Featured Resource
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Getting Started with FiftyOne Workshop
April 16, 2025 | 9 AM PT
When and Where
April 16, 2025 | 9:00 – 10:30 AM Pacific
Virtually over Zoom. Sign up!
Register for the Zoom
About the Workshop
Want greater visibility into the quality of your computer vision datasets and models? Then join us for this free 90-minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset. At the end of the workshop you’ll be able to:
- Visualize complex datasets
- Explore embeddings
- Analyze and improve models
- Perform advanced data curation
- Integrations
This special AgTec edition of our “Getting Started with FiftyOne” workshop is designed for researchers, engineers, and practitioners working with visual data in agriculture. Through practical examples using a Colombian coffee dataset, you’ll gain a deep understanding of data-centric AI workflows tailored to the challenges of the AgTec space.
By the end of this workshop, you’ll be able to:
- Load and visualize agricultural datasets with complex labels
- Explore data insights interactively using embeddings and statistics
- Work with geolocation and map-based visualizations
- Generate high-quality annotations with the Segment Anything Model (SAM2)
- Evaluate model performance and debug predictions using real AgTec scenarios
Prerequisites: working knowledge of Python and basic computer vision concepts.
All attendees will get access to the tutorials, videos, and code examples used in the workshop
About the Instructor
Paula Ramos, PhD
Voxel51
Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. During her PhD and Postdoc research, she deployed multiple low-cost, smart edge & IoT computing technologies, such as farmers, that can be operated without expertise in computer vision systems. The central objective of Paula’s research has been to develop intelligent systems/machines that can understand and recreate the visual world around us to solve real-world needs, such as those in the agricultural industry.