#face recognition

BossSensor project leverages image classification to automatically hide computer screens when a boss is approaching. Using Python 3.5 and OpenCV, the system requires a webcam and a comprehensive facial image dataset for training. End-users benefit from quick reaction to proximity alerts, making it suitable for OSX users seeking privacy in supervised environments. The installation involves setting a virtual environment and transitioning the Keras backend to TensorFlow, ensuring software compatibility without overstated features.

Discover a sophisticated facial recognition and attribute analysis framework utilizing top-tier models such as VGG-Face, FaceNet, and ArcFace for enhanced accuracy. This Python framework offers reliable face identification and includes features for detecting, aligning, and analyzing facial attributes like age, gender, emotion, and race. It is easy to install via PyPI, offering versatile capabilities for integration into various projects.

VideoPipe is a C++ framework for video analysis across platforms, offering easy plugin integration and support for protocols like RTSP and RTMP. Suited for face recognition and traffic analysis, it provides flexible configuration with minimal dependencies and supports inference backends like OpenCV and TensorRT.

This repository delivers a REST API designed for face detection and recognition powered by FastAPI and NVIDIA TensorRT. It supports fast deployment on NVIDIA GPU systems through Docker, optimizing inference speed and allowing model conversion to ONNX and TensorRT formats. Highlights include automatic model retrieval, compatibility with multiple detection models including SCRFD and RetinaFace, and recognition models like ArcFace and PyTorch. Supports batch inference for both detection and recognition, making it suitable for high-performance face analysis in various applications.

OpenFace is an open-source project providing face recognition capabilities via deep neural networks. It serves as a comprehensive platform for image processing, real-time web demonstration, image comparison, and classifier training. Supported by research and tech industry contributions, the project promotes academic and development dialogues. OpenFace offers valuable Python libraries and models for mobile app development and performance assessment, serving as a resourceful tool for both developers and researchers.

Discover a video editing tool that provides precise facial recognition, intelligent voice and clip editing, and advanced video generation like seamless background changes and color enhancement. This tool is designed to deliver clear, smooth results for both professionals and hobbyists seeking innovative and engaging video content.