voxel51/fiftyone
Refine high-quality datasets and visual AI models observed · 2026-08-28
Health v2 · maintenance only
99/100
- Activity 99
- Release rhythm 98
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 13
- age_days: 2324
- days_rel: 14
- days_push: 7
- n_releases_24m: 46
Adoption not part of the score
11042 stars · 817 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
FiftyOne is an open-source Python library and GUI app for building high-quality computer vision datasets and models. It enables visualizing, curating, annotating, and evaluating image, video, and 3D datasets alongside model predictions.
Use cases
- visualize and explore image and video datasets with labels and predictions
- curate and clean datasets by finding duplicate, mislabeled, or low-quality samples
- evaluate object detection and classification models and analyze failure cases
- send data to annotation backends like CVAT or Label Studio
- run vector similarity search over unstructured visual data
- manage 3D point cloud and LiDAR datasets for autonomous driving
- perform active learning to select the most informative samples for labeling
When to choose
- you are building or refining computer vision datasets and need visual inspection
- you need to compare model predictions against ground truth and find error patterns
- you want a Python-first workflow with an interactive GUI for data curation
- you work with multimodal data including images, videos, and 3D point clouds
When to avoid
- you need a fully managed multiuser collaborative platform out of the box (consider FiftyOne Enterprise)
- your project is NLP-only with no visual data
- you need lightweight batch processing without any GUI or visualization
Facets
library · maturity active
data-science machine-learning computer-vision data-visualization image-processing video-processing search-engine vector-database developer-tools computer-vision machine-learning data-science artificial-intelligence deep-learning developer-tools python cross-platform windows data-centric-ai dataset-curation model-evaluation annotation active-learning object-detection image-classification vector-search data-quality visual-ai point-clouds 3d-vision macos linux docker
10 sources
- readme: https://github.com/voxel51/fiftyone · fetched 2026-08-28 · b5d172776ad7
- homepage: https://fiftyone.ai · fetched 2026-08-29 · 1aa94df1b23f
- site_page: https://docs.voxel51.com/ · fetched 2026-08-29 · 4633938689da
- site_page: https://docs.voxel51.com:443/installation/index.html · fetched 2026-08-29 · 66f3ee765f56
- site_page: https://docs.voxel51.com:443/installation/environments.html · fetched 2026-08-29 · 483288f0cfb6
- site_page: https://docs.voxel51.com:443/installation/virtualenv.html · fetched 2026-08-29 · cb63c497b19c
- site_page: https://docs.voxel51.com:443/installation/upgrading-mongodb.html · fetched 2026-08-29 · 3393ce7e5431
- site_page: https://docs.voxel51.com:443/installation/troubleshooting.html · fetched 2026-08-29 · 12cf27ad7a19
- site_page: https://docs.voxel51.com:443/getting_started/annotation/01_quickstart.html · fetched 2026-08-29 · 58b076dc052d
- site_page: https://voxel51.com/integrations · fetched 2026-08-29 · b7f180abfee6
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| voxel51/fiftyone | main | 99 |
For agents
markdown · JSON · MCP: product_card(name="voxel51/fiftyone")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem