• ✅ Real-time frequency detection using FFT + autocorrelation
• ✅ Visual gauge with needle responsiveness and smooth animations
• ✅ Color-coded feedback: Flat (♭) = Red/Left, Sharp (♯) = Yellow/Right, In Tune = Green
• ✅ Precision within ±1.5 cents for perfect tuning
• ✅ Automatic string detection with manual override option
• ✅ Amplitude-based signal validation for clean readings
• ✅ Subtle gradient tint shifts (red → orange → green) reinforce tuning status

• Guitar: Standard, Drop D, Drop C, Open G, DADGAD
• Bass Guitar: 4-string standard tuning
• Ukulele: Standard tuning (G C E A)
• Violin: Standard tuning (G D A E)
• Mandolin: Standard tuning (G D A E)
• Custom tuning creation and management

• Modern gradient design with smooth animations
• Dark/Light theme support for stage performance
• Intuitive string selection with visual feedback
• Responsive design for all screen sizes

• Haptic feedback when perfectly in tune
• Color-blind safe visual indicators
• High contrast ratios for visibility
• Voice-over support

• Reference frequency adjustment (A4 = 430-450 Hz in 0.5 Hz increments)
• Microphone sensitivity levels
• Theme selection (Light/Dark)
• Language selection (English/Portuguese)
• Haptic feedback toggle
• Keep screen on during tuning

• Flutter 3.9.0 or higher
• Dart SDK 3.0.0 or higher
• Android Studio / VS Code with Flutter extension
• Physical device or emulator with microphone access

1. Clone the repository

   git clone https://github.com/pbalduino/menio_tuner.git
   cd menio_tuner

2. Install dependencies

   flutter pub get

3. Run the app

   flutter run

# Check Flutter installation
flutter doctor
# Run tests
flutter test
# Build for Android
flutter build apk
# Build for iOS
flutter build ios

lib/
├── main.dart # App entry point
├── app.dart # App configuration
├── screens/ # UI screens
│ ├── tuner_screen.dart # Main tuning interface
│ ├── settings_screen.dart # Settings and preferences
│ └── tunings_screen.dart # Tuning selection
├── widgets/ # Reusable UI components
│ └── tuner_gauge.dart # Custom gauge widget
├── services/ # Core business logic
│ ├── audio_processor.dart # Audio input processing
│ └── signal_processing.dart # FFT and frequency analysis
└── data/ # Data models and storage
 └── tunings.dart # Tuning definitions

• State Management: StatefulWidget (upgrading to Riverpod)
• Audio Processing: ✅ FFT + Autocorrelation via flutter_audio_capture
• UI Framework: Flutter Material Design
• Platform Integration: ✅ Native audio permissions via permission_handler

• Buffer Size: 4096 samples @ 44.1 kHz (~93ms latency)
• Frequency Range: 80-2000 Hz (covers guitar fundamentals)
• Noise Filtering: Low-pass filter at 2 kHz
• Smoothing: Exponential moving average for stable readings

• ✅ Audio processing pauses when app is backgrounded
• ✅ Efficient memory management with proper disposal
• ✅ Smooth 60fps animations with minimal jank
• ✅ Battery-optimized microphone usage
• ✅ Lifecycle-aware audio stream management
• ✅ Permission-based audio access control
• ✅ Optional debug mode with logging & diagnostics overlay

• (削除) UI Design & Navigation (削除ここまで) ✅
• (削除) Real-time Audio Input Processing (削除ここまで) ✅ (#1)
• (削除) Tuning Selection Navigation (削除ここまで) ✅ (#2)

• (削除) Frequency Smoothing (削除ここまで) ✅ (#3)
• (削除) Fix Default String Selection (削除ここまで) ✅ (#17)
• (削除) Debug Logging (削除ここまで) ✅ (#18)
• Internationalization (i18n) (#19)
• Haptic Feedback (#4)
• Color-blind Accessibility (#5)
• Dark/Light Theme Support (#7)
• State Management (Riverpod) (#9)

• Custom Tuning Creation (#13)
• Multi-instrument Support (#16)
• Advanced Settings (#12, #15)

View all issues →

We welcome contributions! Please see our Contributing Guidelines for details.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests if applicable
5. Commit your changes (git commit -m 'Add amazing feature')
6. Push to the branch (git push origin feature/amazing-feature)
7. Open a Pull Request

• Follow Dart Style Guide
• Use flutter analyze to check for issues
• Format code with dart format .
• Write tests for new features

This project is licensed under the MIT License - see the LICENSE file for details.

• Flutter team for the amazing framework
• Open source audio processing libraries
• Musicians who provided feedback and testing
• Contributors who help make this project better

• 🐛 Bug Reports: Create an issue
• 💡 Feature Requests: Create an issue
• 💬 Questions: Start a discussion