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A plugin to browse OME-Zarr plates by conditions and load images, labels and features from ROIs

Project description

napari-ome-zarr-navigator

License BSD-3 PyPI Python Version tests codecov

A plugin to browse OME-Zarr plates by conditions and load images, labels and features from ROIs

Usage

Plate Browser

The Plate Browser loads an OME-Zarr plate from the local filesystem or via authenticated HTTPS (e.g. a Fractal Server instance). It also auto-detects plates opened via napari-ome-zarr.

navigator_plate_browser

The Plate Browser lets you zoom to a selected well ("Go to well"), which draws a bounding box and centers the camera on that well.

plate_browser_go_to_well

Using ngio condition tables, the Plate Browser can filter the well list to any subset defined by one or more conditions. Plate-level condition tables (fast) and image-level condition tables (slower, aggregated on the fly) are both supported.

plate_browser_filtering

ROI Loader

The ROI Loader can be launched directly from napari's Plugins menu (standalone) or by selecting a well in the Plate Browser ("Select ROI to load"). It supports:

  • Loading images from different multiplexing cycles / acquisitions
  • Loading any ROI from ROI tables, or the whole image when no ROI table is selected
  • Loading label images
  • Loading feature measurements from feature tables
  • Multi-resolution (lazy) mode — streams a full dask pyramid, optimal for large images and remote data
  • Fixed resolution mode — loads a single numpy array, optimal for 3D images and downstream tools in napari that don't handle multi-resolution layers (e.g. the label layer needs to be loaded as fixed resolution for using it in the classifier)

Once a ROI has been loaded for one well, "Load selected ROI for additional well(s)" reuses the same settings for any further wells selected in the Plate Browser.

roi_loader

This plugin is tested with OME-Zarr files generated by Fractal and is designed to work with any OME-Zarr ≥ v0.4. The feature loading workflow is optimised for use with the napari-feature-classifier.


Test data

Test & sample data is available at https://zenodo.org/records/20429951

Installation

Via pixi (recommended)

pixi manages all Python and system dependencies in a single step:

git clone https://github.com/fractal-napari-plugins-collection/napari-ome-zarr-navigator
cd napari-ome-zarr-navigator
pixi run napari

To launch with the full feature-analysis environment (adds napari-feature-classifier and napari-feature-visualization):

pixi run napari-fractal

Via pip

Install into an existing Python ≥ 3.11 environment with napari already present:

pip install napari-ome-zarr-navigator

For a fresh environment we recommend miniforge:

conda create -n napari-ome-zarr python=3.12 napari pyqt -c conda-forge
conda activate napari-ome-zarr
pip install napari-ome-zarr-navigator
napari

Optionally also install additional plugins like napari-feature-classifier and napari-feature-visualization, as in:

pip install napari-feature-classifier napari-feature-visualization

Contributing

Contributions are very welcome. Tests can be run with pixi run test; please ensure coverage stays the same before submitting a pull request.

License

Distributed under the terms of the BSD-3 license, "napari-ome-zarr-navigator" is free and open source software

Issues

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

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