AI Face Detection
Real-time facial expression analysis powered by TensorFlow.js and face-api.js running entirely in the browser.
Models
face-api.js
Backend
None
Inference
Client-side
Performance
WebGL
1. What problem I solved?
Many face analysis tools require sending images or video streams to external servers, creating privacy concerns and latency.
The goal was to build a lightweight application capable of detecting faces and analyzing expressions entirely in the browser.
- • Real-time webcam analysis
- • Image upload support
- • Privacy-first architecture
- • Client-side machine learning
- • Fast emotion recognition
2. How I built it?
The application was built with Next.js, React and TypeScript while leveraging browser-based machine learning.
Face Detection
Integrated face-api.js models to detect faces, landmarks and facial expressions.
TensorFlow.js
Configured TensorFlow.js with WebGL acceleration.
Live Webcam Analysis
Used MediaDevices API to process webcam frames in real time.
Image Upload Analysis
Implemented upload validation and multi-face detection.
3. What I learned?
This project gave me hands-on experience building AI-powered browser applications.