FLUTTER ECOSYSTEM

Djsmk123/waveform_fft

FFT(빠른 푸리에 변환)를 사용한 실시간 오디오 시각화 및 마이크 데이터를 이용한 오디오 캡처용 플러터 패키지

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2025. 3. 17.
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waveform_fft

A Flutter package for real-time audio visualization using FFT (Fast Fourier Transform). This package captures audio input and displays it as an animated waveform using fl_chart.

Features

  • Real-time audio capture and frequency analysis
  • Customizable frequency spectrum ranges
  • Smooth animated waveform visualization
  • Support for different sample rates and buffer sizes
  • Easy-to-use API

Getting Started

Installation

Add this to your package's pubspec.yaml file:

dependencies:
  waveform_fft: ^0.0.1
Platform Setup
Android

Add the following permissions to your android/app/src/main/AndroidManifest.xml:

<uses-permission android:name="android.permission.RECORD_AUDIO" />
<uses-permission android:name="android.permission.MODIFY_AUDIO_SETTINGS" />
iOS

Add the following keys to your ios/Runner/Info.plist:

<key>NSMicrophoneUsageDescription</key>
<string>This app needs access to microphone to visualize audio.</string>
Customizing the Waveform

The WaveFormWidgetEq widget accepts several parameters for customization:

WaveFormWidgetEq(
  data: data,                                           // Frequency data
  animationDuration: Duration(milliseconds: 200),       // Animation speed
  updateInterval: Duration(milliseconds: 48),           // Update frequency
  barWidth: 5.0,                                       // Width of each bar
  maxY: 80.0,                                          // Maximum Y value
  minY: -80.0,                                         // Minimum Y value
  barColor: Colors.white,                              // Color of bars
  barAlpha: 0.5,                                       // Opacity of bars
);
Audio Capture Service

The AudioCaptureService can be customized with different sample rates and buffer sizes:

final service = AudioCaptureService(
  sampleRate: 44100,    // Default: 44100 Hz
  bufferSize: 256,      // Default: 256 samples
);

Note: The AudioCaptureService is a singleton and should be initialized once in your application.

Example

Here's a demo of the audio visualization in action:

Audio Visualization Demo

The example above demonstrates:

  • Real-time audio capture from device microphone
  • FFT processing of audio data
  • Animated waveform visualization
  • Responsive UI with start/stop recording controls

Check out the complete example code in the /example directory to see how to implement this in your app.

Frequency Spectrum

The package includes predefined frequency spectrum ranges from 0Hz to 22kHz, following standard audio frequency bands. You can customize these ranges by modifying the AudioWaveFormConstants.defaultFrequencySpectrum.

Performance Considerations
  • Higher sample rates provide better frequency resolution but require more processing power
  • Smaller buffer sizes reduce latency but may cause performance issues
  • Consider device capabilities when adjusting these parameters

Compatibility

  • Android: API 21+
  • iOS: iOS 13.0+
  • If you do not want to use raw audio data by microphone then you can use any other flutter package like record or flutter_sound etc for audio recording purpose.

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Inspiration