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👏 We have published the Face Livness Detection, Face Recognition SDK and ID Card Recognition SDK for the server.

IDCardRecognition-Docker

Introduction

The demo project demonstrates the server-based recognition capabilities for ID cards, passports, and driver's licenses.

At the core of this project lies the ID Card Recognition SDK, which has been developed to provide comprehensive support for recognizing ID cards, passports, and driver's licenses from over 180 countries.

The demo is integrated with KBY-AI's ID Card Recognition Server SDK.

For other solutions, please explore the following:

Try the API

Online Demo

You can test the SDK using images from the following URL: http://18.221.33.238:9000/

image

Postman

To test the API, you can use Postman. Here are the endpoints for testing:

SDK License

This project uses KBY-AI's Face Recognition Server SDK, which requires a license per machine.

How to run

1. System Requirements

  • CPU: 2 cores or more (Recommended: 2 cores)
  • RAM: 4 GB or more (Recommended: 8 GB)
  • HDD: 4 GB or more (Recommended: 8 GB)
  • OS: Ubuntu 20.04 or later

2. Setup and Test

  • Clone the project:

    git clone https://github.com/kby-ai/IDCardRecognition-Docker.git

  • Download the model from Google Drive: click here

    cd IDCardRecognition-Docker

wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1fmTUG7a9IoMA8QiXR9A0xf3Cr6D5UkdC' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1fmTUG7a9IoMA8QiXR9A0xf3Cr6D5UkdC" -O data.zip && rm -rf /tmp/cookies.txt

unzip data.zip

  • Build the Docker image:

    sudo docker build --pull --rm -f Dockerfile -t kby-ai-idcard:latest .

  • Run the Docker container:

    sudo docker run -v ./license.txt:/root/kby-ai-idcard/license.txt -p 8082:8080 kby-ai-idcard

  • Send us the machine code and replace the license.txt file you received. Then, run the Docker container again.

    image

    image

  • 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://{xx.xx.xx.xx}:8082/idcard_recognition

    Test with a base64-encoded image: Send a POST request to http://{xx.xx.xx.xx}:8081/idcard_recognition_base64

    You can download the Postman collection to easily access and use these endpoints. 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:

    pip install gradio

  • Run the demo Run it using the following command:

    cd gradio
python demo.py

  • You can test within the following URL:
    http://127.0.0.1:9000

About SDK

1. Initializing the SDK

  • Step One

    First, obtain the machine code for activation and request a license based on the machine code.

    machineCode = getMachineCode()
print("machineCode: ", machineCode.decode('utf-8'))

  • Step Two

    Next, activate the SDK using the received license.

    setActivation(license.encode('utf-8'))

    If activation is successful, the return value will be SDK_SUCCESS. Otherwise, an error value will be returned.

  • Step Three

    After activation, call the initialization function of the SDK.

    initSDK()

    If initialization is successful, the return value will be SDK_SUCCESS. Otherwise, an error value will be returned.

2. APIs

  • ID Card Recognition

    The SDK provides a single API for ID card recognition.

    The function can be used as follows:

    ret = idcardRecognition(base64_image.encode('utf-8'))

    The function accepts only one parameter, which should be the base64-encoded format of the image (e.g., JPG, PNG, etc.).

    If the recognition is successful, the function will return a JSON-formatted string containing the recognized information. In case of failure, the return value will be NULL.