Deep neural network trained to detect eye contact from facial image
Head Pose Estimator on Caffe
Spring-boot+ElasticSearch+LIRE+SwaggerUI RESTful.
OneStopVision is an open-source toolkit offering a comprehensive suite of algorithms for face and body analysis, landmark extraction, and ControlNet integration in Stable Diffusion.
Driver Drowsiness Detection - A robust solution leveraging computer vision and machine learning. Unleash the power of facial and eye movement analysis for real-time fatigue alerts, contributing to an unparalleled level of road safety.
facialAnalysisLiteDetection2D: Detector implementation for the analysis of facial features. Using the cvlib API analysis for gender extraction and prediction. Via OpenCV DNN, age prediction. Through tensorflow, emotion detection. Image source reception via YARP, processing and sending of detections via YARP port.
A deep learning-based system for detecting deepfakes in images and videos, with integrated facial emotion analysis. Built using EfficientNetB4, CNN-GRU, OpenCV, and DeepFace to evaluate both authenticity and emotional expression across video frames. Supports detailed evaluation metrics and real-time graph visualization.
DrowsinessGuard: A real-time drowsiness detection system that enhances driver safety using computer vision and facial landmark analysis. Features precise eye tracking, face direction monitoring, and yawn detection to alert drivers of fatigue, helping prevent accidents caused by drowsy driving.
Total 50 persons in indoor scenario, with balanced agender, age from 18 to 50. Each face is annotated with 182 key points, facilitating precise facial feature tracking and analysis.
✨ Visage Health – AI-Powered Skin Health Analyzer Visage Health is an AI-driven web app that analyzes facial health from images using Google Gemini API. Just upload a selfie, and get insights on issues like pimples, dark circles, or skin redness, along with smart skincare suggestions
DeepFace Library lets you recognize and analyze faces quickly with models like VGGFace and Facenet.
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