🧠 SnapClass – AI Powered Attendance System

SnapClass is a next-generation AI-powered attendance system that revolutionizes classroom management using Computer Vision, Voice Biometrics, and QR-based automation.
It enables fast, secure, and accurate student attendance tracking with minimal manual intervention.

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🌐 Live Demo

https://snapclass-main123.streamlit.app/

🚀 Overview

SnapClass leverages advanced AI technologies to automate attendance using multiple biometric modalities:

• 📸 Face Recognition (Computer Vision)
• 🎙️ Voice Biometrics (Audio AI)
• 📱 QR-Based Course Enrollment System

The system is designed for educational institutions to improve efficiency, reduce manual workload, and enhance attendance accuracy.

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✨ Key Features

📸 AI Face Analysis

• Detects and recognizes students from a single class image
• Uses deep learning-based facial embeddings
• Provides fast and highly accurate attendance marking

🎙️ Voice ID Recognition

• Students speak “Present” sequentially
• Uses voice embeddings to match stored biometric profiles
• Ensures secure and fraud-resistant attendance validation

📱 QR-Driven Enrollment

• Each course generates a unique QR code
• Enables instant student enrollment without manual entry
• Simplifies class onboarding process

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⚙️ System Workflow

👨‍🏫 Teacher Journey

1. Secure Login

   • Encrypted authentication system for teachers

2. Dashboard Access

   • Manage subjects, students, and attendance records

3. Course Creation

   • Create subjects and generate QR codes automatically

4. FaceID Attendance

   • Capture classroom image and run AI recognition

5. VoiceID Attendance

   • Conduct real-time voice-based roll call

6. Reports & Analytics

   • Download attendance logs and track performance trends

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🎓 Student Journey

1. Instant Enrollment

   • Join courses using QR code or invite link

2. Biometric Registration

   • Register FaceID and VoiceID once for authentication

3. Personal Dashboard

   • Track attendance percentage and updates in real time

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🏗️ Tech Stack

🧠 AI / Machine Learning

• FaceRecognition (Dlib-based models)
• Librosa (Audio feature extraction)
• Resemblyzer (Voice embeddings)

💻 Backend & Frontend

• Flask (Web framework)
• Streamlit (Interactive UI)

☁️ Database & Cloud

• Supabase (PostgreSQL + Authentication)
• Real-time data synchronization

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📊 System Capabilities

• Real-time biometric authentication
• Multi-modal AI (Face + Voice)
• Automated attendance tracking
• Secure cloud-based storage
• Scalable classroom architecture

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🔐 Security Features

• Encrypted login system
• Biometric authentication for identity verification
• Secure cloud database (Supabase)
• Role-based access (Teacher / Student)

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📦 Project Structure

SnapClass/ │ ├── backend/ # AI models and core logic ├── frontend/ # UI (Streamlit / Flask) ├── models/ # Saved ML models (Face + Voice) ├── utils/ # Helper functions (preprocessing, etc.) ├── database/ # Supabase integration scripts └── app.py # Main entry point