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CompreFace is a facial recognition system designed for human face detection, identification, and biometric identity verification. It provides a registry of known people and the ability to match faces in images against this database to determine a specific identity. The system extracts facial landmarks to map geometry and analyzes physical attributes including age, gender, and head pose. It can also verify whether two different images belong to the same individual. The project is implemented as a microservice-based deployment utilizing a REST API gateway and a PostgreSQL metadata store. It in
lite.ai.toolkit is a C++ computer vision toolkit designed for edge AI deployment. It enables the execution of pre-trained models for object detection, image classification, and segmentation on resource-constrained devices. The project features a multi-backend inference engine that supports the ONNX model runtime, allowing AI models to run across different hardware targets. It includes a GPU-accelerated pipeline specifically for NVIDIA hardware to reduce latency and increase processing speed. The toolkit covers a broad range of facial analysis capabilities, including emotion detection, gender
This project is a collection of practical implementation examples and demonstrations for building mobile applications using a JavaScript-based native framework. It serves as a cross-platform mobile framework demo, providing a gallery of interactive interface patterns and native integration suites. The repository showcases specialized capabilities including high-performance 2D and 3D visual content through OpenGL graphics implementation. It also features a suite of native hardware integrations, covering biometric authentication via fingerprint scanning and gesture-based unlock patterns. The p
This project is a Go library designed for facial detection, landmark mapping, and identity verification. It provides a toolkit for integrating computer vision capabilities into applications, enabling the automated identification and analysis of human faces within digital images. The library utilizes a deep residual network to transform facial data into compact vector representations, which are then compared using geometric distance calculations to confirm identities. It employs histogram-based object detection to locate facial structures and maps specific points on the face to define geometry
Howdy is a biometric authentication system for Linux that uses infrared cameras to provide passwordless login and privileged access. It functions as a Pluggable Authentication Module to integrate facial recognition into the standard Linux authentication pipeline.
The main features of boltgolt/howdy are: Facial Recognition, Linux Authentication, PAM Modules, Biometric Authentication, PAM Biometric Integration, Biometric Face Verification, Infrared Biometric Recognition, Specialized Camera Interfacing.
Open-source alternatives to boltgolt/howdy include: exadel-inc/compreface — CompreFace is a facial recognition system designed for human face detection, identification, and biometric identity… xlite-dev/lite.ai.toolkit — lite.ai.toolkit is a C++ computer vision toolkit designed for edge AI deployment. It enables the execution of… fangwei716/30-days-of-react-native — This project is a collection of practical implementation examples and demonstrations for building mobile applications… kagami/go-face — This project is a Go library designed for facial detection, landmark mapping, and identity verification. It provides a… jumpserver/jumpserver — JumpServer is a privileged access management platform designed to manage and audit secure access to SSH, RDP,… bytedeco/javacv — JavaCV provides a Java-based interface for native computer vision and video processing libraries. It functions as a…