Select regions of interest (ROIs) using napari

napari hub PyPI License Python Version Issues Pull requests

Select regions of interest (ROIs) using napari


You can install napari-roi via pip:

pip install napari-roi

Alternatively, you can install napari-roi via conda:

conda install -c conda-forge napari-roi


The napari-roi plugin can be opened from within napari (napari -> napari-roi: regions of interest) and operates on napari Shapes layers.

ROIs can be added to any napari Shapes layer, either by drawing a standard napari shape (e.g. rectangle), or by adding a rectangular ROI of specified size using the Add ROI functionality in the napari-roi widget. Each ROI is associated with a name, a position (X/Y origin), and a size (width/height). The location of the X/Y origin of all ROIs can be chosen in the napari-roi widget. Note that any shape supported by napari (e.g. ellipse, rectangle, polygon, line, path) can serve as an ROI; for non-rectangular shapes, napari-roi computes rectangular bounding boxes aligned with the napari coordinate system to determine their positions and sizes. ROIs can be edited or deleted by modifying the corresponding shapes in napari, or by editing the corresponding row in the napari-roi widget.

All ROIs in the current Shapes layer can be saved to a comma-separated values (CSV) file using the Save functionality in the napari-roi widget. When the Autosave option is checked, the file is automatically updated on every ROI change. Note that the selected file is specific to the current Shapes layer; ROIs from different Shapes layers cannot be saved to the same file. ROIs can be loaded from a previously saved file and added to the current Shapes layer by opening the file in the napari-roi widget.

CSV files saved using napari-roi adhere to the following format:

NameROI name
X, YPosition (X/Y origin)
W, HSize (width/height)


Created and maintained by Jonas Windhager until February 2023.

Maintained by Milad Adibi from February 2023.








  • 0.1.8

Last updated:

  • 17 February 2023

First released:

  • 19 November 2021


Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 4
  • Forks: 1
  • Issues + PRs: 4

Python versions supported:

Operating system:


  • numpy
  • pandas
  • qtpy

Sign up to receive updates