Real-Time-Emotion-Detection-with-OpenCV-DeepFace and EmotionTracker
About Real-Time-Emotion-Detection-with-OpenCV-DeepFace
Shayanthn/Real-Time-Emotion-Detection-with-OpenCV-DeepFace
This project is a real-time facial emotion recognition system using OpenCV, Mediapipe, and DeepFace. It captures video from a webcam, detects facial landmarks, and analyzes emotions in real-time using deep learning models.
This system helps professionals in fields like market research, UX design, or behavioral science to understand audience reactions by analyzing facial expressions in real-time. It takes live video from a webcam, processes facial movements, and displays detected emotions like happiness, sadness, or anger on-screen with probabilities. This is for researchers, analysts, or content creators who need immediate feedback on emotional responses.
About EmotionTracker
DeepPythonist/EmotionTracker
AI-powered real-time emotion detection desktop app using DeepFace. Track emotions via webcam with privacy-focused local processing, analytics dashboard, and CSV export.
This desktop application helps you understand emotional responses in real-time by analyzing facial expressions via your webcam. It takes live video input and outputs detected emotions, confidence levels, and time-series data, which can be exported to CSV files. Anyone needing to monitor or record emotional cues for research, customer interaction analysis, or personal well-being can use this tool.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work