Annotation Toolbox

napari-nD-annotator

A toolbox for annotating objects one by one in nD


    License BSD-3 PyPI Python Version tests codecov napari hub

    A toolbox for annotating objects one by one in nD

    This plugin contains some tools to make 2D/3D, but basically any dimensional annotation easier. Main features:

    • nD bounding box layer
    • object list from bounding boxes
    • visualizing selected objects from different projections
    • auto-filling labels
    • label slice interpolation

    The main idea is to create bounding boxes around objects we want to annotate, crop them, and annotate them one by one. This has mainly two advantages when visualizing in 3D:

    1. We don't have to load the whole data into memory
    2. The surrounding objects won't occlude the annotated ones, making it easier to check the annotation.

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

    Installation

    You can install napari-nD-annotator via pip:

    pip install napari-nD-annotator

    The plugin is also available in napari-hub, to install it directly from napari, please refer to plugin installation instructions at the official napari website.

    Usage

    You can start napari with the plugin's widgets already opened as:

    napari -w napari-nD-annotator "Object List" "Annotation Toolbox"

    The proposed pipeline goes as follows:

    1. Create a bounding box layer
    2. Select data parts using the bounding boxes
    3. Select an object from the object list
    4. Annotate the object
    5. Repeat from 3.

    Example

    import napari
    from skimage.data import cells3d
    import numpy as np
    viewer = napari.Viewer()
    nuclei = cells3d()[:, 1]
    viewer.add_image(nuclei, colormap="magma")
    viewer.add_labels(np.zeros_like(nuclei))
    napari.run()

    License

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

    Issues

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

    Version:

    • 0.0.6

    Release date:

    • 14 June 2022

    First released:

    • 01 June 2022

    License:

    • BSD-3-Clause

    Supported data:

    • Information not submitted

    Plugin type:

    GitHub activity:

    • Stars: 2
    • Forks: 1
    • Issues + PRs: 12

    Python versions supported:

    Operating system:

    Requirements:

    • numpy
    • magicgui
    • qtpy
    • opencv-python
    • matplotlib
    • napari (==0.4.15)
    • vispy (==0.9.6)
    • scikit-image

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