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FacePlugin Face Recognition SDK — Flutter (Fully On-Premise)

Ready in ~15 minutes (after runtime download): Drop Android AAR + iOS frameworks → Run the example on a phone Jump: Quick start · Get the runtimes · Run the demo · Integrate into your app · Dart API

Customer repo name: FaceRecognition-Flutter

Quick start checklist

Use this for the example app (check each box in order):

• Clone FaceRecognition-Flutter and run dart run tool/bootstrap.dart (or flutter pub get at root + example/)
• Fix anything flutter doctor reports (Android toolchain, Xcode, licenses, JDK)
• Download runtimes from Google Drive
• Android: copy facerecognitionsdk.aar → example/android/libfacesdk/
• iOS: unzip frameworks → ios/Frameworks/ (facerecognitionsdk, FaceRecognitionEngine, onnxruntime)
• iOS (macOS): cd example/ios && pod install
• cd example && flutter run (physical device recommended)
• Home screen status bar shows Ready → Enroll / Identify / Capture / Attribute

Integrating into your own app? Skip to Integrate into your own app — Android AAR path is different (…/android/libs/ under the plugin dependency). Full API and layer guide: doc.faceplugin.com.

Introduction

FacePlugin Face Recognition SDK for Flutter is a fully on-device biometric plugin for Android and iOS. Enroll faces, identify in 1:N with VideoWorker, capture with an oval coach, and read attributes with 2D liveness — all on the phone. The pub package face_recognition_sdk wraps the same native engines as our FaceRecognitionSDK Android and iOS apps.

All processing stays on the device. No biometric data is sent to FacePlugin cloud — built for KYC, eKYC, and cross-platform mobile onboarding.

This repository contains:

Folder	Purpose
Repository root	face_recognition_sdk — the Flutter plugin you depend on in your app
example/	Full demo (Enroll, Identify, Capture, Attribute, Settings, About)

Native binaries are not on GitHub (too large). Download them from Google Drive (links below) and copy into the paths shown.

Main Functionalities

Feature	Supported
Gallery enroll (single-face template)	✓
Live 1:N identify with VideoWorker	✓
2D liveness / anti-spoofing on identify	✓
Oval capture coach with optional enroll	✓
Gallery attributes, landmarks, age, gender, emotion	✓
Local person database (demo)	✓
Settings (thresholds / clear DB)	✓

Product List

Platform	Repository
Android (Recognition)	FaceRecognition-Android
iOS (Recognition)	FaceRecognition-iOS
React Native (Recognition)	FaceRecognition-React-Native
Flutter (Recognition)	FaceRecognition-Flutter (this repo)
Ionic Capacitor (Recognition)	FaceRecognition-Ionic-Capacitor
Ionic Cordova (Recognition)	FaceRecognition-Ionic-Cordova
Windows (Recognition)	FaceRecognition-Windows
Linux / Docker (Recognition)	FaceRecognition-Docker
Android (Liveness)	FaceLivenessDetection-Android
iOS (Liveness)	FaceLivenessDetection-iOS
Windows (Liveness)	FaceLivenessDetection-Windows
Linux / Docker (Liveness)	FaceLivenessDetection-Docker

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Before you start

Step	What you need
1	Flutter (3.44+ recommended). Run flutter doctor and fix reported issues
2	JDK 17+ for Android. Prefer Android Studio’s bundled JDK. JAVA_HOME must point to the JDK home (folder that contains bin), not to bin itself. Optionally: flutter config --jdk-dir <path-to-jdk-home>
3	Accept Android licenses: flutter doctor --android-licenses
4	Physical device recommended (camera / liveness; emulator is limited)
5	Android facerecognitionsdk.aar and iOS frameworks — see Get the runtimes
6	Demo licenses are in example/lib/core/constants/license.dart (Android com.faceplugin.facerecognitionsdk, iOS com.faceplugin.facerecognition.app). Request a new key only if you change applicationId / bundle id — see SDK License

You can run the example app as-is after placing the runtimes. Home tiles unlock when the status bar shows Ready.

System requirements

Platform	Requirement
Flutter	3.44+ (see pubspec.yaml)
Android	minSdk 24, physical device recommended
iOS	iOS 13+, physical device recommended
Dart	3.3+

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Get the runtimes

Same Google Drive packs as FaceRecognitionSDK Android / iOS (includes frc.fpk models inside the runtime).

Android

Google Drive — Android

File	Example app path	Your own app path
facerecognitionsdk.aar	example/android/libfacesdk/facerecognitionsdk.aar	Your app’s android/libfacesdk/facerecognitionsdk.aar + include(":libfacesdk") (copy the module from the example — do not use implementation(files(…aar)) on the plugin)

iOS

Google Drive — iOS

Unzip into ios/Frameworks/:

ios/Frameworks/
├── facerecognitionsdk.framework
├── FaceRecognitionEngine.framework
└── onnxruntime.framework

Then on a Mac: dart run tool/bootstrap.dart (builds matching .xcframeworks) and cd example/ios && pod install. CocoaPods links the .xcframeworks into the plugin pod — plain .framework alone often leaves undefined FaceRecognitionSDK symbols under use_frameworks!.

