Flutter Liveness Plugin

flutter_liveness_plugin is a Flutter plugin built specifically for Android, designed to perform real-time liveness detection using Google ML Kit and the device camera. This plugin is ideal for scenarios requiring secure identity verification, such as KYC processes, biometric login, or authentication systems.

⚠️ iOS support is currently under development.

🛠 Platform Support

Platform Supported
Android ✅ Yes
iOS 🚧 In Progress
Web ❌ No
Desktop ❌ No

🚀 Installation

Add the plugin to your Flutter project:

dependencies:
  flutter_liveness_plugin: ^0.0.8

Then run:

flutter pub get

🔌 Plugin Capabilities

This plugin performs real-time liveness detection using the front-facing camera, leveraging ML Kit's face detection API.

✅ Features:

  • Blink detection
  • Smile detection
  • On-device processing
  • Returns path to captured image (if detection is successful)

📸 Basic Usage

1. Import the package

import 'package:flutter_liveness_plugin/flutter_liveness_plugin.dart';

2. Start liveness detection

String? imagePath = (await FlutterLivenessPlugin.captureLiveImage());

if (imagePath != null && imagePath.isNotEmpty) {
  print("Liveness passed. Image path: $imagePath");
} else {
  print("Liveness check failed or was cancelled.");
}

🔁 What You Get

If liveness validation is successful, the method returns a String path to the captured image.

📋 Required Android Permissions

You must add camera permissions to your AndroidManifest.xml:

<uses-permission android:name="android.permission.CAMERA" />

Also ensure you request permissions at runtime using a package like permission_handler.

📦 How It Works Internally

  • Uses CameraX to open the front-facing camera
  • Applies ML Kit’s Face Detection to identify facial features
  • Tracks eye movement and smiling patterns
  • Validates liveness based on blink and smile conditions
  • Captures and stores the validated image locally
  • Returns the image file path via MethodChannel

🧪 Example

The plugin includes a working example app located in the example/ directory. To try it out:

cd example
flutter run

🔒 Privacy and Security

  • All face processing is done entirely on-device.
  • No internet access is used for detection.
  • No images or video frames are uploaded or shared.
  • The captured image is stored locally and accessible to your app.

📅 Roadmap

  • x Android support
  • iOS support (in progress)
  • More advanced spoofing checks (e.g. depth, light reflection)
  • Configurable detection thresholds

🙌 Contributing

We welcome contributions! Feel free to:

  • Submit a pull request
  • File an issue
  • Suggest enhancements

📃 License

This project is licensed under the MIT License.

Made with ❤️ by Sahil K.

Libraries

flutter_liveness_plugin
flutter_liveness_plugin_method_channel
flutter_liveness_plugin_platform_interface
utils/permission_utils