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napari plugin for ROI tracking and FRAP analysis in time-lapse images

Project description

Napari_Simple_Tracker

PyPI version 1.1.6 Python 3.10-3.14 napari hub

Napari_Simple_Tracker is a lightweight, easy-to-use napari plugin for ROI tracking and FRAP analysis in time-lapse imaging data.
It is intentionally simple while still providing the core tools needed for routine quantitative analysis.

  • Simple: point-based interaction with minimal configuration
  • Practical: tracking, intensity plotting, CSV export, and session save/load are included
  • Readable: ROI masks and track IDs are displayed directly in the napari viewer

Capabilities

Simple_Tracker

  • Multi ROI tracking
  • Linear interpolation across frames
  • Mean intensity measurement within circular ROIs
  • Plot generation
  • CSV export
  • Session save/load

Simple_FRAP_analysis

  • FRAP analysis using a main ROI, with optional reference and background ROIs
  • Background correction
  • Double normalization
  • Full-scale normalization
  • Plot generation
  • CSV export
  • Session save/load

Examples

Simple_Tracker

Simple Tracker demo

Simple_FRAP_analysis

FRAP Analysis demo

Installation

This package is published on PyPI as napari-simple-tracker.

Install with pip

Install the plugin in an environment where napari is already installed:

python -m pip install napari-simple-tracker

Install from napari

  1. Launch napari.
  2. Open Plugins -> Install/Uninstall Plugins....
  3. Use Install by name/URL.
  4. Enter the package name napari-simple-tracker and install it.

Install from source

To install the latest local version from this repository:

git clone https://github.com/Aohirovet/Napari_Simple_Tracker.git
cd Napari_Simple_Tracker
python -m pip install .

If you use a dedicated environment for napari, activate it before running the install command.

Usage

After installation, open napari and launch either widget from:

Plugins -> Napari Simple Tracker -> Simple_Tracker

or

Plugins -> Napari Simple Tracker -> Simple_FRAP_analysis

Quick Start

Open image
  -> place Points
  -> open plugin
  -> run analysis
  -> inspect masks, plots, and CSV output

Simple_Tracker

  1. Load a time-series image in napari.
  2. Create one Points layer for each object to be tracked.
  3. Mark the object center across multiple frames.
  4. Open Plugins -> Napari Simple Tracker -> Simple_Tracker.
  5. Press Run Simple Tracker.

Simple_FRAP_analysis

  1. Load a time-series image in napari.
  2. Create Points layers for the main ROI.
  3. Create one Points layer for the reference ROI.
  4. Optionally create one Points layer for the background ROI.
  5. Open Plugins -> Napari Simple Tracker -> Simple_FRAP_analysis.
  6. Select the relevant layers and ROI radii, then press Run FRAP Analysis.

Documentation

Detailed usage notes, supported image dimensions, output columns, session behavior, and common errors are documented here:

Release Note

For every new public release, increment the version in pyproject.toml before publishing to PyPI or expecting changes to appear on napari-hub.

License

MIT License

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