# napari-process-points-and-surfaces (nppas)
[](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/raw/master/LICENSE)
[](https://pypi.org/project/napari-process-points-and-surfaces)
[](https://python.org)
[](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/actions)
[](https://codecov.io/gh/haesleinhuepf/napari-process-points-and-surfaces)
[](https://en.wikipedia.org/wiki/Software_release_life_cycle#Alpha)
[](https://napari-hub.org/plugins/napari-process-points-and-surfaces)
[](https://doi.org/10.5281/zenodo.7654555)
Process and analyze surfaces using [vedo](https://vedo.embl.es/) in [napari].
The nppas gastruloid example is derived from [AV Luque and JV Veenvliet (2023)](https://zenodo.org/record/7603081) which is licensed [CC-BY](https://creativecommons.org/licenses/by/4.0/legalcode) and can be downloaded from here: https://zenodo.org/record/7603081
## Usage
You find menus for surface generation, smoothing and analysis in the menu `Tools > Surfaces` and `Tools > Points`.
For detailed explanation of the underlying algorithms, please refer to the [vedo](https://vedo.embl.es/) documentation.
For processing meshes in Python scripts, see the [demo notebook](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/blob/main/docs/demo.ipynb).
There you also learn how this screenshot is made:
For performing quantitative measurements of surface in Python scripts, see the [demo notebook](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/blob/main/docs/quality_measurements.ipynb).
There you also learn how this screenshot is made:
### Surface measurements and annotations
Using the menu `Tools > Measurement tables > Surface quality table (vedo, nppas)` you can derive quantiative measurements of
the vertices in a given surface layer.
To differentiate regions when analyzing those measurements it is recommended to use the menu `Tools > Surfaces > Annotate surface manually (nppas)`
after measurements have been made. This tool allows you to draw annotation label values on the surface.
It is recommended to do activate a colorful colormap such as `hsv` before starting to draw annotations.
Furthermore, set the maximum of the contrast limit range to the number of regions you want to annotate + 1.
Annotations can be drawn as freehand lines and circles.
After measurements and annotations were done, you can save the annotation in the same measurement table using the menu
`Tools > Measurement tables > Surface quality/annotation to table (nppas)`
For classifying surface vertices using machine learning, please refer to the [napari APOC](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification) documentation.
### Measurement visualization
To visualize measurements on the surface, just double-click on the table column headers.
## Installation
You can install `napari-process-points-and-surfaces` via mamba/conda and pip:
```
mamba install vedo vtk libnetcdf=4.7.4 -c conda-forge
pip install napari-process-points-and-surfaces
```
### Troubleshooting: Open3d installation
Since version 0.4.0, `nppas` does no longer depend on [open3d](http://www.open3d.org/).
Some deprecated functions still use Open3d though.
Follow the installation instructions in the [open3d documentation](http://www.open3d.org/docs/release/getting_started.htm) to install it and keep using those functions.
Also consider updating code and no longer using these deprecated functions.
See [release notes](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/releases/tag/0.4.0) for details.
## See also
There are other napari plugins with similar / overlapping functionality
* [morphometrics](https://www.napari-hub.org/plugins/morphometrics)
* [napari-accelerated-pixel-and-object-classification](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification)
* [napari-pymeshlab](https://www.napari-hub.org/plugins/napari-pymeshlab)
* [napari-pyclesperanto-assistant](https://www.napari-hub.org/plugins/napari-pyclesperanto-assistant)
* [napari-stress](https://www.napari-hub.org/plugins/napari-stress)
And there is software for doing similar things:
* [meshlab](https://www.meshlab.net/)
* [paraview](https://www.paraview.org/)
## 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-process-points-and-surfaces" is free and open source software
## Acknowledgements
Some code snippets and example data were taken from the [vedo](https://vedo.embl.es/) and [open3d](http://www.open3d.org/)
repositories and documentation. See [thirdparty licenses](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/tree/main/licenses_third_party) for licensing details.
