📸 Snap&Go – AI-Powered Attendance System

Snap&Go is a face recognition-based attendance automation system built using Python, Flask, and OpenCV. Designed for classrooms, it enables teachers to capture a photo of the class and automatically mark attendance in real time using AI-based facial recognition with 75%+ accuracy.

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🚀 Tech Stack

• Backend: Python, Flask, SQL
• Frontend: HTML, CSS, JavaScript
• AI & Vision: OpenCV, DLIB, Scipy, NumPy

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🎯 Key Features

• 🖼️ Real-time Photo Capture
  Built a responsive UI for capturing classroom snapshots on the spot.

• 🧠 Face Recognition with DLIB
  Uses facial landmarks and deep learning to detect and identify students with 75%+ accuracy.

• 🕒 Instant Attendance Processing
  Automatically marks present students by comparing faces with the existing dataset.

• 📊 Attendance Dashboard
  Displays recognized faces and corresponding attendance records.

• ⚡ 40% Efficiency Boost
  Automates manual attendance, saving time and reducing human error.

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🧪 How It Works

1. Capture Image – Teacher captures a classroom photo through the web interface.
2. Face Detection – System uses DLIB & OpenCV to detect all faces.
3. Face Recognition – Detected faces are matched against pre-trained encodings.
4. Attendance Marking – Matching faces are recorded as present in the SQL database.
5. Live Results – Results are shown in real-time on the web interface.