# liuliu/ccv

C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library

Repository: https://github.com/liuliu/ccv
Canonical: https://ross.abutalabs.com/products/ccv
Homepage: http://libccv.org
Language: C++
License: NOASSERTION
License Family: other
Last push: 2026-08-26T05:51:58+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 5831, "days_push": 7, "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 7243, forks 1704 (observed 2026-08-28T04:09:57.777163+00:00)

## What it is
ccv is a modern, minimalist computer vision library written in C/C++ with an application-driven set of state-of-the-art algorithms including face detection, object detection and tracking, text detection, and feature extraction. It is highly portable and embeddable, running on nearly any platform with a C compiler and requiring almost no dependencies, with a built-in cache for transparent image preprocessing.

## Use cases
- detect faces in images
- detect pedestrians and cars in images
- track objects over long-term video
- extract SIFT feature points from images
- detect text regions in natural images
- run convolutional network image classifiers
- embed computer vision in mobile or embedded apps

## When to choose
- you need a dependency-light, easily deployable C computer vision library
- you target mobile or embedded platforms like iOS, Android, or Raspberry Pi
- you need battle-tested implementations of face detection, tracking, or feature extraction
- you want server-side integration with minimal build complexity

## When to avoid
- you need the breadth of algorithms and ecosystem of OpenCV
- you want high-level Python-first APIs or extensive GPU acceleration out of the box
- you need cutting-edge deep learning models rather than classical CV plus ConvNet support

## Facets
- artifact type: library
- maturity: active
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, image-processing, machine-learning
- platform: windows, cross-platform, cpp, c
- tags: face-detection, object-detection, object-tracking, text-detection, sift, convnet, embeddable, minimal-dependencies, linux, macos, android, ios

## Member repositories
- liuliu/ccv (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:57.777163+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 2026-08-29T17:39:44.738629+00:00, confidence not recorded.
  - readme: https://github.com/liuliu/ccv (fetched 2026-08-28T04:09:57.777163+00:00, sha 45e79ae023d8)
  - homepage: http://libccv.org (fetched 2026-08-29T08:34:31.051483+00:00, sha 8a2ff13ba971)
  - site_page: https://libccv.org/doc (fetched 2026-08-29T08:34:31.054026+00:00, sha dcf400ce259f)
- Data as of 2026-08-30T08:39:29.467469+00:00.