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Visualization and Mission Control","Python","Other scientific libraries","\u003ca id=\"tag-graphics\" href=\"#tag-graphics\"\u003eGraphics\u003c/a\u003e","Visualization \u0026 Post-processing","Visualization and Analysis","General image analysis software","🔬 Domain-Specific Applications"],"sub_categories":["Annotation","Data visualization","Verified vs declared","🧬 Biology \u0026 Medicine"],"readme":"# napari\n\n### multi-dimensional image viewer for python\n\n\u003c!-- Project info --\u003e\n[![License](https://img.shields.io/pypi/l/napari.svg)](https://github.com/napari/napari/raw/main/LICENSE)\n[![Supported Python versions](https://img.shields.io/pypi/pyversions/napari.svg)](https://python.org)\n[![Python package index](https://img.shields.io/pypi/v/napari.svg)](https://pypi.org/project/napari)\n[![Python package index download statistics](https://img.shields.io/pypi/dm/napari.svg)](https://pypistats.org/packages/napari)\n[![Conda Version](https://img.shields.io/conda/vn/conda-forge/napari.svg)](https://anaconda.org/conda-forge/napari)\n![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/napari?label=Conda%20downloads)\n[![DOI](https://zenodo.org/badge/144513571.svg)](https://zenodo.org/badge/latestdoi/144513571)\n\n\u003c!-- Project standards and quality  --\u003e\n[![Development Status](https://img.shields.io/pypi/status/napari.svg)](https://en.wikipedia.org/wiki/Software_release_life_cycle#Beta)\n[![SPEC 0 — Minimum Supported Dependencies](https://img.shields.io/badge/SPEC-0%20(aspiring!)-green?labelColor=%23004811\u0026color=%235CA038)](https://scientific-python.org/specs/spec-0000/)\n[![EffVer Versioning](https://img.shields.io/badge/version_scheme-EffVer-0097a7)](https://jacobtomlinson.dev/effver)\n[![Comprehensive Test](https://github.com/napari/napari/actions/workflows/test_comprehensive.yml/badge.svg)](https://github.com/napari/napari/actions/workflows/test_comprehensive.yml)\n[![Code coverage](https://codecov.io/gh/napari/napari/branch/main/graph/badge.svg)](https://codecov.io/gh/napari/napari)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n\n\u003c!-- Community and support --\u003e\n[![Sponsor our Project](https://img.shields.io/badge/donate-to%20napari-blueviolet)](https://numfocus.org/donate-to-napari)\n[![image.sc forum](https://img.shields.io/badge/dynamic/json.svg?label=forum\u0026url=https%3A%2F%2Fforum.image.sc%2Ftags%2Fnapari.json\u0026query=%24.topic_list.tags.0.topic_count\u0026colorB=brightgreen\u0026suffix=%20topics\u0026logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAA4AAAAOCAYAAAAfSC3RAAABPklEQVR42m3SyyqFURTA8Y2BER0TDyExZ+aSPIKUlPIITFzKeQWXwhBlQrmFgUzMMFLKZeguBu5y+//17dP3nc5vuPdee6299gohUYYaDGOyyACq4JmQVoFujOMR77hNfOAGM+hBOQqB9TjHD36xhAa04RCuuXeKOvwHVWIKL9jCK2bRiV284QgL8MwEjAneeo9VNOEaBhzALGtoRy02cIcWhE34jj5YxgW+E5Z4iTPkMYpPLCNY3hdOYEfNbKYdmNngZ1jyEzw7h7AIb3fRTQ95OAZ6yQpGYHMMtOTgouktYwxuXsHgWLLl+4x++Kx1FJrjLTagA77bTPvYgw1rRqY56e+w7GNYsqX6JfPwi7aR+Y5SA+BXtKIRfkfJAYgj14tpOF6+I46c4/cAM3UhM3JxyKsxiOIhH0IO6SH/A1Kb1WBeUjbkAAAAAElFTkSuQmCC)](https://forum.image.sc/tag/napari)\n[![napari on Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/napari/napari/main?urlpath=%2Fdesktop)\n\n**napari** is 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).\n\nWe're developing **napari** in the open! You can follow progress on [our project roadmap]([https://github.com/napari/napari](https://github.com/orgs/napari/projects/24)), test out new versions as we release them, and contribute ideas and code.\n\nIf you want to refer to our documentation, please go to [napari.org](https://www.napari.org). If you want to contribute to it, please refer to the *contributing* section below. \n\nWe're working on [tutorials](https://napari.org/stable/tutorials/), but you can also quickly get started by looking below.\n\n## try it out now!\n[Install uv](https://docs.astral.sh/uv/getting-started/installation/#standalone-installer) to try napari.\nThen launch the program in a terminal window with the command:\n```sh\nuvx \"napari[all]\"\n```\nIn the `File` menu, select `Open Sample` and select a sample image to get started.\n\n\n## installation\nFor a full installation, we recommend installing napari into a virtual environment, like this:\n\n```sh\nconda create -y -n napari-env -c conda-forge python=3.11\nconda activate napari-env\npython -m pip install \"napari[all]\"\n```\n\nIf you prefer conda over pip, you can replace the last line with: `conda install -c conda-forge napari pyqt6`\n\nSee here for the full [installation guide](https://napari.org/stable/tutorials/fundamentals/installation.html).