{"name":"napari-skimage","display_name":"napari skimage","visibility":"public","icon":"","categories":["Annotation","Segmentation","Acquisition"],"schema_version":"0.2.0","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"napari-skimage.make_farid_widget","title":"Make Farid filter widget","python_name":"napari_skimage.skimage_filter_widget:farid_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_prewitt_widget","title":"Make Prewitt filter widget","python_name":"napari_skimage.skimage_filter_widget:prewitt_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_laplace_widget","title":"Make Laplace filter widget","python_name":"napari_skimage.skimage_filter_widget:laplace_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_gaussian_widget","title":"Make gaussian filter widget","python_name":"napari_skimage.skimage_filter_widget:gaussian_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_frangi_widget","title":"Make Frangi filter widget","python_name":"napari_skimage.skimage_filter_widget:frangi_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_median_widget","title":"Make Median filter widget","python_name":"napari_skimage.skimage_filter_widget:median_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_butterworth_widget","title":"Make Butterworth filter widget","python_name":"napari_skimage.skimage_filter_widget:butterworth_filter_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_threshold_widget","title":"Make threshold 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widget","python_name":"napari_skimage.mathsops:maths_image_pairs_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_simple_maths_widget","title":"Make simple maths widget","python_name":"napari_skimage.mathsops:simple_maths_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_conversion_widget","title":"Make conversion widget","python_name":"napari_skimage.mathsops:conversion_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_rank_widget","title":"Make Rank filter widget","python_name":"napari_skimage.skimage_filter_widget:RankFilterWidget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_rolling_ball_restoration_widget","title":"Make rolling ball restoration widget","python_name":"napari_skimage.skimage_restoration_widget:rolling_ball_restoration_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-skimage.make_denoise_nl_means_restoration_widget","title":"Make denoise nl means restoration widget","python_name":"napari_skimage.skimage_restoration_widget:denoise_nl_means_restoration_widget","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":null,"writers":null,"widgets":[{"command":"napari-skimage.make_farid_widget","display_name":"Farid filter","autogenerate":false},{"command":"napari-skimage.make_prewitt_widget","display_name":"Prewitt filter","autogenerate":false},{"command":"napari-skimage.make_laplace_widget","display_name":"Laplace filter","autogenerate":false},{"command":"napari-skimage.make_gaussian_widget","display_name":"Gaussian filter","autogenerate":false},{"command":"napari-skimage.make_frangi_widget","display_name":"Frangi filter","autogenerate":false},{"command":"napari-skimage.make_median_widget","display_name":"Median filter","autogenerate":false},{"command":"napari-skimage.make_butterworth_widget","display_name":"Butterworth filter","autogenerate":false},{"command":"napari-skimage.make_threshold_widget","display_name":"Threshold","autogenerate":false},{"command":"napari-skimage.make_binary_morphology_widget","display_name":"Binary Morphology","autogenerate":false},{"command":"napari-skimage.make_morphology_widget","display_name":"Morphology","autogenerate":false},{"command":"napari-skimage.make_connected_components_widget","display_name":"Connected components","autogenerate":false},{"command":"napari-skimage.make_simple_maths_widget","display_name":"Simple maths","autogenerate":false},{"command":"napari-skimage.make_maths_image_pairs_widget","display_name":"Image pairs maths","autogenerate":false},{"command":"napari-skimage.make_conversion_widget","display_name":"Conversion","autogenerate":false},{"command":"napari-skimage.make_rank_widget","display_name":"Rank filters","autogenerate":false},{"command":"napari-skimage.make_rolling_ball_restoration_widget","display_name":"Rolling ball restoration","autogenerate":false},{"command":"napari-skimage.make_denoise_nl_means_restoration_widget","display_name":"Denoise nl means restoration","autogenerate":false}],"sample_data":null,"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.1","name":"napari-skimage","version":"0.1.2","dynamic":null,"platform":null,"supported_platform":null,"summary":"A plugin to apply scikit-image operations","description":"# napari-skimage\n\n[![License BSD-3](https://img.shields.io/pypi/l/napari-skimage.svg?color=green)](https://github.com/guiwitz/napari-skimage/raw/main/LICENSE)\n[![PyPI](https://img.shields.io/pypi/v/napari-skimage.svg?color=green)](https://pypi.org/project/napari-skimage)\n[![Python Version](https://img.shields.io/pypi/pyversions/napari-skimage.svg?color=green)](https://python.org)\n[![tests](https://github.com/guiwitz/napari-skimage/workflows/tests/badge.svg)](https://github.com/guiwitz/napari-skimage/actions)\n[![codecov](https://codecov.io/gh/guiwitz/napari-skimage/branch/main/graph/badge.svg)](https://codecov.io/gh/guiwitz/napari-skimage)\n[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-skimage)](https://napari-hub.org/plugins/napari-skimage)\n\nnapari-skimage gives easy access to scikit-image functions in napari. The main goal of the plugin is to allow new users of napari, especially without coding experience, to easily explore basic image processing, in a similar way to what is possible in Fiji.