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FiftyOne

Open-source toolkit for curating datasets and evaluating visual AI models

at a glance
verified specs
Pricing Model
freemium
License
Open Source
Telemetry
Concerns reported
Last Verified
Aug 26, 2026
Supported Platforms
Python library installed via `pip install fiftyone`; runs locally and launches a browser-based App. Integrates with PyTorch, TensorFlow, Hugging Face, and Ultralytics, cloud storage (S3, GCS, Azure), annotation tools (CVAT, Label Studio, Labelbox, V7), and vector databases (Qdrant, Pinecone, Redis, MongoDB).
Primary Categories
AI Data Tools
Tags
Computer Vision, Open Source, Machine Learning, Data Quality, Embeddings

FiftyOne is an open-source Python toolkit from Voxel51 for building high-quality datasets and better computer-vision and multimodal AI models. It pairs a browser-based visualization App with programmatic dataset curation, embeddings, similarity search, and model-evaluation workflows.

FiftyOne is an open-source platform, developed by Voxel51, for exploring, curating, and improving datasets used to train computer-vision and multimodal AI models. Its core is a Python library (installed with `pip install fiftyone`) built around a Dataset/Sample data model that stores images, videos, 3D/point-cloud data, and time-series alongside their metadata, labels, and model predictions. A browser-based FiftyOne App lets teams visualize and filter that data side-by-side with annotations and predictions in a single interactive view.

Beyond visualization, the FiftyOne Brain adds machine-learning-powered analytics for data-centric workflows: image and object embeddings for dimensionality reduction, similarity and duplicate search, uniqueness scoring to surface the most informative samples, and mistakenness detection to find likely annotation errors. Dedicated model-evaluation workflows let teams compare models, drill from aggregate metrics down to individual failing samples, and isolate edge cases, positioning FiftyOne as a curation-and-debugging layer rather than a labeling tool in its own right.

The project is designed to sit inside an existing ML stack via a plugin and operator framework and a broad set of integrations. Documented integrations span annotation tools (CVAT, Label Studio, Labelbox, V7), cloud storage (AWS S3, Google Cloud, Azure), vector databases (Qdrant, Pinecone, Redis, MongoDB), ML frameworks (PyTorch, TensorFlow), and model hubs (Hugging Face, Ultralytics), so datasets curated in FiftyOne can flow into labeling, similarity search, and training pipelines.

FiftyOne ships as a free Apache-2.0 open-source core, with a commercial FiftyOne Enterprise offering (marketed in Team, Growth, and Custom tiers) that adds collaboration, role-based access control, dataset versioning, and flexible deployment options including cloud, hybrid, on-premise, and air-gapped setups; Enterprise pricing is not published and is quoted via sales. By default the open-source package emits UUID-based import and App usage analytics, which can be disabled with the `do_not_track` config field or the `FIFTYONE_DO_NOT_TRACK` environment variable.

Pricing & Platform Specs

Pricing Summary

FiftyOne is free and open-source under the Apache License 2.0 for local computer vision workflows. Voxel51 provides FiftyOne Enterprise with custom quote-based pricing for team collaboration, RBAC, and cloud compute orchestration.

full pricing breakdown →

Supported Platforms

Python library installed via `pip install fiftyone`; runs locally and launches a browser-based App. Integrates with PyTorch, TensorFlow, Hugging Face, and Ultralytics, cloud storage (S3, GCS, Azure), annotation tools (CVAT, Label Studio, Labelbox, V7), and vector databases (Qdrant, Pinecone, Redis, MongoDB).

Categories

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freemiumOpen Source

Multimodal data labeling and curation for production AI

Encord is a data labeling and curation platform for teams building production AI systems with complex multimodal data. It supports image, video, audio, DICOM medical imaging, and 3D point cloud annotation with AI-assisted labeling, advanced ontology management, and quality assurance workflows. Features active learning for prioritizing high-value samples and integrates with major ML frameworks.

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Data factory for AI teams and model training

Labelbox is a comprehensive data platform for AI teams handling reinforcement learning, evaluations, robotics, and human feedback workflows. Core capabilities include RL data generation with knowledge work rubrics, custom evaluations for private benchmarks and model comparisons, robotics data with full-stack video and trajectories, and an expert network of 1.5M+ knowledge workers including 50K+ PhDs. Trusted by 80% of leading AI labs for production data operations.

freemium

Sources & verification

Sources checked
Content verified

Verification dates are editorial checks. Routine CMS saves and automatic updatedAt timestamps do not advance them.

FAQ

What is FiftyOne?

FiftyOne is an open-source Python toolkit from Voxel51 for building high-quality datasets and better computer-vision and multimodal AI models. It pairs a browser-based visualization App with programmatic dataset curation, embeddings, similarity search, and model-evaluation workflows.

Is FiftyOne free?

FiftyOne offers a free tier alongside paid plans. FiftyOne is free and open-source under the Apache License 2.0 for local computer vision workflows. Voxel51 provides FiftyOne Enterprise with custom quote-based pricing for team collaboration, RBAC, and cloud compute orchestration.

Is FiftyOne open source?

Yes — FiftyOne is open source.

Is FiftyOne still maintained?

Yes — FiftyOne is active. Its listing was last verified on August 26, 2026.

What are the best FiftyOne alternatives?

The first editor-selected FiftyOne alternatives are Label Studio, Encord, Labelbox.