Attendance system using face recognition is a procedure of recognizing students by using face biostatistics based on the high definition monitoring and other computer technologies. The development of this system is aimed to accomplish digitization of the traditional system of taking attendance by calling names and maintaining pen-paper records.
Our approach is using the world’s simplest face recognition library built using dlib’s state-of-the-art face recognition built with deep learning. This face_recognition model has high accuracy ensuring low false-positive detection , efficiency and robust in nature. After face recognition attendance reports will be generated and stored in excel format.
This system used pretrained fine turing model face_recognition and recognized faces by comparing face encodings
├───ams
│ ├───migrations
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│ ├───templates
│ │ └───static
│ │ ├───css
│ │ ├───js
│ │ └───media
│ └───__pycache__
├───models
├───pictures
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│ │ └───Sample
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├───project2
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├───admin
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│ │ └───vendor
│ │ └───select2
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│ │ └───gis
│ └───js
│ ├───admin
│ └───vendor
│ ├───jquery
│ ├───select2
│ │ └───i18n
│ └───xregexp
├───css
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python manage.py runsslserver --cert cert.pem --key key.pem localhost:3000