Open-source tool for rapid machine learning experimentation
FiftyOne is the open-source tool for building high-quality datasets and computer vision models, with dataset visualization, curation, and model evaluation built in.
Open-source tool for rapid machine learning experimentation launched on November 2, 2020 with 5 votes, #1,364 of 3,461 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 5 years on.
What it does
Everything you need to build, evaluate, and ship better computer vision models. Explore your data in the FiftyOne App. Browse images, videos, and 3D data side-by-side with labels, metadata, and model predictions — all in one interactive view. Reveal hidden structure in your data with embedding visualizations. Mine hard samples, find near-duplicates, and recommend the best data for annotation. Annotation mistakes create an artificial ceiling on model performance. Use FiftyOne to automatically identify possible label mistakes and correct them in-app. Aggregate metrics alone don't give you the full picture. FiftyOne makes it easy to see where your models succeed and fail so you can iterate…from voxel51.com
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FiftyOne – Explore, Analyze and Curate Visual Datasets2020 · github.com · ▲6Refine high-quality datasets and visual AI models. Contribute to voxel51/fiftyone development by creating an account on GitHub.
Every open source tool from the "What's HN working on" thread2024 · github.com · ▲169Public datsets made with https://getomni.ai/. Contribute to getomni-ai/datasets development by creating an account on GitHub.
Embedding Atlas2025 · apple.github.io · ▲150Hey HN, we're happy to release Mycelium, a JavaScript library for creating graph visualizations of machine learning models or any other directed acyclic graphs. Mycelium powers the graph viewer of the Talaria [0] a research model visualization and optimization system, which was used to optimize the efficiency of Apple Foundation Models [1]. Everything works entirely on the client-side in the browser — we provide a rudimentary ONNX loader out of the box, which you can try by dragging model files into our website. It is also simple to define loaders for your own model formats. The library was…
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