Face Recognition Linux SDK

Check the likelihood that two faces belong to the same person. You will get a confidence score and thresholds to evaluate the similarity. Feel free to use our MiniAI Face Recognition Linux SDK.

Note

• Our 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 Recognition 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-FaceSDK-LinuxServer.deb

3. Request License and Update:

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

   $ cd /opt/miniai/face-rec-service
   $ sudo ./MiRequest request /home/ubuntu/Download/trial_key.miq

$ sudo ./MiRequest update /home/ubuntu/Download/trial_30.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-facesvc.service', 'Mini-fdsvc.service', the server has been installed successfully. Refer the below image.

• POST http://127.0.0.1:8083/api/face_detect Face Detection, Face Attributes API

• POST http://127.0.0.1:8083/api/face_detect_base64 Face Detection, Face Attributes API

• POST http://127.0.0.1:8083/api/face_match Face Matching API

• POST http://127.0.0.1:8083/api/face_match_base64 Face Matching API

• URL: http://127.0.0.1:8083/api/face_detect
• Method: POST
• Form Data:
  • image: The image file (PNG, JPG, etc.) to be analyzed. This should be provided as a file upload.

• URL: http://127.0.0.1:8083/api/face_detect_base64
• Method: POST
• Raw Data:
  • JSON Format: { "image": "--base64 image data here--" }

The API returns a JSON object with the recognized details from the input Face image. Here is an example response:

We have included a Gradio demo to showcase the capabilities of our Face Recognition 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/FaceRecognition-Linux.git
   pip install -r requirement.txt
   cd 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 Recognition 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 using pip install requests)

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

import requests

# URL of the web API endpoint
url = 'http://127.0.0.1:8083/api/face_detect'

# Path to the image file you want to send
image_path = './test_image.jpg'

# Read the image file and send it as form data
files = {'image': open(image_path, 'rb')}

try:
    # Send POST request
    response = requests.post(url, files=files)

    # Check if the request was successful
    if response.status_code == 200:
        print('Request was successful!')
        # Parse the JSON response
        response_data = response.json()
        print('Response Data:', response_data)
    else:
        print('Request failed with status code:', response.status_code)
        print('Response content:', response.text)

except requests.exceptions.RequestException as e:
    print('An error occurred:', e)

Feel free to Contact US to get a trial License. We are 24/7 online on WhatsApp.

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.

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