This is incredibly cool. I tried a few songs and it was pretty accurate. Really useful.
newsomix9xl 21 minutes ago [-]
I got excited about an open source steamdeck...
thclpr 48 minutes ago [-]
I built StemDeck, a free and open source desktop application that separates songs into vocals, drums, bass, guitar, piano, and other stems.
It started as a small project for my kid, who was learning bass and drums. Finding suitable backing tracks was surprisingly inconvenient. Most tools required an account, uploaded the audio to a remote server, imposed usage limits, or required a subscription. I wanted something simple that could process music locally.
StemDeck now includes:
- Local six-stem separation using Demucs
- NVIDIA CUDA, Apple Silicon MPS, and CPU processing
- Native releases for Windows, macOS, and Linux
- Local file support for MP3, WAV, FLAC, M4A, MP4, OGG, and Opus
- YouTube and SoundCloud imports
- Direct search for YouTube songs, playlists, and SoundCloud tracks
- Search-result previews before processing
- Playlist imports and a persistent, reorderable job queue
- A browser-based multitrack mixer with volume, mute, solo, and VU meters
- Waveform navigation, zooming, and loop regions
- Playback-speed and pitch-transposition controls
- Automatic BPM, key, scale, LUFS, and peak analysis
- A generated click track that follows the song
- Custom mix, loop-region, individual-stem, ZIP, and video exports
- A persistent local library with folders and search
- A mobile-friendly interface accessible over the local network through a QR code
- Docker and Unraid support
- An in-app updater and nine interface languages
The backend uses Python, FastAPI, Demucs, FFmpeg, yt-dlp, librosa, and Web Audio. The desktop shell is built with Tauri. Processing happens on the user’s machine, and audio is never uploaded to a StemDeck service.
There are no accounts, advertisements, subscriptions, credits, quotas, or telemetry. StemDeck is licensed under Apache 2.0, and I intend to keep it free and open source.
It is still alpha software. Separation quality depends on the source material, CPU processing can be slow, and there are undoubtedly edge cases I have not encountered. Feedback, bug reports, architectural criticism, and contributions are all welcome.
Rendered at 02:12:21 GMT+0000 (Coordinated Universal Time) with Vercel.
StemDeck now includes:
- Local six-stem separation using Demucs - NVIDIA CUDA, Apple Silicon MPS, and CPU processing - Native releases for Windows, macOS, and Linux - Local file support for MP3, WAV, FLAC, M4A, MP4, OGG, and Opus - YouTube and SoundCloud imports - Direct search for YouTube songs, playlists, and SoundCloud tracks - Search-result previews before processing - Playlist imports and a persistent, reorderable job queue - A browser-based multitrack mixer with volume, mute, solo, and VU meters - Waveform navigation, zooming, and loop regions - Playback-speed and pitch-transposition controls - Automatic BPM, key, scale, LUFS, and peak analysis - A generated click track that follows the song - Custom mix, loop-region, individual-stem, ZIP, and video exports - A persistent local library with folders and search - A mobile-friendly interface accessible over the local network through a QR code - Docker and Unraid support - An in-app updater and nine interface languages
The backend uses Python, FastAPI, Demucs, FFmpeg, yt-dlp, librosa, and Web Audio. The desktop shell is built with Tauri. Processing happens on the user’s machine, and audio is never uploaded to a StemDeck service. There are no accounts, advertisements, subscriptions, credits, quotas, or telemetry. StemDeck is licensed under Apache 2.0, and I intend to keep it free and open source. It is still alpha software. Separation quality depends on the source material, CPU processing can be slow, and there are undoubtedly edge cases I have not encountered. Feedback, bug reports, architectural criticism, and contributions are all welcome.