Open source AI face-changing tool that supports high-quality Face Recognition

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InsightFace supports high-quality Face Recognition and face alignment, including face exchange services and cross-platform SDK development.

this project InsightFace(maintained by the deepinsight team) is an open source 2D and 3D facial depth analysis toolbox, mainly based on PyTorch and MXNet implementation. It covers multiple core tasks related to faces. The main modules and functions are as follows:

🛠Core modules

1. Face Recognition

  • A variety of mainstream identification methods and loss functions have been implemented, including ArcFace (CVPR 2019), SubCenter-ArcFace (ECCV 2020), VPL (CVPR 2021), Partial‑FC (CVPR 2022), etc.
  • Supports multiple network backbones, such as IResNet, MobileFaceNet, DenseNet, etc.
  • Provide pre-trained models and complete evaluation tools (such as IJB, Megaface).

2. Face detection

  • Including methods such as RetinaFace (CVPR 2020), SCRFD (High-Efficiency Detection) and BlazeFace.
  • Support complete training, evaluation and reasoning processes.

3. Face Alignment

  • Two key point regression methods, SDUNets (BMVC 2018) and SimpleRegression, have been implemented.
  • A landmark testing process is also provided.

4. 3D facial analysis

  • Participated in the first place in the ECCV 2022 Monocular 3D Facial Reconstruction Competition.

5. Face Swaping

  • provide inswapper_cyn、inswapper_dax、inswapper_512_live High-performance face exchange models such as Picsi.Ai and Discord robots.

📈Latest developments

  • 2025‑03‑02 released inswapper‑512‑live(Real-time face exchange model).
  • 2024‑08‑01 Integrate the latest face exchange models into the Picsi.Ai service.
  • 2024‑05‑04 Released the cross-platform SDK “InspireFace”, which supports C/C++ and multiple inference backends.
  • In 2022, he won the first place in the ECCV 3D Reconstruction Challenge for the first time, and in 2021, he won the first place in the NIST-FRVT Face Recognition Cash Competition.

ˇ How to get started️

  • Support pip installation:pip install -U insightface。
  • Support PyPI packages, command-line demos (such as ArcFace video demos), sample code, and more.
  • Depends on Python 3.x, PyTorch ≥1.6, or MXNet 1.6 – 1.8.
  • The warehouse contains rich code, dataset interfaces, pre-trained model download scripts, evaluation tools, etc.

Applicable scenarios

  • Facial recognition system development: Generate embedding and build recognition, comparison, and verification processes.
  • Face detection and key point location: Support MTCNN, RetinaFace, SCRFD, etc.
  • Face alignment, 3D reconstruction and deformation: suitable for AR, animation, panoramic reconstruction, etc.
  • Face exchange: Used for face-changing applications or content generation research in videos/photos.

summary

InsightFace is a comprehensive, open source and continuously active facial intelligent analysis platform covering the entire process of recognition, detection, alignment, reconstruction and face replacement, and is suitable for scientific and commercial research. It provides modularity, pre-training models, standard evaluation and easy-to-use interfaces, and is a tool for implementing face-related technologies.

Project address: Click to open (https://github.com/deepinsight/insightface)
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