FaceRecognition - Docker
This demo demonstrates face recognition and face liveness detection by mitigating biometric fraud on Linux server in python language.
Overview
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.
SDK
Github
dockerhub
Test Online
Postman
To test the API
, you can use Postman
. Here are the endpoints
for testing:
Test with an image file: Send a
POST
request to http://18.221.33.238:8081/compare_faceTest with a
base64-encoded
image: Send aPOST
request to http://18.221.33.238:8081/compare_face_base64You can download the
Postman
collection to easily access and use theseendpoints
. click here
How to Run
1. System Requirements
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: OpenVINO™ Runtime (Version: 2022.3)
2. Setup and Test
Clone the project:
Download the model from
Google Drive
and unzip it: click here
Build the
Docker
image:
Run the
Docker
container:
Send us the
machine code
and replace thelicense.txt
file you received. Then, run theDocker
container again.
To test the
API
, you can usePostman
. Here are theendpoints
for testing: Test with an image file: Send aPOST
request to http://{xx.xx.xx.xx}:8081/compare_face Test with abase64-encoded
image: Send aPOST
request to http://{xx.xx.xx.xx}:8081/compare_face_base64 You can download thePostman
collection to easily access and use theseendpoints
. click here
3. Execute the Gradio demo
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:
You can test within the following
URL
: http://127.0.0.1:9000
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