The Standford Bunny example dataset has been taken from [The Stanford 3D Scanning Repository](http://graphics.stanford.edu/data/3Dscanrep/).
The nppas gastruloid example is derived from [AV Luque and JV Veenvliet (2023)](https://zenodo.org/record/7603081) which is licensed [CC-BY](https://creativecommons.org/licenses/by/4.0/legalcode) and can be downloaded from here: https://zenodo.org/record/7603081
## Issues
If you encounter any problems, please create a thread on [image.sc] along with a detailed description and tag [@haesleinhuepf].
[napari]: https://github.com/napari/napari
[Cookiecutter]: https://github.com/audreyr/cookiecutter
[@napari]: https://github.com/napari
[MIT]: http://opensource.org/licenses/MIT
[BSD-3]: http://opensource.org/licenses/BSD-3-Clause
[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt
[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt
[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0
[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt
[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin
[file an issue]: https://github.com/haesleinhuepf/napari-process-points-and-surfaces/issues
[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
[image.sc]: https://image.sc
[@haesleinhuepf]: https://twitter.com/haesleinhuepf
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"description": "# napari-process-points-and-surfaces (nppas)\r\n\r\n[](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/raw/master/LICENSE)\r\n[](https://pypi.org/project/napari-process-points-and-surfaces)\r\n[](https://python.org)\r\n[](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/actions)\r\n[](https://codecov.io/gh/haesleinhuepf/napari-process-points-and-surfaces)\r\n[](https://en.wikipedia.org/wiki/Software_release_life_cycle#Alpha)\r\n[](https://napari-hub.org/plugins/napari-process-points-and-surfaces)\r\n[](https://doi.org/10.5281/zenodo.7654555)\r\n\r\nProcess and analyze surfaces using [vedo](https://vedo.embl.es/) in [napari].\r\n\r\n\r\nThe nppas gastruloid example is derived from [AV Luque and JV Veenvliet (2023)](https://zenodo.org/record/7603081) which is licensed [CC-BY](https://creativecommons.org/licenses/by/4.0/legalcode) and can be downloaded from here: https://zenodo.org/record/7603081\r\n\r\n## Usage\r\n\r\nYou find menus for surface generation, smoothing and analysis in the menu `Tools > Surfaces` and `Tools > Points`. \r\nFor detailed explanation of the underlying algorithms, please refer to the [vedo](https://vedo.embl.es/) documentation.\r\n\r\nFor processing meshes in Python scripts, see the [demo notebook](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/blob/main/docs/demo.ipynb). \r\nThere you also learn how this screenshot is made:\r\n\r\n\r\n\r\nFor performing quantitative measurements of surface in Python scripts, see the [demo notebook](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/blob/main/docs/quality_measurements.ipynb). \r\nThere you also learn how this screenshot is made:\r\n\r\n\r\n\r\n### Surface measurements and annotations\r\n\r\nUsing the menu `Tools > Measurement tables > Surface quality table (vedo, nppas)` you can derive quantiative measurements of\r\nthe vertices in a given surface layer. \r\n\r\n\r\n\r\nTo differentiate regions when analyzing those measurements it is recommended to use the menu `Tools > Surfaces > Annotate surface manually (nppas)`\r\nafter measurements have been made. This tool allows you to draw annotation label values on the surface. \r\nIt is recommended to do activate a colorful colormap such as `hsv` before starting to draw annotations. \r\nFurthermore, set the maximum of the contrast limit range to the number of regions you want to annotate + 1.\r\nAnnotations can be drawn as freehand lines and circles.\r\n\r\n\r\n\r\nAfter measurements and annotations were done, you can save the annotation in the same measurement table using the menu\r\n`Tools > Measurement tables > Surface quality/annotation to table (nppas)`\r\n\r\n\r\n\r\nFor classifying surface vertices using machine learning, please refer to the [napari APOC](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification) documentation.