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Event

Jan '24 - Getting Started with FiftyOne Computer Vision Workshop

2024-01-31 – 2024-01-31 Meetup Visit website ↗

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When January 31, 2024 at 9 AM Pacific / 12 PM Eastern for 90 mins

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/fiftyone-workshop-1-31-2024/

Want greater visibility into the quality of your computer vision datasets and models? Then join Leila Kaneda, customer-facing Machine Learning Engineer at Voxel51, for this free 90 minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.

In the first part of the workshop we’ll cover:

  • FiftyOne Basics (terms, architecture, installation, and general usage)
  • An overview of useful workflows to explore, understand, and curate your data
  • How FiftyOne represents and semantically slices unstructured computer vision data

The second half will be 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 of a dataset
  • Add new sample and custom attributes to a dataset
  • Generate and evaluate model predictions
  • Save insightful views into the data

Prerequisites are a working knowledge of python and basic computer vision. All attendees will get access to the tutorials, videos, and code examples used in the workshop.

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FiftyOne Workshop: FiftyOne Basics and Hands-on Introduction

2024-01-31
workshop
Leila Kaneda (Voxel51)

A 90-minute hands-on workshop on the FiftyOne computer vision toolset. Part 1 covers FiftyOne Basics (terms, architecture, installation, and 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 where you load datasets from the FiftyOne Dataset Zoo, navigate the FiftyOne App, programmatically inspect attributes of a dataset, add new samples and custom attributes, generate and evaluate model predictions, and save insightful views into the data. Prerequisites: working knowledge of Python and basic computer vision.