https://github.com/susantabiswas/facial-login-web

Web based facial Authentication system with flask server
https://github.com/susantabiswas/facial-login-web

facial-recognition flask keras neural-network rest-api server siamese-network webcam website

Last synced: 4 months ago
JSON representation

Web based facial Authentication system with flask server

• Host: GitHub
• URL: https://github.com/susantabiswas/facial-login-web
• Owner: susantabiswas
• License: mit
• Created: 2018-02-21T03:10:49.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-09-21T10:48:02.000Z (over 3 years ago)
• Last Synced: 2025-06-21T18:17:15.380Z (12 months ago)
• Topics: facial-recognition, flask, keras, neural-network, rest-api, server, siamese-network, webcam, website
• Language: JavaScript
• Homepage: https://susantabiswas.github.io/facial-login-web/
• Size: 65.3 MB
• Stars: 114
• Watchers: 8
• Forks: 46
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Web based Facial Authentication system

This is a web based facial log in/ Sign up website which uses Facial recognition for user authentication.

It uses flask **server** for running the keras neural network model. 

The model runs on the server side and accepts requests from clients.

Facial recognition is based on Facenet model.

Team members:

**[Susanta Biswas](https://github.com/susantabiswas)** and **[Aditya Singh](https://github.com/adibyte95)**

For running:

1. first run

python keras_server.py

2. go to browser and type **localhost:5000** to access the site

3. enjoy

Some screenshots:




### Homepage

![Homepage](/images/1.jpg)

### Login page

![Log in](/images/2.jpg)

### Sign up page

![Sign up](/images/3.jpg)

### Successful login

![Dashboard](images/4.jpg)

#### References:

- Code for Facenet model is based on the assignment from Convolutional Neural Networks Specialization by Deeplearning.ai on Coursera.


https://www.coursera.org/learn/convolutional-neural-networks/home/welcome 

- Florian Schroff, Dmitry Kalenichenko, James Philbin (2015). [FaceNet: A Unified Embedding for Face Recognition and Clustering](https://arxiv.org/pdf/1503.03832.pdf)

- Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf (2014). [DeepFace: Closing the gap to human-level performance in face verification](https://research.fb.com/wp-content/uploads/2016/11/deepface-closing-the-gap-to-human-level-performance-in-face-verification.pdf) 

- The pretrained model used is inspired by Victor Sy Wang's implementation and was loaded using his code: https://github.com/iwantooxxoox/Keras-OpenFace.

- A lot of inspiration from the official FaceNet github repository: https://github.com/davidsandberg/facenet