How to Annotate Data in FiftyOne: In-App Annotation Walkthrough

FiftyOne is presented as a data-flywheel platform for visualizing, curating, annotating, and evaluating multimodal physical AI datasets, including images, video, 3D point clouds, sensor streams, and robotics episodes. Its open-source tools support per-sample annotation for classifications, bounding boxes, segmentation masks, polylines, 3D cuboids, and custom label attributes, while users can define schemas with a field name, label type, and classes before annotating. The walkthrough uses 27,558 malaria-cell images to demonstrate image-level infection classification and parasite segmentation, using manual brushes and polygons as well as click-to-segment assistance from SAM 2, which can be refined with positive and negative points. FiftyOne also supports custom plugins, such as tools for editing vision-language-model captions associated with robot episodes. For large-scale annotation, Voxel51’s enterprise offering adds collaborative workflows, annotation workforces, GPU-backed larger models, and auto-labeling models or agents, aiming to help teams prioritize important subsets, identify model failures, and iteratively improve training data without leaving the platform.

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