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FiftyOne Computer Vision Community Update – August 2023

Welcome to the monthly blog series where we bring you up to speed on recent happenings in the FiftyOne community and celebrate noteworthy milestones. 🙌 🚀

Community Spotlights

We love hearing how FiftyOne helps you solve challenges and reach new heights! Curious what sorts of use cases are possible with FiftyOne? Here’s a highlight from the open source FiftyOne community.

“Fast Code AI relies on FiftyOne for managing our data lifecycle. Upon receiving initial data from our data labeling partner, IndiVillage, we load it into FiftyOne and scrutinize the labeling for any initial inconsistencies. We then provide feedback and obtain the next batch of data. This is where we train our baseline models and identify any outliers. We sort the data by their ground truth class confidence values in increasing order and display it in FiftyOne. This helps us easily spot and correct any incorrect labels. With approximately 30 attributes per image and over 40 possible values for each attribute, visualizing the data elsewhere is challenging. We greatly appreciate FiftyOne’s contribution to our workflow, as it has significantly increased our efficiency. We cannot imagine managing our data without this tool, as it offers an unmatched level of customization and functionality.”

— Arjun Jain, Founder and Chief Scientist, Fast Code AI

Community Rewards

Is your organization using FiftyOne to solve interesting computer vision problems? Share your success story and claim a box of community rewards as a thank you!

Product Releases

In July there were a few point releases to both the open source and Teams versions of FiftyOne. Here are the links to the releases learn more:

Open Source FiftyOne

FiftyOne Teams

Community Integrations

July brought us two new exciting vector search integrations! 


Milvus is one of the most popular vector databases available, and we’ve made it easy to use Milvus’s vector search capabilities on your computer vision data directly from FiftyOne! FiftyOne provides an API to create Milvus collections, upload vectors, and run similarity queries, both programmatically in Python and via point-and-click in the App. Follow these simple instructions to get started using Milvus + FiftyOne. Shout out to Filip Haltmayer from Zilliz for creating the integration.


LanceDB is a serverless vector database with deep integrations with the Python ecosystem. It requires no setup and is free to use. FiftyOne provides an API to create LanceDB tables and run similarity queries, both programmatically in Python and via point-and-click in the App. Shout out to Ayush Chaurasia from LanceDB for creating the integration.

FiftyOne on GitHub

GitHub is home to the open source FiftyOne project. Here’s the latest snapshot of what’s happening in the FiftyOne GitHub repo:

  • Total stars: 3,900+
  • Total contributors: 65
  • Total used by: 359
  • Total forks: 391
  • Total issues closed so far: 844

FiftyOne Community Slack

The FiftyOne Community Slack channel is where you can join more than 1,900 machine learning engineers and data scientists using FiftyOne to improve the quality of their computer vision data and build better models. Last month alone we had almost 150 new members join. Ask questions, answer questions, or simply follow along with the discussion!

To make it easy to catch the highlights, every Friday we recap interesting questions and answers from Slack in Tips & Tricks blog series. Recent posts include:

Computer Vision Meetups

Computer Vision Meetups Worlwide, sponsored by Voxel51

Voxel51 sponsors 13 virtual Computer Vision Meetups around the world. (To join, visit the Meetup link and scroll down to find the location friendliest to your time zone.)

The Computer Vision Meetups are geared towards data scientists, machine learning engineers, and open source enthusiasts who want to expand their knowledge of computer vision and complementary technologies. We put an emphasis on open source software, and speakers who are computer vision practitioners or academics doing research in the field. This month’s Meetups include:

August Computer Vision Meetup

  • Neural Congealing: Aligning Images to a Joint Semantic Atlas – Dolev Ofri-Amar at Weizmann Institute of Science
  • Advancing Personalized Medicine and Radiotherapy through AI-Enabled Computer Vision – Roushanak Rahmat, PhD, AI Researcher
  • A Practical Approach to Deep Learning for Computer Vision with Tensorflow 2 – Folefac Martins at Vinsight and ML Instructor

August Computer Vision Meetup – APAC

  • Removing Backgrounds Automatically or with a User’s Language – Jizhizi Li, PhD, University of Sydney
  • Self-Supervised Representative Learning for Action Recognition in Videos – Vidhya Vinay, Co-Founder of
  • AI at the Edge: Optimizing Deep Learning Models for Real-World Applications Raz Petel, SightX

Recapping July’s Meetups

If you missed any of last month’s Meetups, you can get the executive summaries and links to the video playbacks here:

Upcoming Computer Vision Events

In addition to Meetups, we invite you to join us for one or more of these upcoming events:

New Docs, Blogs, Videos, and Tutorials

We want everyone to be successful with FiftyOne, and one of the ways we try to do that is by publishing resources that you might find helpful and handy. Here’s a list of some of the new documentation, blogs, videos, tutorials, integrations, and cheat sheets that you may want to check out.



Voxel51’s Commitment to Open Source and Community

Open source, transparency, and giving back to the computer vision community is what we are all about! Whether it’s developing the open source FiftyOne computer vision toolset to help engineers and data scientists build high-quality datasets and models, sponsoring Meetups to help members boost their computer vision knowledge, or giving to charitable causes on behalf of the community, Voxel51 is committed to bringing transparency and clarity to the world’s data.