# seetaface/SeetaFaceEngine

Repository: https://github.com/seetaface/SeetaFaceEngine
Canonical: https://ross.abutalabs.com/products/seetafaceengine
Language: C++
License: NOASSERTION
License Family: other
Last push: 2020-04-04T10:57:01+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": 3641, "days_push": 2342, "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 4636, forks 1750 (observed 2026-08-28T04:08:55.420930+00:00)

## What it is
SeetaFace Engine is an open-source C++ face recognition engine comprising face detection, face alignment, and face identification modules. It runs entirely on CPU with no third-party dependencies and is released under a BSD-2 license.

## Use cases
- detect faces in images in real time
- find facial landmarks in photos
- compare two face images to verify identity
- build a face recognition system without GPU
- embed face recognition in a C++ application with no external dependencies

## When to choose
- you need CPU-only face detection, alignment, and recognition in C++
- you want a dependency-free, BSD-licensed face recognition stack
- you are doing academic research on face recognition

## When to avoid
- you need state-of-the-art accuracy on modern benchmarks
- you want GPU acceleration or active community maintenance
- you need a Python-first or production-supported SDK

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, artificial-intelligence, image-processing
- platform: cpp, windows, cross-platform
- tags: face-recognition, face-detection, facial-landmarks, cpu-only, no-third-party-dependencies, c-plus-plus, linux, macos

## Member repositories
- seetaface/SeetaFaceEngine (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:55.420930+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 2026-08-29T18:19:34.424997+00:00, confidence not recorded.
  - readme: https://github.com/seetaface/SeetaFaceEngine (fetched 2026-08-28T04:08:55.420930+00:00, sha d4a41d0e2972)
- Data as of 2026-08-30T08:39:29.467469+00:00.