A lightweight plugin extending label layer control

This light-weight plugin provides additional control over label layers. It is intended to ease your work when annotating data manually. Example screenshot

It provides you with a widget listing all individual labels. For each label, you can:

  • select it from the list to activate it for further drawing.
  • toggle the visibility of individual labels
  • locate the drawn label (i.e. move to the centroid location at the current zoom level)
  • change the label color with a color picker
  • erase the label (sets all the drawn pixels to the label layer background value)
  • restore an erased label (switching layers will reset this capability)

Everyone that has 2D or 3D data and wants to annotate (or curate annotated data) should find a useful extension with this plugin.

The plugin will recognise and work only on label layers.

Note: The "locate center" button will only work on 2D/3D label layers, i.e.: YX, ZYX, TYX, CYX.

Channels are considered a dimension.

  1. Start napari
  2. Open an image you want to annotate
    1. Best, an image with the same dimension as you labels layer should have
    2. e.g. File > Open Sample > napari > Binary Blobs (3D)
  3. Add (or load) a labels layer
  4. Start the plugin Plugins > napari-annotator: Annotator
  5. Make sure the labels layer is selected
  6. Start drawing

Known limitations

  1. Lag when drawing (see GitHub README for more info).
  2. Maximum 255 labels supported (see GitHub README for more info).

If you encounter bugs, please [file an issue] along with a detailed description. Or open a thread on with a detailed description and a @loicsauteur tag.

For general help, reach out via the with a tag @loicsauteur.

No citation needed. Honorable mention welcome.


  • 0.0.4

Last updated:

  • 03 April 2023

First released:

  • 07 March 2022


Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 3
  • Forks: 0
  • Issues + PRs: 2

Python versions supported:

Operating system:


  • numpy
  • scikit-image
  • qtpy

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