AudioMuse-AI over Raspberry PI 5 8GB in number
Hi All,
this post is to show you AudioMuse-AI resources usage on a Raspberry Pi 5 8GB with NVME SSD hat, during the analysis. All the number are made over the last v2.4.0 release of today.
First of all for whom don't know AudioMuse-AI is a free and opensource software that enable to analyze the raw file of your song (sonic analysis) and based on this analysis it enable to create automatic playlist.
It work with Jellyfin, Navidrome (and other Open Subosnic API compatible music servee) Emby and Lyrion. Also made avaiable Jellyfin Plugin, Navidrome Plugin and I hope soon also an Music Assistant AudioMuse-AI provider plugin that will enable to command it with voice!
..and of course is all selfhostable and privacy first: your computer, your analysis, your data! no one can block you in future behind a paywall!
The reason for this post is that multiple user tought about it as something heavy, but it can work even on a Raspberry PI 5.
In the attached image you can show it during the most heavy part that is the analysis, and you can look how in avarage (k9s screenshot) it use half of the CPU/RAM resources and on the pike it still don't saturate them.
And speaking about resources, eare is the avarage analysis time per track on a Raspberry PI 5:
- Average analysis per track time: ~31 s
Breakdown (per track):
- Download: ~1 s
- MusiCNN analysis: ~9 s
- CLAP load + segment processing + unload: ~10 s
- Lyrics API lookup: ~7 s (NO ASR, off course depending from the API response time)
- Embedding: ~1 s
- ONNX session recycling: ~3 s
This to say that we don't just have it working, but it work also on low hand hardware. For more speed, no problem, you can run multiple worker in parallel during the analysis. Just wake up a worker on your desktop or your laptop!
And what about the idle resources? CPU in idle is not used, and about RAM we worked to balance the time to respond to a first API request and the memory usage, the number for a 188k+ library are:
- Flask RAM in idle: 1282mb => it load up to 3.5-4Gb, and then unload after 5 minutes idle
- Worker RAM in idle: 198mb
and the time for a call, still stay in the order of ms!
About the functionality you can ho on github and look around, you can also navigate some screenshot here:
- https://github.com/NeptuneHub/AudioMuse-AI/tree/main/screenshot/example
The one for which I'm more proud is the Lyrics search by song: it get in input a song and is able to search similar not only by their grove but also by their lyrics.
Hope you can enjoy all of this and maybe convince some new user that AudioMuse-AI is for everyone! and if you like it, please don't miss the chance to leave a ⭐on the github repo!