:

    • 31 October 2022

    License:

    • BSD-3-Clause

    Supported data:

    • Information not submitted

    Plugin type:

    GitHub activity:

    • Stars: 5
    • Forks: 0
    • Issues + PRs: 0

    Python versions supported:

    Operating system:

    Requirements:

    • numpy
    • pyqtgraph
    • denoiseg (>=0.3.0)
    • bioimageio.core
    • magicgui
    • qtpy
    • napari-time-slicer (>=0.4.9)
    • napari (<=0.4.15)
    • vispy (<=0.9.6)
    • imageio (!=2.11.0,!=2.22.1,>=2.5.0)
    • tensorflow ; platform_system != "Darwin" or platform_machine != "arm64"
    • tensorflow-macos ; platform_system == "Darwin" and platform_machine == "arm64"
    • tensorflow-metal ; platform_system == "Darwin" and platform_machine == "arm64"

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