\r\n\r\n### Measurement visualization\r\n\r\nTo visualize measurements on the surface, just double-click on the table column headers.\r\n\r\n\r\n\r\n## Installation\r\n\r\nYou can install `napari-process-points-and-surfaces` via mamba/conda and pip:\r\n\r\n```\r\nmamba install vedo vtk libnetcdf=4.7.4 -c conda-forge\r\npip install napari-process-points-and-surfaces\r\n```\r\n\r\n### Troubleshooting: Open3d installation\r\n\r\nSince version 0.4.0, `nppas` does no longer depend on [open3d](http://www.open3d.org/). \r\nSome deprecated functions still use Open3d though. \r\nFollow the installation instructions in the [open3d documentation](http://www.open3d.org/docs/release/getting_started.htm) to install it and keep using those functions.\r\nAlso consider updating code and no longer using these deprecated functions. \r\nSee [release notes](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/releases/tag/0.4.0) for details.\r\n\r\n## See also\r\n\r\nThere are other napari plugins with similar / overlapping functionality\r\n* [morphometrics](https://www.napari-hub.org/plugins/morphometrics) \r\n* [napari-accelerated-pixel-and-object-classification](https://www.napari-hub.org/plugins/napari-accelerated-pixel-and-object-classification)\r\n* [napari-pymeshlab](https://www.napari-hub.org/plugins/napari-pymeshlab)\r\n* [napari-pyclesperanto-assistant](https://www.napari-hub.org/plugins/napari-pyclesperanto-assistant)\r\n* [napari-stress](https://www.napari-hub.org/plugins/napari-stress)\r\n\r\nAnd there is software for doing similar things:\r\n* [meshlab](https://www.meshlab.net/)\r\n* [paraview](https://www.paraview.org/)\r\n\r\n## Contributing\r\n\r\nContributions are very welcome. Tests can be run with [tox], please ensure\r\nthe coverage at least stays the same before you submit a pull request.\r\n\r\n## License\r\n\r\nDistributed under the terms of the [BSD-3] license,\r\n\"napari-process-points-and-surfaces\" is free and open source software\r\n\r\n## Acknowledgements\r\n\r\nSome code snippets and example data were taken from the [vedo](https://vedo.embl.es/) and [open3d](http://www.open3d.org/) \r\nrepositories and documentation. See [thirdparty licenses](https://github.com/haesleinhuepf/napari-process-points-and-surfaces/tree/main/licenses_third_party) for licensing details.\r\nThe Standford Bunny example dataset has been taken from [The Stanford 3D Scanning Repository](http://graphics.stanford.edu/data/3Dscanrep/).\r\nThe nppas gastruloid example is derived from [AV Luque and JV Veenvliet (2023)](https://zenodo.org/record/7603081) which is licensed [CC-BY](https://creativecommons.org/licenses/by/4.0/legalcode) and can be downloaded from here: https://zenodo.org/record/7603081\r\n\r\n## Issues\r\n\r\nIf you encounter any problems, please create a thread on [image.sc] along with a detailed description and tag [@haesleinhuepf].\r\n\r\n[napari]: https://github.com/napari/napari\r\n[Cookiecutter]: https://github.com/audreyr/cookiecutter\r\n[@napari]: https://github.com/napari\r\n[MIT]: http://opensource.org/licenses/MIT\r\n[BSD-3]: http://opensource.org/licenses/BSD-3-Clause\r\n[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt\r\n[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt\r\n[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0\r\n[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt\r\n[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin\r\n\r\n[file an issue]: https://github.com/haesleinhuepf/napari-process-points-and-surfaces/issues\r\n\r\n[napari]: https://github.com/napari/napari\r\n[tox]: https://tox.readthedocs.io/en/latest/\r\n[pip]: https://pypi.org/project/pip/\r\n[PyPI]: https://pypi.org/\r\n\r\n[image.sc]: https://image.sc\r\n[@haesleinhuepf]: https://twitter.com/haesleinhuepf\r\n",
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