Registry / ai-ml / fiftyone-brain

fiftyone-brain

library0.22.0pypypiunverified

The FiftyOne Brain extends the FiftyOne ecosystem with powerful machine learning capabilities for data curation and model analysis. It provides features like visual similarity search, text-based querying, finding unique and representative samples, detecting media quality issues, and identifying annotation mistakes. The library is actively developed, with frequent releases.

ai-ml vector-search data

pip install fiftyone-brain

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · FIFTYONE-BRAIN

fiftyone-brain

ai-mlpythonv0.22.0

Install

25.9s avg

Import

9346ms

Disk

930MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.22.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.940 runs

build_error

glibc

py 3.10–3.940 runs

installs and imports cleanly · install 25.9s · import 9.346s · 904MB

930MB installed

● package 930MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

fob

✓ import fiftyone.brain as fob

✗ import fiftyone.brain as fob

This quickstart demonstrates how to load a dataset, compute a low-dimensional visualization of its embeddings using UMAP, and then compute a visual similarity index, which are core functionalities of FiftyOne Brain. The visualization can then be explored interactively in the FiftyOne App.

import fiftyone as fo import fiftyone.brain as fob import fiftyone.zoo as foz # Load a sample dataset dataset = foz.load_zoo_dataset("quickstart", max_samples=100) # Compute a 2D visualization of the dataset embeddings print("Computing visualization...") results = fob.compute_visualization( dataset, brain_key="quickstart_viz", method="umap" # Requires `pip install umap-learn` ) print(f"Visualization results stored under brain key: {results.key}") # You can then launch the FiftyOne App to view the visualization # session = fo.launch_app(dataset) # session.wait() # Compute visual similarity index print("Computing similarity index...") fob.compute_similarity( dataset, brain_key="quickstart_similarity", model="clip-vit-base32-torch" # Requires `pip install fiftyone-embeddings` ) print(f"Similarity index computed for brain key: quickstart_similarity")

Debug

Known issues

gotchaWhen re-running a FiftyOne Brain method like `compute_visualization` or `compute_similarity`, if you use the same `brain_key` as a previous run, it will raise a `ValueError`.

fix

Before re-running, either delete the existing run with `dataset.delete_brain_run("your_brain_key")` or provide a new, unique `brain_key`.

affects: All versions

gotchaThe `compute_visualization` method, when using `method="umap"`, requires the `umap-learn` package to be installed separately.

fix

Install the `umap-learn` library: `pip install umap-learn`.

affects: All versions

breaking`compute_visualization` with `TSNE` had compatibility issues with `scikit-learn` versions older than 1.7.0.

fix

Upgrade `fiftyone-brain` to v0.21.4 or newer, or ensure `scikit-learn` is at least 1.7.0 if using an older `fiftyone-brain` version.

affects: <0.21.4

gotchaIf a `brain_key` is not explicitly provided when computing a Brain method, the run will not be persisted on your dataset and will not be accessible via the FiftyOne App.

fix

Always provide a descriptive `brain_key` when calling `compute_visualization`, `compute_similarity`, etc., to ensure the results are saved and accessible.

affects: All versions

gotchaTo use certain embedding models with `compute_similarity` (e.g., 'clip-vit-base32-torch'), you might need to install additional FiftyOne plugins or packages like `fiftyone-embeddings`.

fix

Check the FiftyOne documentation for specific model requirements. Often, `pip install fiftyone-embeddings` or related model-specific packages are needed.

affects: All versions

Upgrade

Version history

0.22.0latest on PyPI · released Jun 3, 2026

Audit

Dependencies

fiftyonerequiredFiftyOne Brain is a core component and extension of FiftyOne, and is often installed alongside it or as part of it.

umap-learnoptionalRequired for using the 'umap' method in compute_visualization.

Agent activity

50 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/voxel51/fiftyone-brain ↗

packagehttps://pypi.org/project/fiftyone-brain/ ↗

homepagehttps://fiftyone.ai ↗