Realtime Face Anti-Spoofing Detection
Realtime Face Anti Spoofing Detection with Face Detector to detect real and fake faces
Why Build This? :thinking:
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? :hammer:
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 :green_book:
The model is trained using Tensorflow from publicly available datasets. Below listed are the data sources that the model is trained on:
3DDFA: https://github.com/cleardusk/3DDFA (Face Detector Library)
Please obtain the necessary permissions before using the datasets as above.
All the required libraries are included in the file
Face Detector library, 3DDFA aka (
face_det) is added as part of the repo for easy development.
- Clone the repo
$ git clone https://github.com/Prem95/face-liveness-detector.git
- Change your directory to the cloned repo
$ cd face-liveness-detector
- Run the following command in your terminal
$ pip install -r requirements.txt
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.