This is a simplified demonstration of the AcoustID algorithm, packaged as a Django app.
It computes fingerprints on a music collection, identifies similar tracks, and can optionally look up track artist and title via AcoustID.
- A PostgreSQL database with the AcoustID Postgres Extension,
- The Chromaprint
fpcalc
program. You can download it from acoustid.org. - A working Django site running on Postgres.
To look up fingerprints against the MusicBrainz database, an API key is needed in the ACOUSTID_API_KEY
environment variable.
See here for instructions.
Add fingerprints
to INSTALLED_APPS
in the Django settings. Then run ./manage.py scan path/to/your/music/collection
to add tracks. fpcalc
is expected in the system PATH
. Because fingerprinting might take a while for a large music collection, scan
uses all available CPUs in parallel.
When completed, head to the Django admin site. Your music is visible under fingerprints
, duplicates are already marked. Use the Identify with MusicBrainz
action in the track list to look up artists and titles of unknown tracks. If successful, tracks are marked as Identified
and the JSON data is shown in the fingerprint details.
Kudos to Lukáš Lalinský, the author of the excellent AcoustID software.