visual-layer/fastdup
fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both images and labels, while significantly reducing data operation costs, all with unmatched scalability. observed · 2026-08-28
Health v2 · maintenance only
67/100
- Activity 99
- Release rhythm 8
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1575
- days_rel: n/a
- days_push: 10
- n_releases_24m: 0
Adoption not part of the score
1904 stars · 93 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
fastdup is a free Python tool for rapidly analyzing image and video datasets to surface duplicates, outliers, broken, dark, bright, blurry, and mislabeled images, plus visual clusters. It scales to large datasets on CPU and helps improve dataset and label quality while cutting data operation costs.
Use cases
- find duplicate images in a dataset
- detect outliers and broken images before training
- find mislabeled images in an image classification dataset
- cluster visually similar images for exploration
- clean and curate a large image or video dataset
- run visual similarity search over a photo collection
- reduce dataset storage by removing redundant frames
When to choose
- you need to audit and clean large image/video datasets quickly on CPU
- you want duplicate, outlier, and quality issue detection in a few lines of Python
- you are preparing computer vision training data and want better labels
When to avoid
- you need a permissively licensed tool for commercial redistribution (CC BY-NC-ND)
- you need a full GUI dataset management platform rather than a Python library
- you work with non-visual data like text or tabular datasets
Facets
library · maturity active
image-processing machine-learning data-science search-engine computer-vision machine-learning data-science image-processing python windows data-curation duplicate-detection outlier-detection image-similarity dataset-quality visual-search computer-vision linux macos
10 sources
- readme: https://github.com/visual-layer/fastdup · fetched 2026-08-28 · c980d865c9e1
- homepage: https://docs.visual-layer.com/fastdup_docs_old/First%20Steps/getting-started · fetched 2026-08-29 · db11b9b852e1
- site_page: https://docs.visual-layer.com/docs/introduction/key-concepts · fetched 2026-08-29 · 862049e86bf0
- site_page: https://docs.visual-layer.com/docs/release-notes/release-notes · fetched 2026-08-29 · 6cd4a095e916
- site_page: https://docs.visual-layer.com · fetched 2026-08-29 · c9a467b55d35
- site_page: https://docs.visual-layer.com/docs/introduction/introduction · fetched 2026-08-29 · 508c9eb2ced4
- site_page: https://docs.visual-layer.com/docs/self-hosting/System_requirements · fetched 2026-08-29 · f68dbf3f0fb1
- site_page: https://docs.visual-layer.com/docs/introduction/prerequisites · fetched 2026-08-29 · 6109cb6bb318
- site_page: https://docs.visual-layer.com/docs/quick-start/tutorial-create-dataset · fetched 2026-08-29 · 427b383ff7d4
- site_page: https://docs.visual-layer.com/docs/quick-start/understanding-clusters · fetched 2026-08-29 · 54a4bae91ade
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| visual-layer/fastdup | main | 67 |
For agents
markdown · JSON · MCP: product_card(name="visual-layer/fastdup")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem