{"name":"mmv-regionseg","display_name":"MMV-RegionSeg","visibility":"public","icon":"","categories":["Segmentation","Image Processing"],"schema_version":"0.2.1","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"mmv-regionseg.make_qwidget","title":"Make example QWidget","python_name":"mmv_regionseg:ExampleQWidget","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":null,"writers":null,"widgets":[{"command":"mmv-regionseg.make_qwidget","display_name":"MMV-Region Segmentation","autogenerate":false}],"sample_data":null,"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.4","name":"mmv-regionseg","version":"0.4.0","dynamic":["license-file"],"platform":null,"supported_platform":null,"summary":"Napari plugin for the segmentation of regions by flood","description":"# mmv-regionseg\n\n[![License BSD-3](https://img.shields.io/pypi/l/mmv-regionseg.svg?color=green)](https://github.com/MMV-Lab/mmv-regionseg/raw/main/LICENSE)\n[![PyPI](https://img.shields.io/pypi/v/mmv-regionseg.svg?color=green)](https://pypi.org/project/mmv-regionseg)\n[![Python Version](https://img.shields.io/pypi/pyversions/mmv-regionseg.svg?color=green)](https://python.org)\n[![tests](https://github.com/MMV-Lab/MMV-RegionSeg/actions/workflows/test_and_deploy.yml/badge.svg)](https://github.com/MMV-Lab/MMV-RegionSeg/actions/workflows/test_and_deploy.yml)\n[![codecov](https://codecov.io/gh/MMV-Lab/mmv-regionseg/branch/main/graph/badge.svg)](https://codecov.io/gh/MMV-Lab/mmv-regionseg)\n[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/mmv-regionseg)](https://napari-hub.org/plugins/mmv-regionseg)\n\n*This README is in English. A German version is available here:* [README.de.md](README.de.md)\n\nA Napari plugin for region segmentation using flood fill\n\n----------------------------------\n\nThis [napari] plugin was generated with [copier] using the [napari-plugin-template].\n\n<!--\nDon't miss the full getting started guide to set up your new package:\nhttps://github.com/napari/napari-plugin-template#getting-started\n\nand review the napari docs for plugin developers:\nhttps://napari.org/stable/plugins/index.html\n-->\n\n## Installation\n\nYou can install `mmv-regionseg` via [pip]:\n\n    pip install mmv-regionseg\n\nTo install latest development version :\n\n    pip install git+https://github.com/MMV-Lab/mmv-regionseg.git\n\n## Documentation\n\n**MMV-RegionSeg** is a Napari plugin designed to segment three-dimensional image data based on the gray value of a selected seed point. Neighboring voxels are assigned to the same class if their intensity is sufficient similar to that of the seed point or falls within a defined tolerance range.\n\n---\n\n### Launching the Plugin\n\n1. Open Napari.\n2. Go to the **Plugins** menu.\n3. Select **MMV-RegionSeg** from the dropdown.\n\nA widget will appear on the right-hand side of the Napari window, containing buttons, labels, and a slider.\n\n---\n\n### Screenshot\n\n![MMV-RegionSeg Plugin Screenshot](https://raw.githubusercontent.com/MMV-Lab/MMV-RegionSeg/main/docs/images/plugin_screenshot1.png)\n\n---\n\n### Loading Image Data\n\nClick the **\"Read image\"** button to load a 3D image in TIFF format. A standard OS file dialog will open. Once the image is selected, Napari will display it as an **image layer**.\n\n---\n\n### Adjusting Tolerance\n\nUse the **slider** below the image loading button to set the gray-value tolerance (0%–100% of the dynamic range):\n\n- **Low tolerance** → risk of incomplete region filling.\n- **High tolerance** → risk of including undesired regions.\n\n> ⚠️ The optimal tolerance often requires some experimentation.\n\n---\n\n### Definition of the Footprint\n\nUse the **dropdown list** to select the footprint for `skimage.segmentation.flood`.\nSee also: [Flood Fill].\n\n- **6 neighbors** → Only voxels directly adjacent in X, Y, and Z are considered.\n- **18 neighbors** → Includes voxels diagonally adjacent along faces and edges.\n- **26 neighbors** → All neighboring voxels are included.\n\n---\n\n### Selecting Seed Points\n\nClick **\"Select seed points\"** to activate a new **points layer** in Napari. You can then define seed points directly in the viewer.\n\n- Each seed point is visualized.