Managing attendance manually is time-consuming and error-prone. Traditional methods such as roll calls and sign-in sheets lack efficiency, accuracy, and security. Additionally, preventing unauthorized access to restricted areas remains a challenge. Our solution, FaceCheck In, automates attendance tracking using AI-powered facial recognition, enhancing efficiency, security, and reliability.
FaceCheck In is an AI-driven facial recognition system designed to automate attendance tracking and monitoring in organizations. It processes live video streams to detect and recognize faces, seamlessly marking attendance. Unrecognized individuals are flagged and stored separately for further review. The platform ensures accuracy, security, and a hassle-free attendance management experience.
To use FaceCheck In, follow these steps:
git clone https://github.com/SSARAWAGI05/AttendanceFrontend.gitpip install -r requirements.txtpython app.pyThis will start the FaceCheck In application, allowing you to access the system through a web interface.
✅ Automated Face Recognition – Detects and marks attendance of registered users in real-time. ✅ Unknown Face Detection – Captures and stores images of unrecognized individuals for review. ✅ Live Video Processing – Continuously updates attendance records using webcam feeds. ✅ User-Friendly Web Interface – Provides an intuitive dashboard for administrators to view attendance records and manage the system. ✅ Enhanced Security – Helps prevent unauthorized access by flagging unknown individuals.
- Flask (Python)
- HTML, CSS, JavaScript
- OpenCV for real-time face detection
- Deep Learning models for facial recognition
We extend our gratitude to the open-source community for providing valuable resources and inspiration that contributed to this project.
Shubam Sarawagi