InsightFace
Open-source 2D and 3D face analysis: detection, recognition, alignment, and more.
About
InsightFace is a widely used open-source face analysis project maintained by Jia Guo and Jiankang Deng. It packages state-of-the-art face detection, recognition, alignment, age/gender estimation, and 3D face reconstruction behind a Python library with ONNX Runtime support, plus an Evaluation Studio desktop GUI and a C++ SDK (InspireFace).
The library code is MIT licensed for academic and commercial use, but the pretrained models are licensed for non-commercial research only, and face-swap model series such as inswapper require contacting the maintainers for licensing. The repository is one of the most starred computer-vision projects on GitHub.
Dual-use flag: this is the same technology family behind face-swap and deepfake tooling. The project itself is a legitimate research library, but face recognition and face swapping carry obvious misuse potential around identity fraud and non-consensual imagery; deployments should respect consent and applicable law.
What it can do
- Face detection and alignment (RetinaFace)
- Face recognition with ArcFace embeddings
- Age, gender, and attribute estimation
- 3D face reconstruction
- Evaluation Studio desktop GUI
- PrivateFrame local video face-blur workflows
Setup
pip install insightface (Python 3.10/3.11 recommended); pretrained models download automatically on first use.
Prerequisites
Python environment; GPU optional but recommended for video workloads.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 87; Trending score 78/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.