Deep neural network trained to detect eye contact from facial image
Head Pose Estimator on Caffe
Real-time Face & emotion recognition system using a lightweight CNN, with OpenCV webcam inference, GroqCloud for chatbot & FastAPI + frontend web deployment.
Spring-boot+ElasticSearch+LIRE+SwaggerUI RESTful.
Artificial Intelligence-Based Face Analysis & Recognition Library
A curated list of face shape detectors, facial symmetry analyzers, golden ratio calculators, and resources for understanding facial proportions. Tools, research, hairstyle guides, glasses fitting, and developer resources for face analysis.
Meshify is a real-time face mesh detection application that uses OpenCV, MediaPipe, and CVZone to identify and track facial landmarks with high accuracy and performance.
A comprehensive facial analysis and identification system packaged in a ready-to-deploy Docker container. This repository provides a complete solution for face detection, recognition, and feature analysis with minimal setup requirements.
A real-time facial analysis platform built with Flask, OpenCV, TensorFlow, PyTorch, and Next.js, featuring live face detection, age & gender estimation, and emotion recognition. Designed for robotics club events, tech fairs, and interactive AI demos, with a futuristic cyberpunk UI powered by Arwes.
Real-time face attribute analysis using OpenCV and DeepFace to detect emotion, age, gender and race from webcam.
Flask‑based web app for detecting facial/skin anomalies and returning a matched condition label with supplement info. Upload an image, run the model, and get a result page with the predicted condition.
AI-powered facial skin quality analysis — 7-zone scoring, concern heatmaps, biological age estimation. Upload a selfie, get instant results.
Identity-preserving facial aging with dual-scale diffusion: global low-frequency residuals for coarse age structure and local crop-level diffusion for high-frequency aging details.
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.
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.
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.
Facial morphometrics from a photograph, with a 95% interval on every measurement and no aggregate score. Runs locally.
PROSOPO is a outerworld facial recognition system designed with a focus on vision with accuracy and speed. It integrates state-of-the-art detection and recognition models with advanced fairness-aware techniques to ensure equitable performance across different species.
Tu cara, medida y explicada: morfometría facial, colorimetría, piel, protocolo no quirúrgico y looks renderizados sobre tu foto. Sin notas de belleza.
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