This is a mixer for "Don't Stop the Music" that uses the results of bliss analysis to find suitable tracks. For details about bliss itself please refer to its 'website.' ( https://lelele.io/bliss.html)
There are two parts to this mixer: - A Linux/macOS/Windows app to analyse your music, save results to an SQLite database, and upload results to LMS - An LMS plugin that contains pre-built mixer binaries for Linux(x86_64, arm, 64-bit arm), macOS (fat binary), and Windows The LMS plugin can be installed from my 'repo' (https://raw.githubusercontent.com/CDrummond/lms-plugins/master/repo.xml) Binaries for the analyser will be placed on the 'Github releases page.' (https://github.com/CDrummond/bliss-analyser/releases) This analyser requires ffmpeg to be installed for Linux and macOS (homebrew), but libraries are bundled with the Windows version. Contained within each ZIP is a README.md file with detailed usage steps. The current 0.0.1 ZIPs can be downloaded from: - 'Linux' (https://github.com/CDrummond/bliss-analyser/releases/download/0.0.1/bliss-analyser-linux-0.0.1.zip) - 'Mac' (https://github.com/CDrummond/bliss-analyser/releases/download/0.0.1/bliss-analyser-mac-0.0.1.zip) - 'Windows' (https://github.com/CDrummond/bliss-analyser/releases/download/0.0.1/bliss-analyser-windows-0.0.1.zip) As a quick guide: - Install the LMS plugin - Download the relevant ZIP of bliss-analyser - Install ffmpeg for Linux or macOS - Edit 'config.ini' in the bliss-analyser folder to contain the correct path to your music files, and the correct LMS hostname or IP address - Analyse your files with: bliss-analyser analyse - Once analysed, upload DB to LMS with: bliss-analyser upload - Choose 'Bliss' as DSTM mixer in LMS On a 2015-era i7 8 core laptop with SSD I can analyse almost 14000 tracks/hour. Obviously this will vary depending upon track lengths, etc, but gives a rough idea of how long the analysis stage will take. The analyser only stores relative paths in its database - hence you can analyse on one machine and run the mixer on another. e.g. If you music is stored in /home/user/Music, then /home/user/Music/Artist/Album/01-Track.mp3 is stored in the database as Artist/Album/01-Track.mp3 This mixer and analyser are Rust ports of the Bliss part of 'MusicSimilarity' (https://forums.slimdevices.com/showthread.php?115609-Announce-Music-Similarity-DSTM-mixer). I started that plugin to see if merging Essentia with Musly results would improve things, then discovered Bliss. For -my- music collection Bliss -appears- to create better mixes, and is much faster than Essentia. Hence this plugin. However, whilst MusicSimilarity supports CUE files (it splits them apart for analysis) bliss-analyser currently does not. I realised I only had 3 CUE albums, and it was easier to just split them into individual files. 'to-bliss.py' (https://raw.githubusercontent.com/CDrummond/music-similarity/master/scripts/to-bliss.py) can be used to convert a MusicSimilarity DB file (if it has bliss analysis) into a bliss.db - saving the need to re-analyse music if it has already been analysed with bliss. *Material debug:* 1. Launch via http: //SERVER:9000/material/?debug=json (Use http: //SERVER:9000/material/?debug=json,cometd to also see update messages, e.g. play queue) 2. Open browser's developer tools 3. Open console tab in developer tools 4. REQ/RESP messages sent to/from LMS will be logged here. ------------------------------------------------------------------------ cpd73's Profile: http://forums.slimdevices.com/member.php?userid=66686 View this thread: http://forums.slimdevices.com/showthread.php?t=116068 _______________________________________________ plugins mailing list plugins@lists.slimdevices.com http://lists.slimdevices.com/mailman/listinfo/plugins
