The napari hub is transitioning to a community-run implementation due to launch in June 2025.
Since October 1, 2024, this version is no longer actively maintained and will not be updated. New plugins and plugin updates will continue to be listed.

Segment Anything V2

napari-SAMV2

Napari plugin for segment anything version 2 model from meta. Plugin primarily useful for segmenting 3d volumetric data or 3d time series data.

Workflow step:
Image annotation
Image segmentation

Napari plugin to use segment anything version 2.1 models from Meta.

Plugin made for segmenting 3d volumetric data or 3d time series data.


Installation

The plugin requires the following pre-requisite to be installed :

  1. Python and pytorch versions

python>=3.10,torch>=2.5.1 and torchvision>=0.20.1 required

To install pytorch with your respective OS please visit - https://pytorch.org/get-started/locally/

  1. SAM v2 installation from meta

Please refer https://github.com/facebookresearch/sam2

  1. Install napari

python -m pip install "napari[all]"

Following is a sample conda environment installation with the above pre-req

conda create -n samv2_env python=3.10
conda activate samv2_env
pip3 install torch torchvision

git clone https://github.com/facebookresearch/sam2.git && cd sam2
pip install -e .

python -m pip install "napari[all]"

pip install napari-SAMV2

Usage

Middle mouse click - positive point or keyboard shortcut "a"

Ctrl + Middle mouse click - negative point or keyboard shortcut "n"

Time Series Segmentation :

samv2_time_series_demo

Volume Segmentation :

samv2_volume_segmentation

Reference :

Example Data in the demo videos are from,

Cell tracking challenge - https://celltrackingchallenge.net/

and

FlyEM project - https://www.janelia.org/project-team/flyem/hemibrain

License

Distributed under the terms of the BSD-3 license, "napari-SAMV2" is free and open source software

Issues

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

Version:

  • 0.0.6

Last updated:

  • 29 April 2025

First released:

  • 08 October 2024

License:

Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 1
  • Forks: 2
  • Issues + PRs: 1

Python versions supported:

Operating system:

Requirements:

  • numpy
  • magicgui
  • qtpy
  • scikit-image