\n- Multiple seed points defined in one step are treated as one class.\n- Use Napari’s **Layer Controls** to move or delete seed points.\n\n---\n\n### Segmentation Options\n\nAfter placing seed points, you can choose between two segmentation methods:\n\n#### Flood\n\nClick **Flood** to perform segmentation using `skimage.segmentation.flood`.\nThis identifies neighboring voxels within the tolerance range and saves them to a new **label layer**.\n\nYou can repeat this for additional classes by selecting new seed points. Each class receives its own label layer.\n\n#### Growth\n\nClick **Growth** to visualize the segmentation **step by step**.  \nThis simulates the growth of a region, similar to the expansion of a cell colony in a Petri dish.\n\n---\n\n### Resetting for New Segmentation\n\nAfter a label layer is created, the **points layer is removed**, allowing you to define new seed points without affecting the existing segmentation results.\n\n---\n\n## Contributing\n\nContributions are welcome!\n\nTests can be run with [tox]; please ensure that coverage does not decrease before submiting a pull request.\n\n## License\n\nDistributed under the terms of the [BSD-3] license,\n\"mmv-regionseg\" is free and open source software\n\n## Issues\n\nIf you encounter any problems, please [file an issue] along with a detailed description.\n\n[napari]: https://github.com/napari/napari\n[copier]: https://copier.readthedocs.io/en/stable/\n[@napari]: https://github.com/napari\n[MIT]: http://opensource.org/licenses/MIT\n[BSD-3]: http://opensource.org/licenses/BSD-3-Clause\n[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt\n[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt\n[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0\n[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt\n[napari-plugin-template]: https://github.com/napari/napari-plugin-template\n\n[file an issue]: https://github.com/MMV-Lab/mmv-regionseg/issues\n\n[napari]: https://github.com/napari/napari\n[tox]: https://tox.readthedocs.io/en/latest/\n[pip]: https://pypi.org/project/pip/\n[PyPI]: https://pypi.org/\n[Flood Fill]: https://scikit-image.org/docs/0.25.x/auto_examples/segmentation/plot_floodfill\n","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":null,"author_email":"Peter Lampen <lampen@isas.de>","maintainer":null,"maintainer_email":null,"license":"Copyright (c) 2025, Peter Lampen\nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n* Redistributions of source code must retain the above copyright notice, this\n  list of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright notice,\n  this list of conditions and the following disclaimer in the documentation\n  and/or other materials provided with the distribution.\n\n* Neither the name of copyright holder nor the names of its\n  contributors may be used to endorse or promote products derived from\n  this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n","classifier":["Development Status :: 3 - Alpha","Intended Audience :: Science/Research","Framework :: napari","Topic :: Scientific/Engineering :: Image Processing","Programming Language :: Python","Programming Language :: Python :: 3","Programming Language :: Python :: 3.9","Programming Language :: Python :: 3.10","Programming Language :: Python :: 3.11","Programming Language :: Python :: 3.12","Operating System :: OS Independent","License :: OSI Approved :: BSD License"],"requires_dist":["napari<0.6.0,>=0.5.0","numpy<2.0,>=1.23","qtpy>=2.0","scikit-image>=0.20","tifffile>=2023.2.28","pyqt5>=5.15; extra == \"qt\"","tox>=4.0; extra == \"testing\"","pytest>=7.0; extra == \"testing\"","pytest-cov>=4.0; extra == \"testing\"","pytest-qt>=4.0; extra == \"testing\""],"requires_python":">=3.9","requires_external":null,"project_url":["Homepage, https://github.com/MMV-Lab/mmv-regionseg","Bug Tracker, https://github.com/MMV-Lab/mmv-regionseg/issues","Documentation, https://github.com/MMV-Lab/mmv-regionseg#README.md","Source Code, https://github.com/MMV-Lab/mmv-regionseg","User Support, https://github.com/MMV-Lab/mmv-regionseg/issues"],"provides_extra":["qt","testing"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}