flutter_tflite_mobile 3.0.0 
flutter_tflite_mobile: ^3.0.0 copied to clipboard
A Flutter package for face detection, liveness verification, and document scanning using TensorFlow Lite and Google ML Kit. Supports identity verification with face capture sequences and DNI document [...]
Changelog #
All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
3.0.0 - 2025-12-04 #
2.0.0 - 2025-12-01 #
Changed #
- Updated all dependencies to pub.flutter-io.cn hosted versions
- Migrated from GitHub-hosted packages to pub.flutter-io.cn packages
- Updated minimum Flutter SDK requirement to >=3.24.0
- Updated Dart SDK requirement to ^3.6.0
Dependencies #
- api_rest_flutter_mobile: ^2.0.0
- auth_api_rest_mobile: ^2.0.0
- flutter_utils_providers: ^1.0.0
- flutter_crud_esquemas_dynamicos_mobile: ^2.0.0
- flutter_http_provider: ^2.0.0
- flutter_models_provider: ^1.0.2
- view_ui_flutter: ^1.0.0
1.0.0 - 2025-11-27 #
Added #
- Initial release of flutter_tflite_mobile
- Face detection using Google ML Kit with real-time processing
- Liveness verification with 5-position face capture sequence (center, up, down, left, right)
- Document scanning for DNI (front and back)
- Close and far distance selfie capture for biometric validation
- Mirror detection for camera orientation setup
- BLoC state management with ReconocimientoBloc
- Custom face oval progress indicator with animations
- Vibration feedback for user guidance
- Image compression support (default 30%)
- Manual capture fallback via ImagePicker
- Permission handling for camera and storage
- Support for iOS and Android platforms
Features #
FaceDetectorView: Main face detection widget with camera integrationCamaraParaDocumento: Document scanning widget with guided framesReconocimientoBloc: State management for capture workflowAnimatedFaceProgress: Animated progress indicator for face capture sequence- Face position validation with angle tolerance (+/-5 degrees)
- Automatic retry logic for failed captures
- Custom painters for face detection overlay
Metadata
Publisher
unverified uploader
Weekly Downloads
Metadata
A Flutter package for face detection, liveness verification, and document scanning using TensorFlow Lite and Google ML Kit. Supports identity verification with face capture sequences and DNI document scanning for iOS and Android.
Documentation
License
MIT (license)
Dependencies
api_rest_flutter_mobile, auth_api_rest_mobile, camera, camera_android, cupertino_icons, device_info_plus, equatable, flutter, flutter_bloc, flutter_crud_esquemas_dynamicos_mobile, flutter_http_provider, flutter_models_provider, flutter_utils_providers, font_awesome_flutter, go_router, google_mlkit_commons, google_mlkit_face_detection, image, image_picker, path_provider, permission_handler, vibration, view_ui_flutter
