{"name":"aiod-napari","display_name":"AI OnDemand","visibility":"public","icon":null,"categories":[],"schema_version":"0.2.1","on_activate":"aiod_napari.load_manifests:activate_plugin","on_deactivate":null,"contributions":{"commands":[{"id":"aiod-napari.inference","title":"Segment using pre-trained models","python_name":"aiod_napari.inference:Inference","short_title":"Inference","category":null,"icon":null,"enablement":null},{"id":"aiod-napari.evaluation","title":"Evaluate segmentations","python_name":"aiod_napari.evaluation:Evaluation","short_title":"Evaluation","category":null,"icon":null,"enablement":null},{"id":"aiod-napari.postprocess","title":"Postprocess segmentations","python_name":"aiod_napari.postprocessing:Postprocess","short_title":"Postprocess","category":null,"icon":null,"enablement":null},{"id":"aiod-napari.example_data","title":"Example FIB SEM data","python_name":"aiod_napari.example_data:load_example_data","short_title":"Example Data","category":null,"icon":null,"enablement":null},{"id":"aiod-napari.bioio_reader","title":"Read bioimaging file formats","python_name":"aiod_napari.io:get_bioio_reader","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"aiod-napari.rle_reader","title":"Read RLE segmentations","python_name":"aiod_napari.io:get_rle_reader","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"aiod-napari.rle_writer","title":"Write segmentations to RLE format","python_name":"aiod_napari.io:rle_writer","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":[{"command":"aiod-napari.rle_reader","filename_patterns":["*.pkl","*.pickle","*.rle"],"accepts_directories":false},{"command":"aiod-napari.bioio_reader","filename_patterns":["*"],"accepts_directories":false}],"writers":[{"command":"aiod-napari.rle_writer","layer_types":["labels"],"filename_extensions":[".pkl",".pickle",".rle"],"display_name":""}],"widgets":[{"command":"aiod-napari.inference","display_name":"Inference","autogenerate":false},{"command":"aiod-napari.evaluation","display_name":"Segmentation Evaluation","autogenerate":false},{"command":"aiod-napari.postprocess","display_name":"Postprocess","autogenerate":false}],"sample_data":[{"command":"aiod-napari.example_data","key":"example_fibsem","display_name":"Example FIB SEM data"}],"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.4","name":"aiod-napari","version":"0.1","dynamic":null,"platform":null,"supported_platform":null,"summary":"A plugin for segmenting images using AI models via the Segment-Flow Nextflow pipeline.","description":"# AIoD Napari Plugin\n\nNapari plugin part of [AI OnDemand (AIoD)](https://franciscrickinstitute.github.io/aiod_docs) to provide an accessible interface for running deep learning models on images via our [Nextflow pipeline](https://github.com/FrancisCrickInstitute/Segment-Flow).\n\n----------------------------------\n\nThis [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.\n\n## Installation\n\nSee our latest installation information in our [documentation](https://franciscrickinstitute.github.io/aiod_docs/sections/front_ends/napari_plugin/#installation)!\n\nIn general, you should see the [official Napari installation instructions](https://napari.org/stable/getting_started/installation.html#install-python-package) first to ensure Napari is installed with an appropriate Qt backend.\n\n### `uv`\nA `uv.lock` file is provided for smoother installation:\n\n```\nuv add aiod_napari\n```\n\n### Conda\nWe have also provided a conda environment file to install all the dependencies for this plugin. To install the environment, run the following command:\n\n    conda env create -f ai-od.yml\n\nNote that when it comes to the installation of napari this may be preferable, depending on whether your system is best supported by the pip- or conda-packaged version.\n\n## Usage\nFor general usage of the plugin, see the [documentation](https://franciscrickinstitute.github.io/aiod_docs/sections/front_ends/napari_plugin/).\n\nFor developers, see our [developer guide](https://franciscrickinstitute.github.io/aiod_docs/sections/contributing/developing/) for some tips on how to get started and contribute to the plugin.\n\n## Contributing\n\nContributions are very welcome. Tests can be run with [tox], please ensure the coverage at least stays the same before you submit a pull request.\n\n## Issues\n\nIf you encounter any problems, please raise an issue along with a detailed description.\n","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":null,"author_email":"Cameron Shand <cameron.shand@crick.ac.uk>, Numan Ahmed <numan.ahmed@crick.ac.uk>, Fiona Young <fiona.young@crick.ac.uk>, Qin Yu <qin.yu@crick.ac.uk>, Jon Smith <jon.smith@crick.ac.uk>","maintainer":null,"maintainer_email":null,"license":"MIT License\n\nCopyright (c) 2026 Cameron Shand\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.","classifier":["Development Status :: 4 - Beta","Framework :: napari","Intended Audience :: Developers","License :: OSI Approved :: MIT License","Operating System :: OS Independent","Programming Language :: Python","Programming Language :: Python :: 3","Programming Language :: Python :: 3 :: Only","Programming Language :: Python :: 3.11","Programming Language :: Python :: 3.12","Topic :: Scientific/Engineering :: Artificial Intelligence","Topic :: Scientific/Engineering :: Image Processing"],"requires_dist":["aiod-registry==0.1","aiod-utils==0.1","dask-image","glasbey","napari>=0.6","numpy<2","pandas","platformdirs","pyyaml","qtpy","requests","scikit-image>0.20","scipy","tabulate","napari; extra == 'testing'","pyqt5; extra == 'testing'","pytest; extra == 'testing'","pytest-cov; extra == 'testing'","pytest-qt; extra == 'testing'","tox; extra == 'testing'"],"requires_python":"<3.13,>=3.11","requires_external":null,"project_url":["homepage, https://github.com/FrancisCrickInstitute/aiod_napari","documentation, https://franciscrickinstitute.github.io/aiod_docs/sections/front_ends/napari_plugin/","source, https://github.com/FrancisCrickInstitute/aiod_napari"],"provides_extra":["testing"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}