awesome-repositories.com
Blog
MCP
awesome-repositories.com

Découvrez les meilleurs dépôts open-source grâce à notre recherche par IA.

ExplorerRecherches sélectionnéesAlternatives open sourceLogiciels auto-hébergésBlogPlan du site
ProjetServeur MCPÀ proposNotre méthodologiePresse
Mentions légalesConfidentialitéConditions d'utilisation
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
worldveil avatar

worldveil/dejavu

0
View on GitHub↗

Dejavu

Dejavu is a Python audio fingerprinting library and recognition engine. It functions as a digital audio signature tool used to analyze sound waves and create unique identifiers for the purposes of audio search and retrieval.

The project enables automatic music identification by matching live audio feeds or recorded clips against a database of fingerprints. It covers audio content matching and digital audio archiving to identify original source recordings from a stored collection.

The system incorporates capabilities for generating audio fingerprints, identifying audio tracks, and recognizing audio segments from both files and microphone streams.

Recherche par IA

Explorez plus de dépôts awesome

Décrivez vos besoins en langage naturel — l'IA classe des milliers de projets open source sélectionnés par pertinence.

Start searching with AI

Features

  • Audio Recognition Tools - Provides a complete engine for identifying audio tracks from digital fingerprints against a stored collection.
  • Fingerprint Indexing - Provides a keyed database indexing system to allow rapid lookup of matching audio fingerprints.
  • Track Verification - Identifies specific audio tracks by comparing live feeds or files against a database of fingerprints.
  • Audio Fingerprinting - Generates unique digital signatures from audio files to enable future identification and retrieval.
  • Audio Source Matching - Enables the comparison of two different audio samples to verify if they share the same source recording.
  • Audio Signature Tools - Provides a utility for analyzing sound waves to create unique identifiers for audio search and retrieval.
  • Audio Temporal Alignment - Validates candidate matches by ensuring the temporal distance between fingerprints is consistent across the recording.
  • Fingerprint Generation - Analyzes spectrograms to identify peak energy points, creating unique digital signatures for audio tracks.
  • Automatic Track Identification - Automatically identifies original music tracks by matching live audio feeds or clips against a fingerprint library.
  • Audio Fingerprinting Libraries - Implements a specialized Python library for creating digital signatures from audio files for track recognition.
  • Fourier Transforms - Uses Fast Fourier Transforms to convert raw audio waveforms into the frequency domain for spectral analysis.
  • Audio Fingerprint Matching - Implements a constellation-map matching system that pairs frequency peaks into hashes for robust audio identification.
  • Audio Collection Archiving - Supports digital audio archiving by generating fingerprints to organize and search large audio collections.
  • Real-Time Audio Streaming Buffers - Implements real-time audio streaming buffers to capture microphone input for continuous recognition.
  • Audio Processing - Audio fingerprinting and recognition.
6,764 stars·1,463 forks·Python·MIT·9 vues

Historique des stars

Graphique de l'historique des stars pour worldveil/dejavuGraphique de l'historique des stars pour worldveil/dejavu

Alternatives open source à Dejavu

Projets open source similaires, classés selon le nombre de fonctionnalités partagées avec Dejavu.
  • cgzirim/seek-tuneAvatar de cgzirim

    cgzirim/seek-tune

    5,583Voir sur GitHub↗

    Seek-Tune is an audio fingerprinting library that implements a Shazam-like algorithm for identifying songs from audio recordings. It generates acoustic fingerprints from audio signals and matches them against a known database to recognize songs. The library converts audio into a time-frequency spectrogram using FFT-based frequency analysis, then extracts peak points to create compact, unique fingerprints for each song. It uses combinatorial hashing to combine nearby peak pairs into hash values with time offsets, enabling efficient database lookup and matching through a peak-pair matching algo

    Goaudio-fingerprintingaudio-processinggo
    Voir sur GitHub↗5,583
  • intro-skipper/intro-skipperAvatar de intro-skipper

    intro-skipper/intro-skipper

    2,469Voir sur GitHub↗

    Intro Skipper is a media server plugin and automated playback utility designed to identify and bypass television opening sequences. It functions as an automated content sequence skipper that detects repeated introduction segments in video files to improve viewing efficiency. The tool employs audio fingerprinting to analyze audio patterns during playback, comparing waveforms against known templates to trigger skip events. It allows for the management of playback preferences across multiple client devices to determine how these opening sequences are handled. The project covers automated media

    C#jellyfinjellyfin-mediasegment-providerjellyfin-plugin
    Voir sur GitHub↗2,469
  • metabrainz/picardAvatar de metabrainz

    metabrainz/picard

    4,625Voir sur GitHub↗

    MusicBrainz Picard is a metadata tagger and audio tag editor that identifies and tags audio files using the MusicBrainz community music database. It functions as a plugin-extensible tagging framework and a scriptable file organizer capable of reading and writing tags across various audio formats including MP3, FLAC, and WAV. The project is distinguished by its acoustic fingerprint identifier, which matches unknown music files to known recordings via sonic fingerprints. It features a custom scripting language for automating metadata transformations and organizing files into structured folder h

    Pythonacoustidaudioid3
    Voir sur GitHub↗4,625
  • aubio/aubioAvatar de aubio

    aubio/aubio

    3,714Voir sur GitHub↗

    Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides a suite of tools for extracting musical features, estimating fundamental frequencies, and tracking rhythmic pulses in audio streams. The library specializes in the detection of pitch and beat, enabling the extraction of musical notes and the estimation of overall tempo. It also includes capabilities for automatic onset detection to identify the start of sonic events and the separation of audio signals into percussive transients and steady-state tonal components. The system c

    Canalysisannotationaudio
    Voir sur GitHub↗3,714
Voir les 30 alternatives à Dejavu→

Questions fréquentes

Que fait worldveil/dejavu ?

Dejavu is a Python audio fingerprinting library and recognition engine. It functions as a digital audio signature tool used to analyze sound waves and create unique identifiers for the purposes of audio search and retrieval.

Quelles sont les fonctionnalités principales de worldveil/dejavu ?

Les fonctionnalités principales de worldveil/dejavu sont : Audio Recognition Tools, Fingerprint Indexing, Track Verification, Audio Fingerprinting, Audio Source Matching, Audio Signature Tools, Audio Temporal Alignment, Fingerprint Generation.

Quelles sont les alternatives open-source à worldveil/dejavu ?

Les alternatives open-source à worldveil/dejavu incluent : cgzirim/seek-tune — Seek-Tune is an audio fingerprinting library that implements a Shazam-like algorithm for identifying songs from audio… intro-skipper/intro-skipper — Intro Skipper is a media server plugin and automated playback utility designed to identify and bypass television… metabrainz/picard — MusicBrainz Picard is a metadata tagger and audio tag editor that identifies and tags audio files using the… aubio/aubio — Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides… librosa/librosa — Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature… sergree/matchering — Matchering is an audio mastering tool and Python library designed to match the frequency balance and loudness of a…