napari

@napari.org

n-dimensional image viewer for Python

And it's a wrap! The hackathon was a fantastic success! 🥳 You can look forward to a longer post about all we did, and one of our biggest releases yet in 0.9.0! Huge thanks to all the participants 🤩, and we hope to see you at the next one!

Hackathon participants discussing a new feature demo.Jules Vanaret shows off slicing of volumes with non-orthogonal transforms.The naPLari hackathon crowd: Wouter-Michiel Vierdag, Grzegorz Bokota, Tim Monko, Giannis Liaskas, Draga Doncila Pop, Lorenzo Gaifas, Aroj Hada, Brian Northan, Jules Vanaret, Zuzana Čočková, Curtis Rueden, Juan Nunez-Iglesias, and Margot Chazotte.Celebratory drink after the last full day of the hackathon. 🍻
napari@napari.org · 3mo ago

🎉 Announcing the naPLari hackathon in Kraków, Poland 🇵🇱, July 24–29 2026, after EuroSciPy! Hack on napari, join deep dives, meet the team. All experience levels welcome! 📝 Register by July 1: napari.typeform.com/naplari-hack #napari #ScientificPython #OpenSource #EuroSciPy #BioImageAnalysis

📣 One of the best parts of #SciPy2026 is seeing the Scientific Python ecosystem evolve in real time. Today's Tools Plenary featured updates from the teams behind Zarr, Xarray, Tiled, Pangeo, scikit-image, Matplotlib, and napari, showcasing new features & future directions 🫶

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Struggling for something to do in a TWO DAY gap without ⚽? How about trying our pre-release of napari 0.8.0? napari.org/dev/release/... Of note, this release drops Py3.10 support and deprecates PyQt5 in favor of PyQt6. It also adds some neat new features and improvements! See below: 👇

napari 0.7.1 is now available!! 🚀 🎉 Read the full release notes here: napari.org/stable/relea... Highlights: the scale bar inherits units from layers, colorbars for points layers, locking layers, and a signed Windows bundle! We thank especially our 9 new brilliant contributors 🤩

Woohoo, copick is out! Access to massive amounts of CryoET data, MCP for agentic, plus a @napari.org interface! We even used it when hosting the CZII CryoET Kaggle competition: www.kaggle.com/competitions... when we needed to support a large collaborative annotation event with humans + ML models.

CZII - CryoET Object Identification

Find small biological structures in large 3D volumes

kaggle.com

Utz Ermel@uermel.bsky.social · 4mo ago

Excited to share our paper about copick, a dataset API and toolkit for collaborative annotation and analysis of #cryoET data! Whether you're picking particles or curating segmentations, copick reduces friction and brings #OME-Zarr to cryoET without breaking pipelines. 🧵👇 doi.org/10.1002/pro.70578

napari 0.7.0 is available now! 🚀🎉 It's a BIG release so read the full release notes, with highlights: napari.org/stable/relea... We want to thank everyone who has worked incredibly hard on this release including our 11 new brilliant contributors 🤩 and the community for their support and feedback!

napari 0.7.0

Mon, Mar 23, 2026 We’re happy to announce the release of napari 0.7.0! napari is a fast, interactive, multi-dimensional image viewer for Python. It’s designed for browsing, annotating, and analyzing…

napari.org

First paper as first & corresponding author, out in PLOS Computational Biology! 🎉 napariTFM brings traction force & monolayer stress microscopy into napari, accessible via GUI; open-source, validated and no coding required. 😉 Check it out 👇

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Check out and give feedback on the latest pre-release 0.7.0rc0! You can install with `pip install "napari[all]>=0.7.0rc0"` or via the bundled app. 😁 🥳 The release notes, with highlights, include so many great new features and changes: napari.org/dev/release/...

napari 0.7.0

⚠️ Note: these release notes are still in draft while 0.7.0 is in release candidate testing. ⚠️ Tue, Mar 10, 2026 We’re happy to announce the release of napari 0.7.0! napari is a fast, interactive,…

napari.org

BIG UPDATES! OCTRON now supports the new SAM3 models (alongside SAM2)! We’ve also added a global switch for Detection vs. Segmentation: Use the same annotations to train either lightweight detection or full segmentation models. Plus, we’ve added support for the new YOLO26 models. ⤵️ 1/12

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Rewrote my Python bioformats wrapper (from aicsimageio/bioio) as a standalone package: - fully bootstrapped Java setup (just pip install) - lazy, repeatably-indexable Array object - fully spec-compliant OME-Zarr group obj. - xarray/dask exports github.com/imaging-form... v0.0.rc1 on PyPI

GitHub - imaging-formats/bffile: Modern Bio-Formats wrapper with clean lazy Python API

Modern Bio-Formats wrapper with clean lazy Python API - imaging-formats/bffile

github.com