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import os | |
import gradio as gr | |
from scipy.io.wavfile import write | |
def inference(audio): | |
os.makedirs("out", exist_ok=True) | |
write('test.wav', audio[0], audio[1]) | |
os.system("python3 -m demucs.separate -n htdemucs --two-stems=vocals -d cpu test.wav -o out") | |
return "./out/htdemucs/test/vocals.wav","./out/htdemucs/test/no_vocals.wav" | |
title = "Demucs Music Source Separation (v4)" | |
description = "This is the latest 'bleeding edge version' which enables the new v4 Hybrid Transformer model. <br> for this space, 2 stem sepration (Karaoke Mode) is enabled and CPU mode which has been optimised for best quality & processing time. <p>| Gradio demo for Demucs(v4): Music Source Separation in the Waveform Domain. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below.</p>" | |
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1911.13254' target='_blank'>Music Source Separation in the Waveform Domain</a> | <a href='https://github.com/facebookresearch/demucs' target='_blank'>Github Repo</a> | <a href='https://www.thafx.com' target='_blank'>//THAFX</a></p>" | |
examples=[['test.mp3']] | |
gr.Interface( | |
inference, | |
gr.Audio(type="numpy", label="Input"), | |
[gr.Audio(type="filepath", label="Vocals"),gr.Audio(type="filepath", label="No Vocals / Instrumental")], | |
title=title, | |
description=description, | |
article=article, | |
examples=examples | |
).launch(enable_queue=True) |