Music Feature Analyzer #

Get song metadata and AI-powered music features from audio files in Flutter.

Extract title, artist, album, duration, bitrate, album art, genre, year, and more from local audio files—then optionally run AI analysis for tempo, mood, instruments, and 20+ musical features. Android and iOS.

Install #

dependencies:
  music_feature_analyzer: ^1.0.1

flutter pub get

· License: MIT

Quick start #

Song metadata (no initialization) #

Get full song details from a file path. Uses native Android MediaMetadataRetriever and iOS AVFoundation.

import 'package:music_feature_analyzer/music_feature_analyzer.dart';

// Single file
final song = await MusicFeatureAnalyzer.metadata('/path/to/song.mp3');
// song.title, song.artist, song.album, song.duration, song.bitrate, song.genre, etc.

// Multiple files
final songs = await MusicFeatureAnalyzer.extractMetadataBatch([
  '/path/to/song1.mp3',
  '/path/to/song2.m4a',
]);

AI features (initialize once) #

Tempo, mood, instruments, energy, danceability, and more. Requires one-time initialize().

await MusicFeatureAnalyzer.initialize();

final features = await MusicFeatureAnalyzer.analyzeSong(song!);
// features.tempoBpm, features.mood, features.instruments, features.danceability, etc.

// Background processing (keeps UI responsive)
final results = await MusicFeatureAnalyzer.extractFeaturesInBackground(
  filePaths,
  onProgress: (current, total) => print('$current / $total'),
  onSongUpdated: (path, features) => {},
  onCompleted: () => print('Done'),
);

What you get #

Metadata (SongModel) #

AI features (ExtractedSongFeatures) #

From analyzeSong(), analyzeSongs(), or extractFeaturesInBackground():

• Categories: tempo, beat, energy, mood, vocals, estimatedGenre
• Lists: instruments, yamnetInstruments, moodTags
• Numeric: tempoBpm, beatStrength, danceability, loudness, valence, arousal, spectralCentroid, spectralRolloff, zeroCrossingRate, spectralFlux, complexity, confidence, and more.

API summary #

How analysis works #

• Metadata: Read directly from the file via native APIs. No model load.
• Short / unknown duration: One short segment from the middle.
• Duration ≥ 30 s: Three segments (middle of each third); numeric features averaged, genre/mood from highest-confidence segment.
• Background: extractFeaturesInBackground runs in an isolate; duration is read from file metadata when not provided.

Requirements #

• Flutter 3.0.0+, Dart 3.8.1+
• Android API 21+ · iOS 12.0+
• Platforms: Android and iOS only (no desktop or web).

Formats: MP3, WAV, FLAC, AAC, M4A, OGG, WMA, OPUS, AIFF, ALAC (and platform-supported formats).

For media library access, configure permissions in your app. See BUILD_COMPATIBILITY.md for setup; CHANGELOG.md for version history; example/README.md for a full demo.

Links #

• Pub.dev
• GitHub
• Issues

Music Feature Analyzer · MIT License · P M JESIL