A lightweight Flutter package that provides a single function to determine whether a face captured by the camera is live or a spoof (e.g., photo, video, or mask). Designed for secure facial authentication, it leverages machine learning models to analyze micro-movements and depth cues. The package supports both Android and iOS platforms, making it ideal for integrating real-time liveness checks into apps requiring biometric security. It simplifies implementation with minimal setup and seamless integration via the Flutter ecosystem.
Use cases
- Biometric authentication in banking apps
- Secure login systems
- Identity verification services
- Preventing spoof attacks in facial recognition
- Real-time face validation during onboarding
Key features
- Single-function API
- Cross-platform support (Android & iOS)
- Lightweight and easy to integrate
- Uses ML for accurate liveness detection
- Minimal configuration required
Suitable for
- Developers building secure facial recognition features
- Apps requiring anti-spoofing measures
- Mobile applications with identity verification workflows
- Teams seeking quick integration of liveness detection
Considerations
- Relies on device camera quality and lighting conditions
- May require model updates for improved accuracy
- Performance varies slightly across different hardware
- Not suitable for offline-only use without bundled models
- Requires proper user permissions for camera access