fiftyone-brain
FiftyOne Brain
Decision gist · record as of 2026-08-14
Yes. FiftyOne Brain is actively maintained, has low install friction, carries a permissive license, and addresses a real need in dataset analysis and ML workflows. It integrates well with the broader FiftyOne ecosystem and depends only on stable, widely-used scientific libraries. No known security vulnerabilities. Install it if you work with computer vision datasets and need systematic quality and similarity analysis.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Designed as part of the FiftyOne ecosystem; most functionality assumes a FiftyOne dataset object.
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache (permissive) — Apache License (permissive) means you can use, modify, and distribute this package freely in commercial and open-source projects with minimal restrictions.
last release 2026-08-11 (3 days) · last repo commit 2026-08-13 · 161 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 185,875 downloads/mo, #9,999 on PyPI
Alternatives
Verify before relying
pip install fiftyone-brain
import fiftyone.brain as fb
# Use brain capabilities on a FiftyOne dataset- Whether fiftyone-brain can be used standalone or requires the full fiftyone package installation
- Specific performance characteristics for large-scale datasets (scalability limits)
- Whether visual similarity search and other features require additional model downloads or setup
What it is and what it does
FiftyOne Brain is an AI/ML toolkit that extends the FiftyOne ecosystem with automated dataset and model analysis capabilities. It provides features like visual similarity search, text-based querying, detection of unique and representative samples, and identification of media quality issues and annotation mistakes. The package depends on numpy, scipy, and scikit-learn for its numerical and machine learning operations.
It is intended for data scientists and ML engineers working with computer vision and image datasets who need to systematically explore, validate, and improve their data quality. The package is actively maintained, supports current Python versions (3.10 through 3.14), and carries an Apache License that permits both commercial and open-source use.
Use it for
- Find visually similar images in a dataset to identify duplicates or near-duplicates
- Detect annotation errors and labeling inconsistencies across a dataset
- Identify representative or unique samples for active learning or model validation
- Analyze media quality issues such as blur, noise, or lighting problems
- Query datasets using natural language descriptions to locate relevant samples
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
FiftyOne Brain is actively maintained, has low install friction, carries a permissive license, and addresses a real need in dataset analysis and ML workflows. It integrates well with the broader FiftyOne ecosystem and depends only on stable, widely-used scientific libraries. No known security vulnerabilities. Install it if you work with computer vision datasets and need systematic quality and similarity analysis.
Install
fiftyone-brain on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Actively maintained with a release 3 days old and recent commits. Depends on numpy, scipy, and scikit-learn—all stable, widely-used scientific packages.
Requires Python 3.10 or later. Designed as part of the FiftyOne ecosystem; most functionality assumes a FiftyOne dataset object.
License in practice
Apache License (permissive) means you can use, modify, and distribute this package freely in commercial and open-source projects with minimal restrictions.
Quickstart
pip install fiftyone-brain
import fiftyone.brain as fb
# Use brain capabilities on a FiftyOne datasetVerify before relying
- Whether fiftyone-brain can be used standalone or requires the full fiftyone package installation
- Specific performance characteristics for large-scale datasets (scalability limits)
- Whether visual similarity search and other features require additional model downloads or setup
Package facts
| License | Apache permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesnumpyscipyscikit-learn |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 185,875 / month, #9,999 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Image ProcessingTopic :: Scientific/Engineering :: Image RecognitionTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: Visualization |
Evidence: fiftyone_brain-0.24.0-py3-none-any.whl
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