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Face recognition & attendance logging

This project implements an automated face-based attendance system using MTCNN for face detection and alignment, face_recognition for embedding extraction, and cosine-similarity matching to identify students. The system marks attendance in an Excel sheet and includes evaluation metrics such as confusion matrix, precision-recall, and ROC curves. The approach uses pretrained models (transfer learning) and performs supervised face matching without training a custom neural network.

Group project contributors: Aryan Pal, Dikshith Poojary and Tejas Rana.

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Recognize faces from photos and log attendance to Excel.

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