flutter_audio_toolkit 0.3.5

Advanced audio plugin with native support for MP3/WAV/OGG to AAC/M4A conversion, precise trimming, waveform extraction, and comprehensive noise detection & analysis

Changelog

0.3.5 - 2025-06-26

• #1 Bug Fix (Compile-time error on iOS)

0.3.4 - 2025-06-14

🌐 Web Platform Support (Limited)

• NEW: Added web platform support with limited functionality
• Waveform Extraction: Web implementation generates realistic fake waveforms
• Format Support Detection: Browser codec support checking via HTML Audio API
• Audio Info Extraction: Basic metadata retrieval for web-accessible audio files
• Audio Player Compatibility: Existing audio player widgets work on web
• Clear Error Messages: Helpful error messages for unsupported operations
• Documentation: Updated README with web platform limitations and capabilities

🔧 Technical Improvements

• Modern Web APIs: Uses package:web and dart:js_interop (no deprecated APIs)
• Dependency Updates: Added flutter_web_plugins and web package dependencies
• Code Quality: All web implementations pass static analysis
• Platform Detection: Proper platform-specific feature availability

⚠️ Web Platform Limitations

• Audio conversion and trimming are not supported (browser security restrictions)
• Waveform extraction returns generated patterns (Web Audio API CORS limitations)
• File system access restricted to HTTP URLs only
• Performance is limited compared to native platforms

0.3.3 - 2025-06-10

• Bug Fixes

0.3.2 - 2025-06-13

🆕 Audio Player Features

🎵 Interactive Audio Players with Waveform Visualization

• TrueWaveformAudioPlayer: Audio player using real extracted waveform data
• FakeWaveformAudioPlayer: Audio player using generated waveform patterns
• Interactive Waveform: Tap-to-seek functionality on waveform display
• Customizable Controls: Configurable play/pause, volume, progress, and time labels
• Flexible Control Layouts: Position controls top, bottom, overlay, left, or right
• Real-time Progress: Visual progress overlay showing played portion
• Position Indicator: Real-time playback position marker on waveform
• Event Callbacks: Comprehensive event system for state, position, and error handling

🎮 Player Configuration Options

• AudioPlayerControlsConfig: Complete control customization (buttons, colors, positions)
• WaveformVisualizationConfig: Waveform styling and interaction settings
• AudioPlayerColors: Comprehensive color theming for all UI elements
• AudioPlayerCallbacks: Event handling for all player interactions

🎨 Enhanced Visual Features

• Customizable Waveform Styles: Colors, gradients, line widths, opacity
• Progress Visualization: Different colors for played/unplayed portions
• Control Theming: Fully customizable button colors and styles
• Responsive Design: Adaptive layouts for different screen sizes

🔧 Implementation Details

• Native Audio Playback: Platform-optimized audio rendering
• Memory Efficient: Optimized waveform rendering and audio processing
• Background Threading: Audio operations on background threads
• State Management: Robust state management for player controls and visualization

📚 Documentation

• Complete Audio Player Guide: Comprehensive guide with examples and best practices
• Example Integration: Full working example in demo app
• API Documentation: Detailed parameter documentation for all new classes

0.3.1 - 2025-06-10

• Fixed Dart Format Issues

0.3.0 - 2025-06-10

🆕 Major New Features

🔊 Noise Detection & Audio Quality Analysis

• Comprehensive Audio Analysis: Deep analysis of audio quality with detailed metrics
• 15+ Noise Type Detection: Identify background noises like car horns, dog barking, construction, etc.
• Audio Quality Metrics: Peak levels, SNR, dynamic range, LUFS loudness measurement
• Frequency Analysis: Spectral analysis with problematic frequency band detection
• Quality Grading: Automatic quality scoring (Excellent, Good, Fair, Poor, Very Poor)
• Issue Detection: Automatic detection of clipping, distortion, and balance problems
• Network Analysis: Analyze audio quality directly from URLs

🎨 Enhanced Waveform Generation

• 25+ Waveform Patterns: Expanded from 7 to 25+ realistic patterns
• New Pattern Categories:
  • Basic Waveforms: square, sawtooth, triangle (added to existing sine, random, etc.)
  • Musical Patterns: electronic, classical, rock, jazz, ambient
  • Voice & Speech: podcast, audiobook (improved speech patterns)
  • Nature & Relaxation: whiteNoise, pinkNoise, heartbeat, ocean, rain, binauralBeats
• Visual Styling System: 9 predefined color schemes with customizable visual properties
• Themed Generation: Automatic pattern-to-style matching for optimal visual presentation
• Style Application: Apply visual styles to existing waveform data