\n\nThis [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.\n\n## Philosophy\n\nThe plugin is still in early development and does not cover all functions of scikit-image. If you are interested in a specific function, please open an issue or a pull request. scikit-image functions are turned into interactive widgets mostly via magicgui, a tool that allows to create GUIs from functions in a simple way (in particular not requiring Qt knowledge). The code avoids on purpose complex approaches, e.g. to automate the creation of widgets, in order to keep the code simple and easy to understand for beginners.\n\n## Installation\n\nYou can install `napari-skimage` via [pip]:\n\n    pip install napari-skimage\n\n\n\nTo install latest development version :\n\n    pip install git+https://github.com/guiwitz/napari-skimage.git\n\n## Usage\n\nThe plugin function can be accessed under ```Plugins -> napari-skimage```. Each function will appear as a widget on the right of the napari window. Some functions such as ```Gaussian Filter``` give access to a single operation and its options. Some functions such as ```Thresholding``` give access to variants of the same operation via a dropdown menu. Currently the plugin does not support multi-channel processing and will consider those as stacks. At the moment, the plugin offers access to the following operation types.\n\n### Filtering\n\nA set of classical filters: Gaussian, Prewitt, Laplace etc. as well as rank filters such as median, minimum, maximum etc.\n\n![Gaussian filter](docs/gaussian.png)\n\n### Thresholding\nA set of thresholding methods: Otsu, Li, Yen etc.\n![Thresholding](docs/thresholding.png)\n\n### Binary morphological operations\nA set of binary morphology operations: binary erosion, binary dilation etc.\n![Binary morphological operations](docs/binary_morphology.png)\n\n### Morphological operations\nA set of morphological operations: erosion, dilation, opening, closing etc.\n![Morphological operations](docs/morphology.png)\n\n### Restoration\nA set of restoration operations such as rolling ball, or non-local means denoising.\n![Restoration](docs/denoise_nl.png)\n\n### Mathematics \nIn addition the plugin provides a set of simple mathematical operators to:\n- operate on single images e.g. square, square root, log etc.\n- operate on two images e.g. add, subtract, multiply etc.\n![Mathematics](docs/simple_maths.png)\n\n## Code structure\n\nEach set of functions is grouped in a separate module. For example all filtering operations are grouped in ```src/napari_skimge/skimage_filter_widget.py```. A set of test in ```src/_tests/test_basic_widgets.py``` simply check that each widget can be created and generated an output of the correct size using the default settings.\n\n## Contributing\n\nContributions are very welcome. Tests can be run with [tox], please ensure\nthe coverage at least stays the same before you submit a pull request.\n\n## License\n\nDistributed under the terms of the [BSD-3] license,\n\"napari-skimage\" 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[Cookiecutter]: https://github.com/audreyr/cookiecutter\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[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin\n\n[file an issue]: https://github.com/guiwitz/napari-skimage/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","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":"Guillaume Witz","author_email":"guillaume.witz@unibe.ch","maintainer":null,"maintainer_email":null,"license":"\nCopyright (c) 2024, Guillaume Witz, Data Science Lab, University of Bern\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 :: 2 - Pre-Alpha","Framework :: napari","Intended Audience :: Developers","License :: OSI Approved :: BSD License","Operating System :: OS Independent","Programming Language :: Python","Programming Language :: Python :: 3","Programming Language :: Python :: 3 :: Only","Programming Language :: Python :: 3.9","Programming Language :: Python :: 3.10","Programming Language :: Python :: 3.11","Programming Language :: Python :: 3.12","Topic :: Scientific/Engineering :: Image Processing"],"requires_dist":["numpy","magicgui","qtpy","scikit-image","tox ; extra == 'testing'","pytest ; extra == 'testing'","pytest-cov ; extra == 'testing'","pytest-qt ; extra == 'testing'","napari ; extra == 'testing'","pyqt5 ; extra == 'testing'"],"requires_python":">=3.9","requires_external":null,"project_url":["Bug Tracker, https://github.com/guiwitz/napari-skimage/issues","Documentation, https://github.com/guiwitz/napari-skimage#README.md","Source Code, https://github.com/guiwitz/napari-skimage","User Support, https://github.com/guiwitz/napari-skimage/issues"],"provides_extra":["testing"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}