Spaces:
Running
Running
| from spleeter.separator import Separator | |
| import gradio as gr | |
| import shutil | |
| def spleeter(aud, instrument): | |
| separator = Separator('spleeter:2stems') | |
| try: | |
| shutil.rmtree("output") | |
| except FileNotFoundError: | |
| pass | |
| separator.separate_to_file(aud, "output/", filename_format="audio_example/{instrument}.wav") | |
| return f"./output/audio_example/{instrument}.wav", f"./output/audio_example/{instrument}.wav" | |
| inputs = [ | |
| gr.inputs.Audio(label="Input Audio File", type="filepath"), | |
| gr.inputs.Radio(label="Output", choices=["accompaniment", "vocals"], type="value") | |
| ] | |
| outputs = [ | |
| gr.outputs.Audio(label="Output Audio", type="filepath"), | |
| gr.outputs.File(label="Output File") | |
| ] | |
| title = "Music Spleeter" | |
| description = "Clearing a musical composition of the performer's voice is a common task. It is solved well, for example, by professional audio file editing programs. AI algorithms have also been gaining ground recently." | |
| article = "<div style='text-align: center; max-width:800px; margin:10px auto;'><p>In this case we use Deezer's Spleeter with ready pretrained models. It can leave as an output both just the music and just the performer's voice.</p><p>Sources: <a href='https://github.com/deezer/spleeter/' target='_blank'>Spleeter</a>: a Fast and Efficient Music Source Separation Tool with Pre-Trained Models</p><p style='text-align: center'><a href='https://starstat.yt/cat/music' target='_blank'>StarStat Music</a>: Youtubers Net Worth in category Music</p></div>" | |
| examples = [ | |
| ["audio_example.mp3", "vocals"] | |
| ] | |
| gr.Interface(spleeter, inputs, outputs, title=title, description=description, article=article, examples=examples).launch() |