Overview of maximizing the potential of the FiftyOne open-source SDK and App to efficiently store and annotate training data for Generative AI workflows, including cloud-based storage/hosting architecture, training/apply models for semi-automatic data annotation, and CVAT integration for pixel-perfect side-by-side evaluation.

In this talk we’ll explore how we maximize the potential of the FiftyOne open source SDK and App to efficiently store and annotate training data critical to Finegrain’s Generative AI workflows. We will provide an overview of our cloud-based storage and hosting architecture, showcase how we leverage FiftyOne for training and applying models for semi-automatic data annotation, and demonstrate how we extend the CVAT integration to enable pixel-perfect side-by-side evaluation of our Generative AI models.

Hands-on introduction to FiftyOne: load datasets from the FiftyOne Dataset Zoo; navigate the FiftyOne App; programmatically inspect attributes of a dataset; add new sample and custom attributes to a dataset; generate and evaluate model predictions; save insightful views into the data.

The second half provides a hands-on introduction to FiftyOne: Load datasets from the FiftyOne Dataset Zoo; Navigate the FiftyOne App; Programmatically inspect attributes of a dataset; Add new sample and custom attributes to a dataset; Generate and evaluate model predictions; Save insightful views into the data.

Hands-on workshop to learn how to leverage the FiftyOne computer vision toolset. Topics include FiftyOne Basics (terms, architecture, installation, and general usage); overview of useful workflows to explore, understand, and curate data; how FiftyOne represents and semantically slices unstructured computer vision data. The second half is a hands-on introduction to FiftyOne, where you will learn how to load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes, add new samples and custom attributes, generate and evaluate model predictions, and save insightful views into the data.

Two-part workshop led by Dan Gural. Part 1 covers FiftyOne basics (terms, architecture, installation, general usage), an overview of useful workflows to explore, understand, and curate data, and how FiftyOne represents and semantically slices unstructured computer vision data. Part 2 is a hands-on introduction to FiftyOne: loading datasets from the FiftyOne Dataset Zoo, navigating the FiftyOne App, programmatically inspecting attributes, adding new samples and custom attributes, generating and evaluating model predictions, and saving insightful views into the data. Prerequisites: working knowledge of Python and basic computer vision. Attendees will gain access to tutorials, videos, and code examples used in the workshop.

A hands-on introduction to FiftyOne: load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes of a dataset, add new samples and custom attributes to a dataset, generate and evaluate model predictions, and save insightful views into the data.