FaceRecognition - Docker
This demo demonstrates face recognition and face liveness detection by mitigating biometric fraud on Linux server in python language.
Last updated
This demo demonstrates face recognition and face liveness detection by mitigating biometric fraud on Linux server in python language.
Last updated
This project demonstrates an advanced face recognition
technology implemented via a Dockerized Flask API
.
It stands for face recognition docker
, facial recognition docker
, face liveness check docker
, spoofing prevention docker
, face matching docker
, face comparison docker
, face search engine docker
, face identification docker
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
: