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Douglas Blank edited this page Nov 11, 2022
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Kangas is a tool for exploring, analyzing, and visualizing large-scale multimedia data. It provides a straightforward Python API for logging large tables of data, along with an intuitive visual interface for performing complex queries against your dataset.
The key features of Kangas include:
- Scalability. Kangas DataGrid, the fundamental class for representing datasets, can easily store millions of rows of data.
- Performance. Group, sort, and filter across millions of data points in seconds with a simple, fast UI.
- Interoperability. Any data, any environment. Kangas can run in a notebook or as a standalone app, both locally and remotely.
- Integrated computer vision support. Visualize and filter bounding boxes, labels, and metadata without any extra setup.
You can access a live demo of Kangas at kangas.comet.com.
Kangas DataGrid is completely open source; sponsored by Comet ML
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Home
- User Guides
- Installation - installing kangas
- Reading data - importing data
- Constructing DataGrids - building from scratch
- Exploring data - exploration and analysis
- Examples - scripts and notebooks
- Kangas Command-Line Interface
- Kangas Python API
- Integrations - with Hugging Face and Comet
- User Interface
- FAQ - Frequently Asked Questions
- Under the Hood
- Security - issues related to security
- Development - setting up a development environment
- Roadmap - plans and known issues
- User Guides