#Face Recognition

The project provides an accurate method for detecting 2D and 3D facial landmarks through Python, utilizing FAN's deep learning techniques. It is compatible with several face detectors such as SFD, Dlib, and BlazeFace and can handle batch processing for directories. Operating efficiently on both CPU and GPU, it is optimized for devices with CUDA capabilities. Users can select different precision settings to improve performance. The installation is simple via pip or conda, with options for source builds and Docker support. User contributions and feedback are welcomed to enhance the project.

InsightFace provides an open-source toolbox for 2D and 3D face analysis using advanced algorithms. It offers solutions in face recognition, detection, and alignment, along with face-swapping capabilities. The latest updates feature face-swapping models in the Picsi.Ai service and the release of the InspireFace SDK. Aimed at research and commercial use under the MIT License, it supports cross-platform development. Discover innovative methods such as ArcFace and Partial FC.

Facenet implements face recognition using TensorFlow, inspired by renowned academic works. It supports TensorFlow r1.7 and Python 3.x/2.7 environments, featuring models trained on CASIA-WebFace and VGGFace2, offering high accuracy through MTCNN-aligned data. This project is suited for developing scalable face recognition systems with comprehensive training resources.

Explore efficient face recognition in Pytorch with pretrained Inception ResNet (V1) and MTCNN models on VGGFace2 and CASIA-Webface. This repository offers complete pipelines for detection, recognition, and video tracking, supporting easy integration via Docker and Git with automatic pretrained weight downloads.

Explore the latest on-premise Face SDK tailored for Linux servers featuring face recognition, liveness detection, and face attribute analysis. Perfect for integrating into eKYC and CCTV systems, this SDK aids in fraud prevention and offers deep demographic insights. Access practical Docker demos and various deployment strategies. Try Recognito's API with free trials and utilize comprehensive documentation for effective implementation. Designed specifically for Linux, meet the required system specifications for reliable identity verification and security tasks.

Explore the TensorFlow 101 project to learn various deep learning applications with comprehensive tutorials and practical examples. Diverse models like VGG-Face and FaceNet are utilized in tasks such as facial recognition and emotion analysis.