🧑‍💼 Face Recognition Attendance System

A real-time attendance system built with Python, OpenCV, and Firebase Realtime Database, that marks student attendance automatically using facial recognition.

🧰 Technologies Used

• Python 3
• OpenCV – For real-time webcam input and image handling
• face_recognition – For detecting and recognizing student faces
• Firebase Admin SDK – For syncing with Firebase Realtime Database and Storage
• cvzone – For drawing UI elements on the screen
• NumPy – For image and data array processing

✅ Key Benefits

• 🎯 High Accuracy: Prevents proxy attendance and manual marking errors.
• ⚡ Fast & Automatic: Detects and marks attendance instantly using a webcam.
• 👁️ Live Feedback: Students get immediate visual confirmation of their attendance.
• 📂 Smart Data Handling: Attendance is safely stored in Firebase and easy to manage.
• 🌐 Flexible Use: Works seamlessly in schools, colleges, or office setups.

📁 Project Structure

FaceRecognitionAttendance/
├── Images/                   # Student face images (named by ID)
├── Resources/
│   ├── background.png        # App UI background layout
│   └── Modes/                # UI screens (Loading, Marked, Already Marked, etc.)
├── EncodeGenrartor.py        # Generates encodings and uploads them to Firebase
├── main.py                   # Main app script for face recognition and attendance
├── EncodeFile.p              # Serialized (pickled) face encodings
└── serviceAccountKey.json    # Firebase credentials (keep private)

✨ Features

• 👤 Real-time face recognition using webcam for automatic attendance
• 📡 Instant Firebase Realtime Database integration for storing attendance records
• 🖼️ Graphical UI with visual feedback: "Active", "Marked", "Already Marked", "Loading"
• 📋 Displays student details: Name, ID, Branch, Year, Major, etc.
• 🧠 Uses pickle-based facial encoding for fast and efficient recognition
• 🔄 Prevents duplicate entries with "Already Marked" alert
• 🔐 Secure and scalable using Firebase Admin SDK credentials

🖼️ UI Images

Below are the screenshots of the graphical user interface of the Face Recognition Attendance System:

Active Mode

System is ready for face recognition.

Student Details

Displays student details like Name, ID, Branch, Year, Major.

Marked Mode

Attendance has been recorded for the student.

Already Marked

The student has already been marked as present.

📦 Installation

To set up the Face Recognition Attendance System on your local machine, follow these steps:

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1. Clone the Repository

Start by cloning the repository to your local machine:

git clone https://github.com/harshitnagar22/face-attendance-system-python-opencv.git
cd face-attendance-system-python-opencv

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2. Install the Required Dependencies

Once the virtual environment is activated, install the required Python packages using the following command:

pip install -r requirements.txt

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3. Set Up Firebase Credentials

Download your Firebase Admin SDK credentials (serviceAccountKey.json) from your Firebase project and place it in the root directory of the project.

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4. Run the System

You're now ready to run the Face Recognition Attendance System:

python main.py

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🚀 How to Run

1. Add student face images inside the Images/ folder (e.g., 1001.png, 1002.png).
2. Generate encodings and upload data: python EncodeGenrartor.py
3. Start the face recognition system: python main.py

To use an external webcam, change this line in main.py: cap = cv2.VideoCapture(1) # Use 1 or 2 based on your camera index

🙋‍♂️ Created by

Harshit Nagar
🎓 BTech CSE @ JECRC University
🔗 LinkedIn: https://www.linkedin.com/in/harshit-nagar-708a27290

🤝 Contributing

Contributions are welcome! If you have ideas to improve this project, feel free to fork the repo and submit a pull request.

Steps to Contribute:

1. 🍴 Fork the repository
2. 🛠️ Create your feature branch (git checkout -b feature/YourFeature)
3. ✅ Commit your changes (git commit -m 'Add some feature')
4. 🚀 Push to the branch (git push origin feature/YourFeature)
5. 📬 Open a Pull Request

You can contribute by:

• Fixing bugs 🐞
• Improving performance ⚙️
• Enhancing UI 🎨
• Adding new features 💡
• Improving documentation 📝

Make sure your code follows clean coding practices and includes comments where necessary.

✨ Use Cases

The Face Recognition Attendance System is ideal for various settings:

🎓 Schools & Colleges:

• Automates student attendance and prevents proxy attendance.

🏢 Corporate Offices:

• Tracks employee attendance and integrates with HR systems.

🎤 Events & Conferences:

• Quick and accurate attendance verification for event participants.

💻 Online Classes:

• Verifies real-time attendance in virtual classrooms.

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🚀 Future Plans

The project is evolving with exciting future enhancements:

🌐 System Integrations:

• Integrate with LMS for automatic course attendance and HR systems for employee tracking.

📊 Reporting & Alerts:

• Real-time attendance alerts and detailed reports with visual data.

📱 Mobile App:

• A mobile app for easy attendance tracking on the go.

😃 Advanced Features:

• Add facial expression recognition to track engagement.

🏋️‍♂️ Scalability:

• Optimize for large-scale use in universities and big organizations.

⭐ Like the Project?

If you found this helpful, star the repo 🌟 and share it with others!

📝 License

This project is licensed under the MIT License.
See the LICENSE file for details.