btrack
A framework for Bayesian multi-object tracking
btrack
is a multi object tracking algorithm,
specifically used to reconstruct trajectories in crowded fields. New
observations are assigned to tracks by evaluating the posterior probability of
each potential linkage from a Bayesian belief matrix for all possible
linkages.
We developed btrack
for cell tracking in time-lapse microscopy data.
Installation¶
To install the napari
plugin associated with btrack
run the command.
pip install btrack[napari]
Example data¶
You can try out the btrack plugin using sample data:
python btrack/napari/examples/show_btrack_widget.py
which will launch napari
and the btrack
widget, along with some sample data.
Setting parameters¶
There are detailed tips and instructions on parameter settings over at the documentation.
Associated plugins¶
- napari-arboretum - Napari plugin to enable track graph and lineage tree visualization.
Supported data:
- Information not submitted
Plugin type:
Save layers:
GitHub activity:
- Stars: 311
- Forks: 50
- Issues + PRs: 54