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import gradio as gr | |
from audiosr import super_resolution, build_model | |
def inference(audio_file, model_name, guidance_scale, ddim_steps): | |
audiosr = build_model(model_name=model_name) | |
waveform = super_resolution( | |
audiosr, | |
audio_file, | |
guidance_scale=guidance_scale, | |
ddim_steps=ddim_steps | |
) | |
return (44100, waveform) | |
iface = gr.Interface( | |
fn=inference, | |
inputs=[ | |
gr.Audio(type="filepath", label="Input Audio"), | |
gr.Dropdown(["basic", "speech"], value="basic", label="Model"), | |
gr.Slider(1, 10, value=3.5, step=0.1, label="Guidance Scale"), | |
gr.Slider(1, 100, value=50, step=1, label="DDIM Steps") | |
], | |
outputs=gr.Audio(type="numpy", label="Output Audio"), | |
title="AudioSR", | |
description="Audio Super Resolution with AudioSR" | |
) | |
iface.launch() |