◐ModelAudio & SpeechFree
Demucs
Meta AI's music source separation model that splits any song into vocals, drums, bass, and other stems.
インストール数92k
評価★ 4.8
レビュー31
Demucs
Demucs is Meta AI Research's music source separation model. It can split any music track into four stems — vocals, drums, bass, and other instruments — with state-of-the-art quality. Hybrid Demucs v4 combines waveform and spectrogram modelling for best-in-class performance on the SDR benchmark.
Key Features
- Four-stem separation (vocals, drums, bass, other) and six-stem variant
- Hybrid Demucs v4 sets the state of the art on the MusDB18-HQ benchmark
- Fine-grained model variants: htdemucs (default), htdemucs_ft, mdx, mdx_extra
- CLI for one-command separation; Python API for programmatic use
- Karaoke mode (exclude vocals) and guitar/piano two-stem separation
Quick Start
pip install demucs
demucs --mp3 mysong.mp3 # outputs to separated/htdemucs/
from demucs.apply import apply_model
from demucs.pretrained import get_model
from demucs.audio import AudioFile, save_audio
model = get_model("htdemucs")
audio = AudioFile("song.wav").read(streams=0, samplerate=model.samplerate, channels=model.audio_channels)
sources = apply_model(model, audio[None])
# sources shape: [batch, stems, channels, time]
npx ai-supply add demucs-music-source-separation
Curated mirror of the open-source Demucs (MIT). Get it from the source.