AI-powered face recognition system

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  Student Dashboard

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  Home page

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  Attendance Report

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  Admin Dashboard

Inspiration

Traditional attendance systems are time-consuming, prone to human error, and vulnerable to proxy attendance. Many institutions still rely on manual processes that lack efficiency and transparency. This inspired us to develop an AI-powered solution that automates attendance using face recognition from group photos.

What it does

The system detects multiple faces from a group photo or live capture, matches them with registered student records, and automatically updates subject-wise attendance. Teachers can define lecture duration and download reports, while students can view their attendance and interact with a chatbot for queries.

How we built it

The project is developed using Python-based technologies, with Streamlit for the frontend and Flask for backend handling. Face recognition libraries are used for facial encoding and matching, and a structured database stores student details and subject-wise attendance records. The chatbot supports both text and voice queries.

Challenges we ran into

Accurately detecting multiple faces in group images, handling different lighting conditions, avoiding duplicate detections, and designing subject-wise attendance logic were major challenges. Implementing role-based access control and optimizing system performance were also critical tasks.

Accomplishments that we're proud of

We successfully implemented automated group photo attendance detection, subject-wise tracking, chatbot integration, and a fully functional role-based system. The project works as a complete end-to-end prototype suitable for real-world application.

What we learned

Through this project, we gained practical experience in face recognition implementation, backend–frontend integration, real-world dataset handling, system security, and AI performance optimization.

What's next for AI-powered face recognition system

Future enhancements include mobile app integration, cloud deployment, real-time CCTV-based attendance detection, anti-spoofing security features, and advanced analytics dashboards for institutional insights.

Built With

• arcface
• cnn
• flask-(backend)
• natural-language-processing
• opencv-and-face-recognition-(face-detection-&-matching)
• python
• sqlite/mysql-(database)
• streamlit-(frontend)