Face Recognition Attendance Tracking for Classrooms and Offices

Added Jun 2025 3 design docs

Taking attendance by roll call or paper sign-in sheets wastes teaching time, invites proxy sign-ins, and produces records that are tedious to compile. Schools, training centers, and HR teams want attendance capture that is fast, hard to game, and automatically logged, without requiring badges or manual data entry. This project has the intern build a Flask web application that automates the entire flow: OpenCV detects faces from a live webcam stream, a convolutional neural network built with TensorFlow recognizes each enrolled individual, and the system records a timestamped attendance entry the moment a known face is confirmed. The intern implements an enrollment workflow for registering new people with sample images, real-time prediction overlays on the video feed so users get immediate confirmation, and attendance views for reviewing who was present on a given day. The application ships as a Docker container for painless installation on a classroom or office machine. Completing the system teaches face detection and recognition pipelines end to end, the practical differences between detecting a face and identifying a person, and how to design biometric software responsibly. The intern leaves with a deployable product demonstrating applied vision, web development, and deployment skills together.

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