FaceLivenessDetection - Docker
This demo demonstrates 3D passive face liveness detection python SDK by mitigating biometric fraud on Linux server.
Last updated
This demo demonstrates 3D passive face liveness detection python SDK by mitigating biometric fraud on Linux server.
Last updated
This project demonstrates an advanced face liveness detection technology implemented via a Dockerized Flask API.
It stands for 3D passive face liveness detection docker, face anti-spoofing docker, face fraudulent check docker, face liveness check docker, fraud prevention docker, spoof prevention docker, face fraud detection docker and biometric fraud with liveness detection on Linux server.
To test the API, you can use Postman. Here are the endpoints for testing:
CPU: 2 cores or more (Recommended: 8 cores)
RAM: 4 GB or more (Recommended: 8 GB)
HDD: 4 GB or more (Recommended: 8 GB)
OS: Ubuntu 20.04 or later
Dependency: OpenVINOâ„¢ Runtime (Version: 2022.3)
Clone the project:
Build the Docker image:
Run the Docker container:
Send us the machine code and replace the license.txt file you received. Then, run the Docker container again.
Setup Gradio
Ensure that you have the necessary dependencies installed.
Gradio requires Python 3.6 or above.
You can install Gradio using pip by running the following command:
Run the demo by using the following command:
Test with an image file: Send a POST request to
Test with a base64-encoded image: Send a POST request to
You can download the Postman collection to easily access and use these endpoints.
Download the model from Google Drive and unzip it:
To test the API, you can use Postman. Here are the endpoints for testing:
Test with an image file: Send a POST request to .
Test with a base64-encoded image: Send a POST request to .
You can download the Postman collection to easily access and use these endpoints.
You can test within the following URL:
