👤 Face Recognition Attendance System

A real-time face recognition system using DeepFace, OpenCV, and Tkinter. It detects faces, recognizes known individuals, predicts age and emotion, and automatically logs attendance to a CSV file — all through a simple graphical interface.

✨ Features

• 🧠 Face Recognition using DeepFace
• 😀 Emotion & Age Prediction
• 🕒 Automated Attendance Logging with timestamp
• 📋 CSV File Output for records
• 🖼️ User-Friendly GUI built with Tkinter
• 📁 Photo-based Registration

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⚙️ Tech Stack

Technology	Usage
Python	Core programming language
DeepFace	Face recognition and analysis
OpenCV	Face detection and image capture
Tkinter	GUI development
Pandas	Data handling and CSV logging

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🧑‍💻 Setup Instructions

1. Clone the repository:

   git clone https://github.com/asmxtaa/Face-Recognition-Attendance.git
   cd Face-Recognition-Attendance

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   venv\Scripts\activate  # On Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Add registered user images:

   • Place face images (e.g., Asmita.jpg) into the registered_faces/ folder.

5. Run the app:

   python ss.pyw

6. View attendance table:

   python tables.py

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📁 Project Structure

├── ss.pyw               # Main GUI launcher
├── recognition.py       # Handles recognition logic
├── detection.py         # Face preprocessing
├── tables.py            # Attendance table viewer
├── registered_faces/    # Store images of known users
├── attendance_log.csv   # Auto-generated attendance log

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📋 Output Format

Attendance logs are stored in attendance_log.csv in the following format:

Name, Date, Time, Emotion, Age

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🧑‍🎨 Built By

Asmita Mandal 🌸
GitHub • LinkedIn

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📄 License

This project is open-source and available under the MIT License.