# flann-lib/flann

Fast Library for Approximate Nearest Neighbors

Repository: https://github.com/flann-lib/flann
Canonical: https://ross.abutalabs.com/products/flann
Homepage: http://people.cs.ubc.ca/~mariusm/flann
Language: C++
License: NOASSERTION
License Family: other
Last push: 2024-07-29T19:01:47+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 5637, "days_push": 765, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2373, forks 662 (observed 2026-08-28T04:06:41.906441+00:00)

## What it is
FLANN is a C++ library for fast approximate nearest neighbor searches in high-dimensional spaces. It bundles multiple search algorithms with automatic algorithm and parameter selection, plus bindings for C, MATLAB, Python, and Ruby.

## Use cases
- find approximate nearest neighbors in high-dimensional data
- speed up kNN search for large feature datasets
- match image feature descriptors like SIFT
- automatically pick the best NN search algorithm and parameters
- use nearest neighbor search from Python or MATLAB

## When to choose
- you need fast approximate NN search in C++ with multi-language bindings
- your dataset is high-dimensional and exact search is too slow
- you want automatic algorithm/parameter tuning out of the box

## When to avoid
- you need exact nearest neighbor results
- you want a modern, actively developed library with recent features
- you need GPU-accelerated similarity search

## Facets
- artifact type: library
- maturity: maintenance
- function: search-engine, machine-learning
- domain: machine-learning, computer-vision
- platform: cpp, python, cross-platform
- tags: nearest-neighbor-search, ann, knn, high-dimensional, bindings, algorithms

## Member repositories
- flann-lib/flann (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:41.906441+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:35:05.948514+00:00, confidence not recorded.
  - readme: https://github.com/flann-lib/flann (fetched 2026-08-28T04:06:41.906441+00:00, sha f8bdf87ea30e)
- Data as of 2026-08-30T08:39:29.467469+00:00.