DeepFace vs Sigal
A side-by-side comparison of two self-hosted photo management options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
DeepFace
Face recognition and facial attribute analysis framework
VS
Sigal
Simple static photo gallery generator written in Python
| Feature | DeepFace | Sigal |
|---|---|---|
| Category | Photo Management | Photo Management |
| License | MIT | MIT |
| Language | Python | JavaScript |
| Setup difficulty | Medium | Easy |
| Min. RAM | 2,048 MB | 128 MB |
| Deployment | docker, bare-metal | bare-metal |
| GitHub stars | ★ 23,222 | ★ 942 |
| First released | 2020 | 2012 |
| Replaces | AWS Rekognition, Azure Face API | Flickr |
Why pick each one
Choose DeepFace if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 23.2k GitHub stars
- Written in Python
Frequently asked questions
Is DeepFace or Sigal better?
Neither is universally better. DeepFace has the larger community, while Sigal is simpler to set up (easy difficulty). Choose based on the comparison table above and your own setup.
Are DeepFace and Sigal free and open-source?
Yes. DeepFace is licensed under MIT and Sigal under MIT. Both can be self-hosted at no software cost.
Can I run DeepFace and Sigal with Docker?
DeepFace: yes. Sigal: check the project docs for container support.