The Face Recognition Attendance System is an AI-powered application 🤖 designed to automate attendance tracking 📋 using facial recognition technology. It utilizes OpenCV, MediaPipe, Firebase, and face_recognition to detect 👀 and recognize students' faces, record attendance ✅, and update a real-time database 📡.
- 🎯 Real-Time Face Detection & Recognition: Uses OpenCV and
face_recognitionto identify individuals. - 📊 Automatic Attendance Logging: Updates student attendance in Firebase based on recognition results.
- 🖼️ Profile Display: Retrieves and displays student information, including name, major, and profile picture.
- 🔄 Mode-Based UI Updates: Implements different display modes for detection, recognition, and attendance confirmation.
- ⏳ Time-Based Attendance Restriction: Prevents multiple entries within 30 seconds to avoid duplicate records.
- 🎨 Customizable UI: Overlays student details on a background image for better visualization.
- 🐍 Python
- 🖼️ OpenCV (Computer Vision)
- 🏷️ face_recognition (Face Detection & Encoding)
- 🔥 Firebase Realtime Database (Cloud Storage)
- ✋ MediaPipe (Hand & Face Tracking)
- 📊 NumPy & Pickle (Data Processing & Storage)
- 📷 Face Detection: The system captures a frame from the webcam and detects faces.
- 🧬 Face Encoding & Matching: Extracts facial features and compares them with known encodings.
- 📌 Attendance Update: If a face matches, the system updates the student's attendance in Firebase.
- 📄 Display Student Details: Retrieves and shows student information, including attendance history.
- 🔄 UI Mode Switching: Dynamically changes UI elements based on recognition status.