comet-ml/kangas

🦘 Explore multimedia datasets at scale

49
/ 100
Emerging

Kangas helps machine learning engineers and data scientists explore, analyze, and visualize large multimedia datasets. You can input various data sources like CSVs, Pandas DataFrames, or image collections, and it outputs an interactive visual interface to query and understand your data. This is ideal for anyone working with datasets containing images, videos, or audio at scale.

1,063 stars. No commits in the last 6 months. Available on PyPI.

Use this if you need to quickly visualize, filter, and sort millions of multimedia data points, especially those with attached metadata like bounding boxes or labels.

Not ideal if you are primarily focused on tracking and comparing machine learning experiment training runs, which tools like TensorBoard are designed for.

data-exploration computer-vision machine-learning-engineering multimedia-analysis
Stale 6m
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 14 / 25

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Stars

1,063

Forks

50

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Dec 07, 2024

Commits (30d)

0

Dependencies

15

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