FaceAttribute - Flutter

This Flutter demo app demonstrates face recognition, face liveness detection, face auto-capture, age/gender detection, automatic face capture, face quality facial occlusion, eye closure.

Overview

This demo project integrates several facial recognition technologies, including 3D passive face liveness detection, face recognition, automatic face capture, and analysis of various face attributes such as age, gender, face quality, facial occlusion, eye closure, and mouth opening.

The system utilizes face liveness detection technology to generate a real-time liveness score based on a single image captured by the camera.

Additionally, the demo offers face recognition capabilities, enabling enrollment from a gallery and real-time identification of faces captured by the camera.

The demo also features an automatic face capture function that verifies various facial attributes, such as face quality, facial orientation (yaw, roll, pitch), facial occlusion (e.g., mask, sunglass, hand over face), eye closure, mouth opening, and the position of the face within the region of interest (ROI).

Github

Google Play

Screenshots

How to Run

1. Flutter Setup

Make sure you have Flutter installed.

We have tested the project with Flutter version 3.22.3.

If you don't have Flutter installed, please follow the instructions provided in the official Flutter documentation:

2. Running the App

Run the following commands:

flutter pub upgrade
flutter run

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

FaceSDK Plugin

1.1 `Face SDK` Setup

Android

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

  • Add SDK to the project in settings.gradle

include ':libfacesdk'

1.2 `FaceSDK Plugin` Setup

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

  • Add the dependency in 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 Usage

2.1 FacesdkPlugin

  • 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,
      'check_eye_closeness': true,
      'check_face_occlusion': true,
      'check_mouth_opened': true,
      'estimate_age_gender': true
    });

  • Extract face feature using the extractFaces method:

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

  • Calculate 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 following file in the Github repository.

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

PreviousFaceAttribute - iOSNextIDCardRecognition - Android

Last updated