Home Projects face-alignment
face-alignment
Python

face-alignment

:fire: 2D and 3D Face alignment library build using pytorch

by 1adrianb · GitHub
Stars
Forks
Created
Last commit
Language
deep-learningface-alignmentface-detectionBSD-3-ClausePython
View on GitHub
In plain words

Detect facial features in images using a library that works with both 2D and 3D coordinates.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
face-alignment — GitHub preview card
📈 Star history
7.53k7.52k
2026-07-042026-08-31
📈 Track face-alignment

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

:fire: 2D and 3D Face alignment library build using pytorch

face-alignment has 7.5k stars on GitHub. It has been forked 1.4k times. face-alignment is written mainly in Python. It has been in active development since 2017. face-alignment is available under the BSD-3-Clause license. Its main topics are deep-learning, face-alignment, face-detection, face-detector.

Frequently asked questions

What is face-alignment?

:fire: 2D and 3D Face alignment library build using pytorch

Is face-alignment open source?

face-alignment is an open-source project. It is released under the BSD-3-Clause license.

Is face-alignment free?

Yes. face-alignment is free and open source — you can use, modify and self-host it.

What license does face-alignment use?

face-alignment is available under the BSD-3-Clause license.

What language is face-alignment written in?

face-alignment is written mainly in Python.

🏅 Maintainer of this project?
olud.ai badge — face-alignment

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=1adrianb-face-alignment)](https://olud.ai/project/1adrianb-face-alignment.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.