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Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV

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Realtime Face Anti-Spoofing Detection 🤖

Realtime Face Anti Spoofing Detection with Face Detector to detect real and fake faces

Python contributions welcome Forks Stargazers

Please star this repo if it is useful for you!:star2:



Why Build This? 🤔

Face anti-spoofing systems has lately attracted increasing attention due to its important role in securing face recognition systems from fraudulent attacks. This project aims to provide a starting point in recognising real and fake faces based on a model that is trained with publicly available dataset

Where to use? 🔨

This Face Anti Spoofing detector can be used in many different systems that needs realtime facial recognition with facial landmarks. Potentially could be used in security systems, biometrics, attendence systems and etc.

Can be integrated with hardware systems for application in offices, schools, and public places for various use cases.

Datasets and Library 📗

The model is trained using Tensorflow from publicly available datasets. Below listed are the data sources that the model is trained on:

CASIA: https://github.com/namtpham/casia2groundtruth

OULU: https://sites.google.com/site/oulunpudatabase/

NUAA: http://parnec.nuaa.edu.cn/_upload/tpl/02/db/731/template731/pages/xtan/NUAAImposterDB_download.html

3DDFA: https://github.com/cleardusk/3DDFA (Face Detector Library)

Please obtain the necessary permissions before using the datasets as above.

Prerequisites ☔

All the required libraries are included in the file requirements.txt Face Detector library, 3DDFA aka (face_det) is added as part of the repo for easy development.

Installation 💻

  1. Clone the repo
$ git clone https://github.com/Prem95/face-liveness-detector.git
  1. Change your directory to the cloned repo
$ cd face-liveness-detector
  1. Run the following command in your terminal
$ pip install -r requirements.txt

Usage ⚡

Run the following command in your terminal

$ python main.py

Note: Current Face Anti Spoofing threshold is set at a value of 0.70. This can be finetuned based on different situations as needed.

Contribution ⚡

Feel free to file a new issue with a respective title and description on the the face-liveness-detector repository.

Feature Request ⚡

Please also submit a pull request for any issues that might appear or any enhancements/features that could make this project perform better. I would love to review your pull request!

Code of Conduct 👍

You can find our Code of Conduct here.

License 👍

All rights reserved according to MIT © Prem Kumar

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Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV

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