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Face Liveness Detection Linux SDK

A 100% spoofing-prevention rate for both 3D printed and resin facial masks, confirms MiniAiLive® as a leading facial recognition solution for preventing biometric fraud in remote applications, such as online banking, requiring identity verification before granting access to sensitive data or valuable assets. Feel free to use our MiniAI 3D Face Passive Liveness Detection (face anti-spoofing) Linux SDK.

Note

SDK is fully on-premise, processing all happens on hosting server and no data leaves server.

• Installation Guide
• API Details
• Gradio Demo
• Python Test API Example

• Python 3.6+
• Linux
• CPU: 2 cores or more
• RAM: 8 GB or more

1. Download the Face Liveness Detection Linux Server Installer:

   Download the Server installer for your operating system from the following link:

   Download the On-premise Server Installer

2. Install the On-premise Server:

   Run the installer and follow the on-screen instructions to complete the installation. Go to the Download folder and run this command.

   $cd Download$ sudo dpkg -i --force-overwrite MiniAiLive-FaceLiveness-LinuxServer.deb

You can refer our Documentation here.https://docs.miniai.live

3. Request License and Update:

   You can generate the License Request file by using this command:

   $cd /opt/mini-faceliveness/$ sudo ./MiRequest request /home/ubuntu/Download/trial_request.miq

Then you can see the license request file on your directory, and send it to us via email or WhatsApp. We will send the license based on your Unique Request file, then you can upload the license file to allow to use. Refer the below images.

$ sudo ./MiRequest update /home/ubuntu/Download/Faceliveness_trial_linux.mis

4. Verify Installation:

   After installation, verify that the On-premise Server is correctly installed by using this command:

   $ systemctl list-units --state running

   If you can see 'Mini-faceliveness-svc.service', the server has been installed successfully. Refer the below image.

• POST http://127.0.0.1:8092/api/check_liveness Face Liveness Detection API
• POST http://127.0.0.1:8092/api/check_liveness_base64 Face Liveness Detection API

• URL:http://127.0.0.1:8092/api/check_liveness
• Method:POST
• Form Data:
  • image: The image file (PNG, JPG, etc.) to be analyzed. This should be provided as a file upload.

• URL:http://127.0.0.1:8092/api/check_liveness_base64
• Method:POST
• Raw Data:
  • JSON Format:{"image": "--base64 image data here--"}

The API returns a JSON object with the liveness result of the input face image. Here is an example response:

We have included a Gradio demo to showcase the capabilities of our Face Liveness Detection SDK. Gradio is a Python library that allows you to quickly create user interfaces for machine learning models.

1. Install Gradio:

   First, you need to install Gradio. You can do this using pip:

   git clone https://github.com/MiniAiLive/FaceLivenessDetection-Linux.gitpip install -r requirement.txtcd gradio

2. Run Gradio Demo:

   python app.py

To help you get started with using the API, here is a comprehensive example of how to interact with the Face Liveness Detection API using Python. You can use API with another language you want to use like C++, C#, Ruby, Java, Javascript, and more

• Python 3.6+
• requests library (you can install it usingpip install requests)

This example demonstrates how to send an image file to the API endpoint and process the response.

importrequests# URL of the web API endpointurl='http://127.0.0.1:8092/api/check_liveness'# Path to the image file you want to sendimage_path='./test_image.jpg'# Read the image file and send it as form datafiles= {'image':open(image_path,'rb')}try:# Send POST requestresponse=requests.post(url,files=files)# Check if the request was successfulifresponse.status_code==200:print('Request was successful!')# Parse the JSON responseresponse_data=response.json()print('Response Data:',response_data)else:print('Request failed with status code:',response.status_code)print('Response content:',response.text)exceptrequests.exceptions.RequestExceptionase:print('An error occurred:',e)

Feel free toContact US to get a trial License. We are 24/7 online onWhatsApp.

MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies. We provide cutting-edge solutions for various industries, leveraging the power of AI to drive innovation and efficiency.

For any inquiries or questions, please contact us onWhatsApp.