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🆔 ID Document Liveness Detection - Linux - Here

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FaceRecognition-Flutter

Overview

This repository demonstrates both face liveness detection and face recognition technology for Flutter on Android and iOS platforms.

In this repository, we integrated KBY-AI's face liveness detection and face recognition technology into this Flutter project for both Android and iOS.

◾FaceSDK(Mobile) Details

◾FaceSDK(Mobile) Product List

To get Face SDK(server), please visit products here.

Try with Demo App

Google Play

App Store

Performance Video

You can visit our YouTube video here to see how well our demo app works.

Screenshots

SDK License

This repo integrated KBY-AI's face recognition SDK, which requires a license for each application ID.

• The code below shows how to use the license: https://github.com/kby-ai/FaceRecognition-Flutter/blob/76f1982ed301e219d864f22b584e9e34222464ea/lib/main.dart#L68-L90

• To request a license, please contact us:
  🧙Email: [email protected]
  🧙Telegram: @kbyaisupport
  🧙WhatsApp: +19092802609
  🧙Discord: KBY-AI
  🧙Teams: KBY-AI
  

How To Run

1. Flutter Setup

Make sure you have Flutter installed.
We have tested the project with Flutter version 3.35.7.
If you don't have Flutter installed, please follow the instructions provided in the official Flutter documentation here.

2. Running the App

Run the following commands:

  flutter clean
  flutter pub get
  flutter run

If you plan to run the iOS app, please refer to the following link for detailed instructions.

3. Building the APK for Release

To create a release APK, configure ProGuard as described in this file:https://github.com/kby-ai/FaceRecognition-Flutter/blob/76f1982ed301e219d864f22b584e9e34222464ea/android/app/proguard-rules.pro#L22-L22

About SDK

1. Setup

1.1 Setting Up Face SDK library

Android

• Copy the Face SDK library(folder libfacesdk) to the folder android in your project.
  

• Add Face SDK library to the project in settings.gradle in the folder android in your project.

  include ':libfacesdk'

  1.2 Setting Up Fotoapparat library

  Android

• Copy Fotoapparat library (folder libfotoapparat) to the folder android in your project.
  

• Add Fotoapparat library to the project in settings.gradle in the folder android in your project.

  include ':libfotoapparat'

  1.3 Setting Up Face SDK Plugin

• Copy the folder facesdk_plugin to the root folder of your project.
  

• Add the dependency in your pubspec.yaml file.

  facesdk_plugin:
    path: ./facesdk_plugin

• Import the facesdk_plugin package.

  import 'package:facesdk_plugin/facesdk_plugin.dart';
  import 'package:facesdk_plugin/facedetection_interface.dart';

  2 API Usages

  2.1 Facesdk Plugin

• Activate the FacesdkPlugin by calling the setActivation method:

  final _facesdkPlugin = FacesdkPlugin();
  ...
  await _facesdkPlugin
          .setActivation(
              "Os8QQO1k4+7MpzJ00bVHLv3UENK8YEB04ohoJsU29wwW1u4fBzrpF6MYoqxpxXw9m5LGd0fKsuiK"
              "fETuwulmSR/gzdSndn8M/XrEMXnOtUs1W+XmB1SfKlNUkjUApax82KztTASiMsRyJ635xj8C6oE1"
              "gzCe9fN0CT1ysqCQuD3fA66HPZ/Dhpae2GdKIZtZVOK8mXzuWvhnNOPb1lRLg4K1IL95djy0PKTh"
              "BNPKNpI6nfDMnzcbpw0612xwHO3YKKvR7B9iqRbalL0jLblDsmnOqV7u1glLvAfSCL7F5G1grwxL"
              "Yo1VrNPVGDWA/Qj6Z2tPC0ENQaB4u/vXAS0ipg==")
          .then((value) => facepluginState = value ?? -1);  

• Initialize the FacesdkPlugin:

  await _facesdkPlugin
          .init()
          .then((value) => facepluginState = value ?? -1)

• Set parameters using the setParam method:

  await _facesdkPlugin
        .setParam({'check_liveness_level': livenessLevel ?? 0})

• Extract faces using the extractFaces method:

  final faces = await _facesdkPlugin.extractFaces(image.path)

• Calculate the similarity between faces using the similarityCalculation method:

  double similarity = await _facesdkPlugin.similarityCalculation(
              face['templates'], person.templates) ??
          -1;

  2.2 FaceDetectionInterface

  To build the native camera screen and process face detection, please refer to the lib/facedetectionview.dart file in the repository.

This file contains the necessary code for implementing the camera screen and performing face detection.