Open Source BSD Facial Recognition Software

VGGFace2 is a large-scale face recognition dataset developed to support research on facial recognition across variations in pose, age, illumination, and identity. It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. The project also includes preprocessing tools, face detection scripts, and etc.

face-api.js is a JavaScript and TypeScript library for face analysis in web browsers and Node.js. It runs neural networks through TensorFlow.js and accepts images, videos, canvases, or tensors as input. The API can locate one or many faces using several detector models with configurable accuracy and performance settings. It can identify facial landmarks, compute recognition descriptors, classify expressions, and estimate age and gender. High-level chained methods let developers combine detection and analysis tasks in a compact workflow. Browser applications can draw boxes, labels, landmarks, and results on overlay canvases. Node.js support is available through image and canvas polyfills, with native TensorFlow bindings recommended for faster processing.

Blazeface is a lightweight, high-performance face detection model designed for mobile and embedded devices, developed by TensorFlow. It is optimized for real-time face detection tasks and runs efficiently on mobile CPUs, ensuring minimal latency and power consumption. Blazeface is based on a fast architecture and uses deep learning techniques to detect faces with high accuracy, even in challenging conditions. It supports multiple face detection in varying lighting and poses, and is designed to work in real-world applications like mobile apps, robotics, and other resource-constrained environments.

The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis.

System using to verify personality by face's photo.

Libface is a cross platform framework for developing face recognition algorithms and testing its performance.

With the growing need to exchange information and share resources, information security has become more important than ever in both the public and private sectors. Although many technologies have been developed to control access to files or resources, to enforce security policies, and to audit network usages, there does not exist a technology that can verify that the user who is using the system is the same person who logged in. FaceAccess provides a prototype implementation as a "login module" of an information system. The goal is to enhance the level of system security by periodically checking the user’s identity without disrupting the user’s activities. Installation instructions can be found in the package. If you need anymore guidance, please use the Wiki to post any kind of inquiry. NB: Please Donate to support the development of this project. PM me for other means. Any kind of support will be very much appreciated. Thanks a bunch.

Ivolution is a face timelapse generator. Feed it with a bunch of images and it will generate a movie with your face centered on the screen. Ivolution uses face detection and modifies the images so that your face always keeps the same size and location over the movie. Images are processed in chronological order, so that you can see your face evoluate over time !

The purpose of this project is to provide a biometric security solution by using voice print, fingerprint and/or facial recognition along with a password and/or smart card support using AES to protect data. Please read forums for if interested.

An open source face recognition project.

The development of a biometric system and applications e.g. Access Control based on the system to recognize and verify people. The primary goal is face recognition, but other human attributes might get used too in the future.

Face Detection and Recognition using Intel's OpenCV library

WHAY is a Video-based Face Recognition tool written in MATLAB. It aims to exploits PCA recognizing as better as possible and tests the limits of this approach.

WRChat is a fast and lightweight single room chat system for the web where lots of people can join in and talk to each other. Its main features are: Frames , Newest messages first, ASCII happy face recognition, User registration, preferences, internal mai

Artificial neural network with eigenfaces for face recognition

1>Face Recognition on real-time based. 2>shirt -color recognition on image based.

Java framework for face detection and face recognition based on different plugin and filter types. Includes Eigenfaces in pure Java, OpenCV detection via JNI, integration of the Betaface.com Web Service, skin color filter, Adobe XMP Export and a nice GUI