The Voxel51 engineering team is thrilled to announce the general availability of FiftyOne 0.23.5 and FiftyOne Teams 1.5.6, which brings with them dozens of enhancements and fixes to streamline your computer vision workflows. This pair of releases includes over a dozen new features and fixes. Read on to learn more.
Wait, what’s FiftyOne?
FiftyOne is the open source machine learning toolset that enables data science teams to improve the performance of their computer vision models by helping them curate high quality datasets, evaluate models, find mistakes, visualize embeddings, and get to production faster.
Okay, but what’s FiftyOne Teams?
FiftyOne Teams extends FiftyOne with a GSuite-like experience for teams that want to collaborate on data stored in a centralized location with additional features like user permissions, dataset versioning, cloud-backed media, and enterprise security.
If this sounds interesting, read on! Then schedule a demo to learn more about FiftyOne Teams.
What’s new in FiftyOne 0.23.5
This release includes the following updates:
What’s New
- Added support for apply monocular depth estimation transformers from the Hugging Face transformers library directly to FiftyOne datasets – #4082
- Added subcounts to search results in the sidebar – #3973
- Added fiftyone.operators.types.ViewTargetProperty to make it simpler to add view selection to a fiftyone.operators.Operator – #4076
What’s new in FiftyOne Teams 1.5.6
Includes all updates from FiftyOne 0.23.5, plus:
- Improved dataset search user experience
- Post login redirects will now send the user to the correct page
Check out the release notes for a full rundown of additional enhancements and bugfixes.
Get involved in the FiftyOne open source community!
If you are working on computer vision use cases and unstructured data, the FiftyOne community is for you. There are tons of ways to get involved, for example:
FiftyOne Community Slack
With over 2,500 members, the community Slack channel is THE place to interact with the FiftyOne developers and exchange solutions with machine learning engineers doing computer vision in production.
To make it easy to catch the highlights, every Friday we recap interesting questions and answers from Slack in our Tips & Tricks blog series. Check out almost 300 tips and tricks in the archives like:
- 3D Detections – FiftyOne Tips and Tricks
- Exploring Polylines – FiftyOne Tips and Tricks
- Creating Pose Skeletons from Scratch – FiftyOne Tips and Tricks
- Dynamic Groups – FiftyOne Tips and Tricks
- Understanding Grouped Datasets
Computer Vision and AI, Machine Learning, and Data Science Meetups
Voxel51 sponsors 13 virtual Computer Vision Meetups and 12 AI, Machine Learning and Data Science Meetups around the world with over 20,000
members. (To join, visit the Meetup links and scroll down to find the location friendliest to your time zone.)
The 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. Our next Meetup is happening March 21:
- Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models – Andrew Owens at the University of Michigan
- Omnidirectional Computer Vision – Ciarán Eising at the University of Limerick & the D2iCE Research Group
- Illuminating the Underground World with Multimodal Algorithms – Adonaí Vera, Machine Learning Engineer
- The Role of AI in Fixing Hiring – Saurav Pandit, PhD at AI 2030
FiftyOne on GitHub
If you want to start contributing to the FiftyOne project resolving issues, reporting bugs or making enhancements to the Docs, check out these resources:
- Good first issues
- Building the Docs (video, instructions)
Industry Spotlight: Computer Vision in Retail
Check out the fifth installment of Voxel51’s computer vision industry spotlight blog series. In this series, we highlight how different industries — from construction to climate tech, from retail to robotics, and more — are using computer vision, machine learning, and artificial intelligence to drive innovation. We’ll dive deep into the main computer vision tasks being put to use, current and future challenges, and companies at the forefront.
In this edition, we’ll focus on retail! Check out the “How Computer Vision Is Changing Retail” blog to get the details!