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Run the demo

git clone https://github.com/Faceplugin-ltd/FaceRecognition-Flutter.git
cd FaceRecognition-Flutter
dart run tool/bootstrap.dart
# Place AAR + iOS frameworks as above
cd example
flutter run

Keep demo ids for the included license:

Platform	Id
Android applicationId	com.faceplugin.facerecognitionsdk
iOS bundle id	com.faceplugin.facerecognition.app

1. Wait for the home status bar → Ready.
2. Use Enroll, Identify, Capture, and Attribute for on-device 1:N matching, oval capture, attributes, and 2D liveness.

Screenshots

Home	Identify	Capture

Capture result	Attribute	Attribute (emotion)

Attribute (quality)	Settings	About

Home (tiles)	Attribute (liveness)

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SDK License

Licenses are offline and bound to your applicationId / bundle identifier.

The sample app already includes a valid key for com.faceplugin.facerecognitionsdk. You only need a new key if you use a different id.

How to get a license

The code below shows how to use the license:

FaceRecognition-Flutter/example/lib/core/constants/license.dart

Lines 6 to 14 in 7ecff0a

	const androidApplicationId = 'com.faceplugin.facerecognitionsdk';
	const iosBundleId = 'com.faceplugin.facerecognition.app';
	const androidLicense =
	'FP1.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';
	const iosLicense =
	'FP1.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';

FaceRecognition-Flutter/example/lib/services/sdk_service.dart

Lines 28 to 39 in 7ecff0a

	final act = await fr.setActivation(demoLicense());
	debugPrint('[FaceRecognition] setActivation=$act');
	if (act != fr.sdkSuccess) {
	final detail = await fr.lastLicenseError();
	_status = '${_statusLabel(act)}${detail.isNotEmpty ? ': $detail' : ''}';
	_ready = false;
	_loading = false;
	notifyListeners();
	return;
	}
	final code = await fr.init();

Please contact us to get a license for your own app.

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Integrate into your own app

You need the Flutter plugin + native runtimes. You do not need the example UI or person database (those are demo-only).

1. Add a path or git dependency:

dependencies:
  face_recognition_sdk:
    git:
      url: https://github.com/Faceplugin-ltd/FaceRecognition-Flutter.git

Or path:

dependencies:
  face_recognition_sdk:
    path: ../FaceRecognition-Flutter

2. Copy runtimes:

Platform	Copy to
Android	Copy example/android/libfacesdk/ into your app android/libfacesdk/, put facerecognitionsdk.aar there, and include(":libfacesdk") in settings.gradle(.kts). (Do not implementation(files(…aar)) inside the plugin — AGP will fail bundleDebugAar.)
iOS	Plugin checkout ios/Frameworks/ (three frameworks), then pod install

3. Set your applicationId / iOS bundle id and request a license for that id (not the demo id).

4. Permissions: camera + photo library (see example AndroidManifest.xml / Info.plist).

5. Minimal usage:

import 'package:face_recognition_sdk/face_recognition_sdk.dart';

Future<void> activate() async {
  final code = await getMachineCode(); // FPMC1.… — send when requesting a key
  final act = await setActivation('FP1.…'); // bound to YOUR applicationId / bundle id
  if (act != sdkSuccess) {
    throw StateError(await lastLicenseError());
  }
  final initCode = await init();
  if (initCode != sdkSuccess) {
    throw StateError('init failed: $initCode');
  }
}

Future<void> enrollStill(String imagePath) async {
  final faces = await faceDetection(imagePath);
  if (faces.length != 1) return;
  final template = await templateExtraction(imagePath, faces.first);
  final cropB64 = await cropFace(imagePath, faces.first);
  // Store template + crop in YOUR database
}

Thresholds (identify, liveness, pose, eye-close, Capture settings) are parameters you pass from Dart — change them freely for your product. Defaults in the example Settings match FaceRecognitionSDK Apps (identify 0.67, liveness 0.5, level 0, pose 40°, eyeclose 0.5).

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About SDK (Dart API)

Call order: getMachineCode → setActivation → init → detect / VideoWorker → deinit when done.

API	Purpose
getMachineCode()	FPMC1.… for license requests
setActivation(license)	Activate with FP1.…
init() / deinit()	Load / unload engine
faceDetection(image, param?)	Canonical FaceBox list
detect(image, crop?, flags?)	Raw engine JSON
templateExtraction / cropFace / similarity	Enroll + 1:1 match
startVideoWorker / syncVideoWorkerDatabase / ingestLiveCameraFrame	Live 1:N
videoWorkerEvents	Stream of tracking / match JSON
FaceCapture	Optional oval capture UI (package:face_recognition_sdk/capture)
lastLicenseError()	Human-readable license failure

FaceBox (cheat sheet)

Boxes include geometry (x1,y1,x2,y2), pose, liveness / quality / eyes / occlusion scores and labels, age / gender / emotion / mask / glasses, optional attributes map, and landmarks + landmarkCount.

Status codes

Code	Meaning
0	Success
1	License invalid
2	License expired
3	Not activated
4	Init failed

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Example app layout

Path	Role
example/lib/core/constants/license.dart	Demo FP1 keys only
example/lib/services/	SdkService, Settings, PersonDatabase (demo)
example/lib/screens/	Home, Identify, Capture, Attribute, Result, Settings, About

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Contact