README.md

Attendance Management using Face Recognition

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.

Description

This system used pretrained fine turing model face_recognition and recognized faces by comparing face encodings

This is how directory structure looks like

├───ams │ ├───migrations │ │ └───__pycache__ │ ├───templates │ │ └───static │ │ ├───css │ │ ├───js │ │ └───media │ └───__pycache__ ├───models ├───pictures │ ├───N18 │ │ └───cse │ │ ├───cse1 │ │ └───cse2 │ │ └───Sample │ ├───N19 │ │ └───cse │ │ └───cse1 │ └───N20 │ └───cse │ ├───cse1 │ │ ├───N181022 │ │ ├───N200037 │ │ ├───N200377 │ │ ├───N200381│ │ │ │ ├───N201064 │ │ └───N201070 │ └───cse2 │ ├───N170976 │ ├───N180789 │ ├───N180825 │ └───N181022 ├───project2 │ └───__pycache__ └───static ├───admin │ ├───css │ │ └───vendor │ │ └───select2 │ ├───img │ │ └───gis │ └───js │ ├───admin │ └───vendor │ ├───jquery │ ├───select2 │ │ └───i18n │ └───xregexp ├───css ├───js └───media

Seeting up application

start the mysql server first

specify the mysql port and credentials of mysql in project2>settings.py files as shown in the below figure

Now got to the build directory and open command prompt and then enter
python manage.py runsslserver --cert cert.pem --key key.pem localhost:3000

open the address in the browser and browse for localhost:3000

References

Know More About The AMS

• Documentation (Technical Details)
• Video (Promo)
• Frontend React Source Code