Package: napari
naparimulti-dimensional image viewer for pythonnapariis a fast, interactive, multi-dimensional image viewer for Python. It's designed for browsing, annotating, and analyzing large multi-dimensional images. It's built on top of Qt (for the GUI), vispy (for performant GPU-based rendering), and the scientific Python stack (numpy, scipy).We're developingnapariin the open! But the project is in analphastage, and there will still likely bebreaking changeswith each release. You can follow progress onthis repository, test out new versions as we release them, and contribute ideas and code.We're working ontutorials, but you can also quickly get started by looking below.installationIt is recommended to install napari into a virtual environment, like this:condacreate-y-nnapari-env-cconda-forgepython=3.9
condaactivatenapari-env
python-mpipinstall"napari[all]"If you prefer conda over pip, you can replace the last line with:conda install -c conda-forge napari pyqtSee here for the fullinstallation guide.simple example(The examples below require thescikit-imagepackage to run. We just use data samples from this package for demonstration purposes. If you change the examples to use your own dataset, you may not need to install this package.)From inside an IPython shell, you can open up an interactive viewer by callingfromskimageimportdataimportnapariviewer=napari.view_image(data.cells3d(),channel_axis=1,ndisplay=3)To use napari from inside a script, usenapari.run():fromskimageimportdataimportnapariviewer=napari.view_image(data.cells3d(),channel_axis=1,ndisplay=3)napari.run()# start the "event loop" and show the viewerfeaturesCheck out the scripts in ourexamplesfolderto see some of the functionality we're developing!naparisupports six main different layer types,Image,Labels,Points,Vectors,Shapes, andSurface, each corresponding to a different data type, visualization, and interactivity. You can add multiple layers of different types into the viewer and then start working with them, adjusting their properties.All our layer types support n-dimensional data and the viewer provides the ability to quickly browse and visualize either 2D or 3D slices of the data.naparialso supports bidirectional communication between the viewer and the Python kernel, which is especially useful when launching from jupyter notebooks or when using our built-in console. Using the console allows you to interactively load and save data from the viewer and control all the features of the viewer programmatically.You can extendnapariusing custom shortcuts, key bindings, and mouse functions.tutorialsFor more details on how to usenaparicheckout ourtutorials. These are still a work in progress, but we'll be updating them regularly.mission, values, and roadmapFor more information about our plans fornapariyou can read ourmission and values statement, which includes more details on our vision for supporting a plugin ecosystem around napari.
You can see details ofthe project roadmap here.contributingContributions are encouraged! Please read ourcontributing guideto get started. Given that we're in an early stage, you may want to reach out on ourGithub Issuesbefore jumping in.code of conductnaparihas aCode of Conductthat should be honored by everyone who participates in thenaparicommunity.governanceYou can learn more about how thenapariproject is organized and managed from ourgovernance model, which includes information about, and ways to contact the@napari/steering-council and @napari/core-devs.citing napariIf you findnapariuseful please citethis repositoryusing its DOI as follows:napari contributors (2019). napari: a multi-dimensional image viewer for python.doi:10.5281/zenodo.3555620Note this DOI will resolve to all versions of napari. To cite a specific version please find the
DOI of that version on ourzenodo page. The DOI of the latest version is in the badge at the top of this page.helpWe're a community partner on theimage.sc forumand all help and support requests should be posted on the forum with the tagnapari. We look forward to interacting with you there.Bug reports should be made on ourgithub issuesusing
the bug report template. If you think something isn't working, don't hesitate to reach out - it is probably us and not you!institutional and funding partners