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a free, open-source web app for annotating, training, and evaluating image understanding algorithms

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Piximi

Piximi is a free, open source web app for performing image understanding tasks. It’s written by by dozens of engineers and scientists from institutions like the Biological Research Centre Szeged, Broad Institute of MIT and Harvard, Chan Zuckerberg Initiative, ETH Zurich, and FIMM Helsinki.

Piximi's target users are computational or non-computational scientists interested in image analysis from fields like astronomy, biology, and medicine.

Contributing

Both technical and non-technical contributions are welcome and encouraged! In addition to general-purpose programming tasks, there’re numerous tasks for anyone with expertise or an interest in computer graphics, computer vision, image processing, or machine learning. There’re also a number of areas that’d benefit from non-technical contributors too, including writing or improving documentation and translations, packaging example classifiers, and even providing user feedback (especially around problems in fields where current contributors lack familiarity). The Contributing article on our wiki has more information about contributing to Piximi.

Organization

This repository includes both the Piximi web app (packages/piximi) and the handful of discrete @piximi sub-packages (packages/@piximi/*) written concurrently or alongside the web app. The packages included in the packages directory are versioned together and simultaneously published to the NPM package repository.

  • @piximi/components: generic React components
  • @piximi/evaluate-classifier-dialog: Piximi’s EvaluateClassifierDialog component
  • @piximi/fit-classifier-dialog: Piximi’s FitClassifierDialog component
  • @piximi/gallery-dialog: Piximi’s GalleryDialog component
  • @piximi/help-dialog: Piximi’s HelpDialog component
  • @piximi/hooks: generic React hooks
  • @piximi/image-viewer-dialog: Piximi’s ImageViewerDialog component
  • @piximi/models: Piximi’s TensorFlow.js models
  • @piximi/navigation-drawer: Piximi’s NavigationDrawer component
  • @piximi/open-example-classifier-dialog: Piximi’s OpenExampleClassifierDialog component
  • @piximi/send-feedback-dialog: Piximi’s SendFeedbackDialog component
  • @piximi/settings-dialog: Piximi’s SettingsDialog component
  • @piximi/store: Piximi’s Redux actions, reducers, selectors, and stores
  • @piximi/theme: Piximi’s Material UI theme
  • @piximi/translations: Piximi’s translations
  • @piximi/types: Piximi’s generic TypeScript definitions
  • @piximi/upload-image-dialog: Piximi’s UploadImageDialog component
  • piximi: Piximi web app

Scripts

bootstrap

Use the bootstrap command to bootstrap the packages found in the ./packages directory:

yarn bootstrap

build

Use the build command to build the packages found in the ./packages directory:

yarn build

clean

Use the clean command to clean the build artifacts created by “build.”

yarn clean

test

Use the test command to run the unit tests found in the packages in the ./packages directory:

yarn test

Dependencies

Use the lerna add command to add a dependency to one or more packages.

If a dependency is used by just one package, use the scope option to specify the correct package name. For example:

lerna add foo --scope=@piximi/bar

adds the foo package to the decencies of the @piximi/bar package.

If a dependency is used by more than one package, use the scope option to specify the correct packages and provide the peer option to specify that the package is a peer dependency. For example:

lerna add foo --peer --scope=@piximi/bar, @piximi/baz 

adds the foo package to the peer dependencies of both the @piximi/bar and @piximi/baz package.

If a dependency is used by every package (e.g. TypeScript) you can omit the scope option. For example,

lerna add foo ---peer 

adds the foo package to the peer dependencies of the packages found in packages/@piximi and the packages/piximi package.

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a free, open-source web app for annotating, training, and evaluating image understanding algorithms

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  • TypeScript 96.0%
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