metabrainz/picard
Picard
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 hierarchies through automated renaming and moving.
The system covers a broad range of capabilities, including community database lookups, CD metadata tagging through ripper log parsing, and the retrieval and embedding of album cover art. It also supports classical music hierarchies and provides tools for contributing acoustic fingerprints and release information back to the community database.
The application integrates Python for extending the tagging pipeline and provides a command-line interface for batch processing and custom configuration launches.
Features
- Music Metadata Integration - Retrieves accurate artist and album information from community databases to organize and update audio tags.
- Audio File Handling - Reads and writes metadata tags for common audio formats including MP3, FLAC, and WAV.
- Scripted File Transfers - Transfers music files to target directories based on automated naming and organization scripts.
- Album Clustering - Groups individual audio files into logical album units to facilitate batch metadata lookups and matching.
- Automated File Naming - MusicBrainz Picard defines specific naming conventions and tag formats using a scripting language.
- Metadata Transformation Scripts - MusicBrainz Picard applies user-defined scripts written in a custom language to transform metadata and file naming during tagging.
- Automated File Organizers - Automatically renames and moves music files into structured folder hierarchies based on metadata scripts.
- Metadata Tagging - Writes retrieved community metadata to audio files and optionally triggers renaming or moving.
- Audio Tagging - Uses format-specific libraries to read and write metadata tags across diverse audio containers.
- Acoustic Fingerprinting Systems - Implements sonic fingerprinting to identify unknown audio files by matching them against a community database.
- Crowdsourced Metadata Databases - Queries a community-curated music database using lookup keys to retrieve accurate album and track metadata.
- Automation Scripting Engines - Provides a custom scripting engine for automating metadata transformations and file renaming.
- Tag-Based File Renamers - Renames music files automatically using embedded metadata tags according to configurable scripts.
- Audio Metadata Editors - Reads and writes metadata tags across various audio formats including MP3, FLAC, and WAV.
- Audio Fingerprinting - Identifies unknown music files by generating sonic fingerprints and matching them against a recording database.
- Metadata Tagging - Identifies and tags audio files using the MusicBrainz community music database.
- Metadata Automators - MusicBrainz Picard modifies music metadata automatically upon loading data from external databases.
- Music Metadata Retrieval - Searches metadata databases for albums matching selected files to retrieve and display track listings.
- Extensible Plugin Architectures - Implements a framework that allows plugins to hook into the tagging pipeline for new metadata and automation.
- Format Abstraction Interfaces - Provides a unified abstraction layer for reading and writing tags across multiple audio formats.
- Tagging Pipeline Extensions - Extends the metadata pipeline with custom scripts and community plugins to support new formats and automation.
- Third-Party Plugins - Provides a plugin architecture that allows third-party extensions to add new metadata sources and audio format support.
- Hook-Based Plugin Systems - Loads plugins into specific lifecycle hooks to modify metadata and integrate new cover art sources.
- Metadata-Based Clustering - Groups unprocessed audio files into clusters based on metadata to facilitate batch lookup and tagging.
- CD Table of Contents Matching - Matches ripped audio files to specific album releases using CD table of contents and database lookups.
- Fingerprint Submissions - Allows users to contribute generated acoustic fingerprints to community databases to improve music identification.
- Collaborative Database Contributions - Submits disc IDs and acoustic fingerprints to community databases for collaborative improvement.
- Python Plugin Integrations - Integrates Python scripts to allow for flexible metadata modification and support for new audio formats.
- Metadata Pre-population - Pre-populates artist, track, and timing data to simplify adding new recordings to the global database.
- Release Submissions - Enables sending groups of audio files as new release entries to a community music database.
- Physical Media Metadata Retrieval - Loads track data from physical CDs and applies matching metadata from a community database.
- Scripting Context Providers - MusicBrainz Picard provides access to system data like dates and track counts for use in script logic.
- Variable Interpolators - MusicBrainz Picard inserts metadata values into tags and file names using percent-wrapped variables.
- Batch Processing - Processes batches of audio files by forwarding paths to a running application instance.
- Audio Track Previews - MusicBrainz Picard provides an integrated player to preview audio tracks before or after tagging.
- Cover Art Embedding - Inserts cover art images from online sources directly into audio files.
- Media Album Organization - Groups individual audio files into logical albums and propagates shared metadata across all tracks.
- Album Art Retrievals - Finds and attaches album cover art from online sources to music files.
- Multi-Value Metadata Processing - MusicBrainz Picard joins, slices, and deduplicates multi-value tags using dedicated processing functions.
- Automatic Track Identification - Links individual audio files to exact tracks on a specific release for precise metadata tagging.
- Disc ID Matching - Links a physical CD disc ID to a corresponding release in a community database.
- Log Parsing - Parses CD ripper log files to extract the table of contents for accurate database lookups.
- Custom Scripting Functions - MusicBrainz Picard introduces new functions for use within naming and metadata engines.
- Plugin-Based Architectures - Features a plugin-based architecture that allows extending the tagging pipeline with new metadata sources.
- Data Difference Views - MusicBrainz Picard provides a side-by-side view of original and proposed tag values before writing to files.
- Audio and Video - Automated music tagging and metadata tool.
- Audio Tools - Tool to automatically identify, tag, and organize music.
- Audio Utilities - Identifies and tags music files.
- Audio Video Tools - Listed in the “Audio Video Tools” section of the Awesome Mac awesome list.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
