Face-Recognition-Based-Attendance-System

A web app to recognize faces of all students in photo and mark their attendance in Database using Deep Learning.

Project Flow

MTCNN Architecture

Facenet Architecture Intuition

Other files:

app.py : Backend code using Flask.
Face_recog_facenet : Model Building Code.
face_net.h5 : Saved wights of Facenet model.
pred_3_svm_face_model.pkl : Saved Svm Model.
requirements.txs : File with all required libraries.
template : HTML/CSS codes.
Test : This will store images to test our app.

How to run

Step 1:

open Terminal and Install the required libraries by pip install -r requirements.txt

Step 2:

Use "export FLASK_APP=app.py"

Step 3:

Use this "flask run" to run server.

Future Work

Reducing response time, At present it is around 40-50 secs per image on CPU.

Making Backend better with personalised logins for every student and faculty.

Improving model accuracy by using better image processing techniques.

Testing model with more number of students in one frame.