Palmari provides a plugin to analyze PALM movies, as well as microscope recordings of other SMLM-based SPT modalities. Set up your pipeline on one file, run it on a folder !


Palmari allows you to process your SPT recordings (PALM or other modalities, 2D) with an all-inclusive pipeline: spot detection, sub-pixel localization, tracking & more. Start quickly with default parameters or customize your pipeline, and run it on entire folder of microscope recordings.


On a single recording

To run Palmari on a single microscope recording, click on "Palmari > run Palmari on file..." You'll see a panel open on the right with a pre-loaded default analysis pipeline.

Default pipeline

You can run steps of the pipeline one after the other and tweak the parameters so that they suit your experimental setup. Don't forget to set the pixel size and exposure. You can also add and remove processing steps by clicking on the "Edit pipeline" button.

Visualize results at each step of the process

When you're satisfied with te results, just click on "Save locs and tracks" to export localizations and trajectories in a CSV format.

On a series of files

Once you've set up your processing pipeline, you can save it under the form of a yaml file by clicking on "save pipeline". Then, to use it to process all your acquisitions within a same series of experimental recordings, click on "palmari > run Palmari on folder...", load the pipeline, select the folder where your files lie, and click process !

What to do next ? Try Tracktor

If you want to test the statistical significance of the difference between the sets of trajectories observed in one or the other experiment (or set of experiments), you may want to try Tracktor. It's an online platform developed at tout lab that allows to statistically compare sets of trajectories.

It notably

  1. estimates the p-value of the following null hypothesis "Both these sets of trajectories were generated by the same stochastic process",
  2. identifies trajectories that are more found in one set than in another,
  3. provides nice visualizations of various standard metrics.


Find more details on Palmari in the documentation.

Getting Help

Email Hippolyte Verdier :


  • 0.3.0

Last updated:

  • 01 May 2023

First released:

  • 06 May 2022


  • "CeCILL"

Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 4
  • Forks: 2
  • Issues + PRs: 0

Python versions supported:

Operating system:


  • click
  • dask (>=2022.1.0)
  • dask-image (>=2021.12.0)
  • imageio-ffmpeg
  • magicgui (>=0.5.0)
  • matplotlib (>=3.5)
  • munkres
  • napari
  • napari-aicsimageio
  • numpy
  • pandas
  • pyyaml
  • qtpy
  • scikit-image (>=0.18.3)
  • scikit-learn
  • toml
  • tqdm
  • trackpy (>=0.5.0)