📊 Advanced Metadata Extraction

• Comprehensive Metadata: Extract 35+ metadata fields from audio files
• Cover Art Support: Extract and handle embedded album artwork
• Technical Details: Detailed codec, bitrate, and encoding information
• Date/Time Fields: Recording dates, release dates with proper DateTime handling
• Custom Fields: Support for additional metadata through extensible system

🔧 Enhanced Features

• Improved Algorithm Accuracy: Better pattern generation algorithms for all waveform types
• Memory Optimization: More efficient audio processing and analysis
• Progress Tracking: Enhanced progress callbacks for all new operations
• Error Handling: Robust error handling for network operations and file processing

🎛️ New API Methods

// Noise Detection & Analysis
final analysisResult = await toolkit.analyzeAudioNoise(inputPath);
final networkAnalysis = await toolkit.analyzeAudioNoiseFromUrl(url, localPath);

// Enhanced Waveform Generation
final themedWaveform = toolkit.generateThemedWaveform(pattern: WaveformPattern.jazz);
final styledWaveform = toolkit.generateStyledWaveform(pattern: WaveformPattern.electronic, style: WaveformColorSchemes.neon);
final waveformWithStyle = existingWaveform.withStyle(WaveformColorSchemes.fire);

// Advanced Metadata
final metadata = await toolkit.extractMetadata(inputPath);
final networkMetadata = await toolkit.extractMetadataFromUrl(url, localPath);

🏗️ Architecture Improvements

• Modular Design: Separated concerns into specialized analyzer and generator modules
• Type Safety: Enhanced type definitions for all new models
• Documentation: Comprehensive dartdoc documentation for all new APIs
• Testing: 100+ new test cases covering all noise detection and enhanced waveform features

📋 New Data Models

• NoiseDetectionResult - Complete analysis results
• AudioQualityMetrics - Detailed quality measurements
• FrequencyAnalysis - Spectral analysis data
• DetectedNoise - Individual noise detection results
• WaveformStyle - Visual styling configuration
• AudioMetadata - Comprehensive metadata container

0.2.0 - 2025-06-08

Added

• Multi-Platform Support: Added support for macOS, Linux, and Windows platforms
• macOS Implementation: Full native implementation using AVFoundation (same as iOS)
• Linux & Windows: Basic plugin structure with platform-specific error handling
• Platform Documentation: Updated README with comprehensive platform support matrix
• Desktop Compatibility: Plugin now declares support for all desktop platforms

Enhanced

• Updated platform support matrix in README
• Added platform-specific implementation notes
• Improved plugin architecture for cross-platform compatibility

Technical Details

• macOS: Complete AVFoundation implementation for audio conversion, trimming, and waveform extraction
• Linux: GTK-based plugin structure (requires FFmpeg/GStreamer for full functionality)
• Windows: Win32 plugin structure (requires Media Foundation/FFmpeg for full functionality)

Notes

• Desktop platforms (Linux, Windows) have basic plugin structure but require additional audio processing libraries
• macOS has full feature parity with iOS using the same AVFoundation APIs

0.1.0 - 2025-06-07

Added

• Fake Waveform Generation: Generate realistic waveform patterns for testing and previews
• 7 Waveform Patterns: Sine, Random, Music, Speech, Pulse, Fade, and Burst patterns
• Network URL Support: Process audio files from network URLs with fake waveform generation
• Modular Architecture: Complete refactoring of example app with Provider state management
• Enhanced Example App: Added fake waveform UI with pattern selection and color-coded display
• Pattern-specific amplitude algorithms for realistic waveform simulation
• URL validation and network audio file support
• Comprehensive testing for fake waveform functionality

Enhanced

• Example app refactored from 1180 lines to 122 lines (89% reduction)
• Added Provider state management pattern
• Extracted business logic into service classes
• Modularized UI components into reusable widgets
• Improved error handling and progress tracking

Fixed

• Library formatting and method signature issues
• Enhanced dependency management

0.0.1 - 2025-06-07

Added

• Initial release of flutter_audio_toolkit plugin
• Audio conversion from MP3, WAV, OGG to AAC/M4A formats
• Audio trimming with precise time range selection
• Waveform data extraction for visualization
• Native implementations for Android (MediaCodec/MediaMuxer) and iOS (AVFoundation)
• Progress tracking for all operations
• Audio file information retrieval
• Comprehensive example app with UI for all features
• Full test coverage including unit and widget tests
• Platform-specific permission handling
• Error handling and validation
• Performance optimized for large audio files

Platform Support

• Android: API 21+ using MediaCodec, MediaMuxer, MediaExtractor
• iOS: 12.0+ using AVAssetExportSession, AVAudioConverter, AVAssetReader

Features

• Convert audio files between formats
• Trim audio files to specific time ranges
• Extract waveform amplitude data
• Get detailed audio file information
• Real-time progress callbacks
• Native performance optimization