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Face Recognition

Face Recognition is an MIT-licensed Python library and command-line tool for detecting, recognizing and manipulating faces in images, using dlib’s deep-learning-based face-recognition implementation.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Face Recognition — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when an application needs a Python or CLI component for face detection, facial landmarks or image-based face comparison.

Who it is for

  • Python developers building image-processing applications
  • Teams creating command-line face-detection or identification workflows
  • Developers prototyping local face matching with dlib-backed recognition

Documented uses

  • Find faces in photographs or folders of photographs
  • Extract facial landmarks such as eyes, nose, mouth and chin outlines
  • Create face encodings and compare unknown images with known faces
  • Add face recognition to Python-based or command-line image workflows
Before you choose

Requirements & limits

The repository is public and lists an MIT license. The documented installation path covers macOS and Linux; Windows is not officially supported. Platform-specific instructions are also provided for FreeBSD, Raspberry Pi 2+ and Nvidia Jetson Nano.

  • Python and dlib are central prerequisites for the documented installation path.
  • The project exposes both Python functions and separate face_recognition and face_detection command-line programs.
  • Command-line recognition requires one named reference image for each known person.
  • The repository documents facial landmarks as well as detection and recognition, allowing broader image-processing workflows.
  • The implementation is MIT licensed according to the repository metadata.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up Face Recognition on macOS or Linux

Prepare the documented Python library and command-line tools for local use.

Before you start

  • Python 3.3+ or Python 2.7
  • macOS or Linux
  • dlib with Python bindings
  • CMake

Steps

  1. Install dlib with its Python bindings using the project’s macOS or Ubuntu instructions.

  2. Install CMake.

  3. Install the module with pip3, or pip2 for Python 2.

  4. Use the installed face_recognition and face_detection command-line programs for the documented image workflows.

Expected outcome

The library and its two command-line programs are installed for face recognition and face detection workflows.

Guide limitations

  • Windows is not officially supported.
  • The source documents installation and command-line usage, but this guide does not establish a successful local run.
  • The command-line recognition workflow requires a folder with one image per known person, with filenames identifying them.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
1 October 2026
Original website title
ageitgey/face_recognition · Official homepage title · retained in its source language
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