This project is an advanced face recognition attendance system that harnesses the power of Django and deep learning to deliver a secure and accurate solution for attendance tracking. Utilizing the MTCNN (Multi-Task Cascaded Convolutional Networks) for face detection and the InceptionResnetV1 model for face encoding, this application recognizes faces in real-time and records attendance automatically.
Key Features:
Real-Time Face Recognition: Integrates MTCNN and InceptionResnetV1 for precise face detection and encoding.
Multi-Camera Support: Configurable for multiple IP and local cameras.
Automated Attendance Logging: Supports automated check-in/check-out, reducing the need for manual intervention.
Admin Dashboard: Access to the student database, attendance records, and customizable settings.
Alert Sound on Successful Recognition: Uses Pygame to play a sound for successful face recognition.
Secure Login and Access: Restricts admin access to view, edit, and authorize users, ensuring data security.
This project is ideal for institutions and businesses looking to streamline their attendance tracking system and improve security with biometric verification.
Installation Requirements (requirements.txt):
To run this project, the following Python libraries and dependencies are required:
Setup Instructions:
Install dependencies:
pip install -r requirements.txt
Configure the database and apply migrations:
python manage.py migrate
Run the Django development server:
python manage.py runserver
Access the application at http://127.0.0.1:8000 and log in to explore the features.
What’s app me for installation guide: @ +919525845873
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