napari-pram

plugin for PRAM data annotation and processing


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    Source code:

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    Plugin for PRAM data annotation and processing.

    PRAM Demo


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

    Usage

    Open napari-pram toolbox:

    On the toolbar, select [Plugins] > napari-pram: Open PRAM's toolbox

    Load PRAM image and annotations:

    Press Command/Control + O:

    • Select *.json files for annotations (from either VGG Annotator or napari-pram)
    • Select *.png files for PRAM image

    Annotate

    • Press Annotate
    • Click the plus-in-circle icon on the top-left panel and start editing

    Run PRAM particles detector

    • Select a proper threshold between 1 (ultra sensitive) - 10 (less sensitive)
    • Press Run Detector

    Evaluate

    • Press Evaluate
    • Hide/Unhide true positive/ false postive/false negative layers

    Load new image

    • Press Clear All to remove all layers

    Export to JSON

    • Press Save to File to export all annotations, predictions from the algorithm to a JSON file

    Installation

    Following this tutorial to install napari.

    Alternatively, you can follow my instructions as follows:

    You will need a python environment. I recommend Conda. Create a new environment, for example:

    conda create --name napari-env python=3.7 pip 

    Activate the new environment:

    conda activate napari-env 

    Install napari via pip:

    pip install napari[all]

    Then you can finally install our plugin napari-pram via pip:

    pip install napari-pram

    Alternatively, the plugin can be installed using napari-GUI

    [Plugins] > Install/Uninstall Plugins and search for napari-pram

    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 MIT license, "napari-pram" is free and open source software

    Issues

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

    Version:

    • 0.1.3

    Release date:

    • 03 May 2022

    First released:

    • 29 April 2022

    License:

    • MIT

    Supported data:

    • Information not submitted

    GitHub activity:

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

    Python versions supported:

    Operating system:

    Requirements:

    • numpy
    • magicgui
    • qtpy
    • opencv-python
    • scipy

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