A framework for Bayesian multi-object tracking

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    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.



    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/

    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.


    • 0.6.5

    Last updated:

    • 05 March 2024

    First released:

    • 27 May 2020


    Supported data:

    • Information not submitted

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    GitHub activity:

    • Stars: 309
    • Forks: 50
    • Issues + PRs: 54

    Python versions supported:

    Operating system:


    • cvxopt >=1.3.1
    • h5py >=2.10.0
    • numpy >=1.17.3
    • pandas >=2.0.3
    • pooch >=1.0.0
    • pydantic <2
    • scikit-image >=0.16.2
    • scipy >=1.3.1
    • tqdm >=4.65.0