A Napari plugin for detecting objects in 2D, 2D + time, 3D, and 3D + time, using the locate function from TrackPy and works best on objects that have a similar size and smooth intensity profile. Detected points can be filtered afterwards based on size and intensity. When detecting 3D objects in very crowded samples, the 3D 'Plane' view may make it easier to see the detected objects. Point intensities on image layers can be measured and visualized in a napari-skimage-regionprops inspired table widget, optionally per region.
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.
You can install napari-trackpy-point-detection via pip:
To install latest development version :
pip install git+https://github.com/AnniekStok/napari-trackpy-point-detection.git
Choose an estimated diameter in xy (and optionally z) (this must be an odd integer) and an estimated distance between objects. When your data is 3D but you leave the 'Use Z dimension' checkbox unticked, the third dimension will be treated as time, meaning that objects are detected frame by frame. The 'Intensity percentile threshold' parameter can be used to filter out dimmer objects that are below set intensity percentile.
Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.
Distributed under the terms of the BSD-3 license, "napari-trackpy-point-detection" is free and open source software
If you encounter any problems, please file an issue along with a detailed description.