\n\n## simple example\n\nThis example uses a data sample from the `scikit-image` library, but you can pass your own dataset as an array to `imshow`.\nFrom inside an IPython shell, you can open up an interactive viewer by calling\n\n```python\nfrom skimage import data\nimport napari\n\nviewer, layers = napari.imshow(data.cells3d(), channel_axis=1, ndisplay=3)\n```\n\n![napari viewer with a multichannel image of cells displayed as two image layers: nuclei and membrane.](./src/napari/resources/multichannel_cells.png)\n\n\nTo use napari from inside a script, use `napari.run()`:\n\n```python\nfrom skimage import data\nimport napari\n\nviewer, layers = napari.imshow(data.cells3d(), channel_axis=1, ndisplay=3)\nnapari.run()  # start the \"event loop\" and show the viewer\n```\n\n## features\n\nCheck out the scripts in our [`examples` folder](examples) to see some of the functionality we're developing!\n\n**napari** supports six main different layer types, `Image`, `Labels`, `Points`, `Vectors`, `Shapes`, and `Surface`, 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.\n\nAll 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.\n\n**napari** also 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.\n\nYou can extend **napari** using custom shortcuts, key bindings, and mouse functions.\n\n## tutorials\n\nFor more details on how to use `napari` checkout our [tutorials](https://napari.org/stable/tutorials/). These are still a work in progress, but we'll be updating them regularly.\n\n## mission, values, and roadmap\n\nFor more information about our plans for `napari` you can read our [mission and values statement](https://napari.org/stable/community/mission_and_values.html), which includes more details on our vision for supporting a plugin ecosystem around napari.\nYou can see details of [the project roadmap here](https://napari.org/stable/roadmaps/index.html).\n\n## contributing\n\nContributions are encouraged! See [CONTRIBUTING.md](https://github.com/napari/napari/blob/main/CONTRIBUTING.md) for resources to get started.\n\nIf you want to contribute to or edit our documentation, please go to [napari/docs](https://github.com/napari/docs).\n\nVisit our [project weather report dashboard](https://napari.org/weather-report/) to see metrics and how development is progressing.\n\n## code of conduct\n\n`napari` has a [Code of Conduct](https://napari.org/stable/community/code_of_conduct.html) that should be honored by everyone who participates in the `napari` community.\n\n## governance\n\nYou can learn more about how the `napari` project is organized and managed from our [governance model](https://napari.org/stable/community/governance.html), which includes information about, and ways to contact the [@napari/steering-council and @napari/core-devs](https://napari.org/stable/community/team.html#current-core-developers).\n\n## citing napari\n\nIf you find `napari` useful please cite [this repository](https://github.com/napari/napari) using its DOI as follows:\n\n\u003e napari contributors (2019). napari: a multi-dimensional image viewer for python. [doi:10.5281/zenodo.3555620](https://zenodo.org/record/3555620)\n\nNote this DOI will resolve to all versions of napari. To cite a specific version please find the\nDOI of that version on our [zenodo page](https://zenodo.org/record/3555620). The DOI of the latest version is in the badge at the top of this page.\n\n## help\n\nWe're a community partner on the [image.sc forum](https://forum.image.sc/tags/napari) and all help and support requests should be posted on the forum with the tag `napari`. We look forward to interacting with you there.\n\nBug reports should be made on our [GitHub issues](https://github.com/napari/napari/issues/new?template=bug_report.md) using\nthe bug report template. If you think something isn't working, don't hesitate to reach out - it is probably us and not you!\n\n## institutional and funding partners\n\n\u003ca href=\"https://chanzuckerberg.com/\"\u003e\n  \u003cpicture\u003e\n    \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"https://chanzuckerberg.com/wp-content/themes/czi/img/logo-white.svg\"\u003e\n    \u003cimg alt=\"CZI logo\" src=\"https://chanzuckerberg.com/wp-content/themes/czi/img/logo.svg\"\u003e\n  \u003c/picture\u003e\n\u003c/a\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnapari%2Fnapari","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnapari%2Fnapari","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnapari%2Fnapari/lists"}