How does visualization work in FiftyOne? | Voxel51
How does visualization work in FiftyOne? Eric Hofesmann, founding ML engineer and product managerat Voxel51, explains how FiftyOne works as a data flywheel platform for physical AI, and why visualization is only the first step. FiftyOne is agnostic to the type of data you're working with. Bring in road scene images for automotive perception, manufacturing parts for defect detection, medical imagery for classification, or robot episodes with multiple cameras, depth maps, 3D points, and joint states. Then query your entire dataset, filter on custom metadata, and jump straight to the subset you need. This is the first video in FiftyOne Questions, a series where each video answers one question about FiftyOne and Voxel51, our enterprise offering. 📝 Read the full post, with all three videos: voxel51.com/blog/in-app-annotation-fiftyone ⏱️ Chapters 0:00 Meet Eric 0:53 FiftyOne is a data flywheel 1:12 One platform for automotive, manufacturing, and medical data 1:37 Multimodal data: images, video, 3D, time series, and sensors 2:12 Query and filter your entire dataset 2:47 What the fastest teams to production have in common ▶️ Next in the series What can I annotate in FiftyOne? https://youtu.be/WrrThA30S5I How do I annotate a dataset in FiftyOne? https://youtu.be/LABk0yzGbTY 🔗 Learn more What is a data flywheel? https://voxel51.com/glossary/data-flywheel FiftyOne open source: https://voxel51.com/fiftyone Voxel51 for annotation at scale: https://voxel51.com/annotation Docs: https://docs.voxel51.com Get started: pip install fiftyone 💬 Join the community: https://community.voxel51.com FiftyOne is the open source multimodal data platform for physical AI. Voxel51 is the enterprise platform built on it, adding annotation workflows, auto labeling, GPU-backed models, and team collaboration. Together they help ML teams curate, annotate, and evaluate data for visual AI and physical AI models, across images, video, 3D, and multimodal sensor data. #FiftyOne #PhysicalAI #MultimodalAI