Submitted by calebkaiser t3_yx2krb in MachineLearning
Project Link: https://github.com/comet-ml/kangas
My colleagues and I have been working over the last several months on a tool for visualizing and exploring large, multimedia datasets, with a particular emphasis on computer vision. Today, we're open sourcing the repository and sharing it publicly!
The project is called Kangas, and its Python API will be familiar to anyone whose used Pandas, with one major difference: When you call `DataGrid.show()` on a Kangas DataGrid, you see a UI like this:
We've focused on a handful of features for this first release:
- Scalability. Kangas stores your DataGrids as SQLite databases, as opposed to in-memory like other tools, allowing you to store larger amounts of data and perform queries quickly.
- Simplicity. We want it to be incredibly easy to build and render a DataGrid. No tinkering with custom showImage() and plotLabels() methods—just load in your DataGrid and the server will handle metadata parsing, asset rendering, and more.
- Interoperability. Kangas can run inside a notebook environment, as a standalone app on your local machine, or can even be deployed as a web app (as we've done at kangas.comet.com ). It also supports a wide variety of data types, and has more robust multimedia support on the immediate roadmap.
Under the hood, Kangas is built on SQLite, along with React Server Components and Next.js, which allows it to render performantly. It's still early days, but we're very excited to share the project with the community and get some initial feedback. Please, don't hesitate to open a ticket or a PR—we love community contributions.
I'm happy to answer any questions you may have here or on the repo!
Spiritual-Reply5896 t1_iwn1g6i wrote
How would you say it compares to FiftyOne, are your goals the same as with their project?