napari blob detection

napari-blob-detection

Detects blobs in images


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    Detects blobs in images


    This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.

    This plugin consists of two widgets:

    1. Detects blobs on images
    2. Convert points layer to labels layer

    Detects blobs on images

    This widget uses scikit-image's blob detection algorithms to detect bright blobs on dark backgrounds.

    Parameters

    • method: Laplacian of Gaussian (most accurate) or Difference of Gaussian (faster approximation)
    • image: Image layer for blob detection. Can be a 2D, 3D, or higher dimensionality image.
    • dimensionality: users can specify if the image is 2D(+t) or 3D(+t).
    • min sigma: the smallest blob size to detect
    • max sigma: the largest blob size to detect
    • threshold: the lower the threshold, the more low intensity blobs are detected.

    Output

    Blobs are represented by the Points layer. The size of each blob is proportional to Points.feature['sigma'], which signifies the scale at which the feature point was found.

    Convert points layer to labels layer

    This widget takes a points layer and converts it into a labels layer, with the image dimension matching the selected image layer. By converting points to labels, users can leverage feature extraction functions that are available to labels to the detected points.


    Installation

    You can install napari-blob-detection via pip:

    pip install napari-blob-detection

    To install latest development version :

    pip install git+https://github.com/andy-sweet/napari-blob-detection.git

    Contributing

    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.

    License

    Distributed under the terms of the BSD-3 license, "napari-blob-detection" is free and open source software

    Issues

    If you encounter any problems, please file an issue along with a detailed description.

    Version:

    • 0.0.2

    Release date:

    • 22 April 2022

    First released:

    • 22 April 2022

    License:

    • BSD-3-Clause

    Supported data:

    • Information not submitted

    Plugin type:

    GitHub activity:

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

    Python versions supported:

    Operating system:

    Requirements:

    • napari (>=0.4.13)
    • numpy
    • scikit-image
    • magicgui

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