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from pyharp import ModelCard, build_endpoint, save_and_return_filepath
from audiotools import AudioSignal
from audioldm import build_model, style_transfer
import gradio as gr
import soundfile as sf
audioldm = build_model(model_name="audioldm-m-full")
def process_fn(input_audio_path, prompt, seed, guidance_scale, num_inference_steps, num_candidates, audio_length_in_s, transfer_strength):
waveform = style_transfer(
audioldm,
prompt,
input_audio_path,
transfer_strength,
int(seed),
duration = audio_length_in_s,
guidance_scale = guidance_scale,
ddim_steps = int(num_inference_steps),
batchsize = int(num_candidates),
config=None,
)
waveform = waveform[:,None,:]
sf.write("./output.wav", waveform[0, 0], samplerate=16000)
#save_wave(waveform, "./", name="output.wav") #broken, always appends _0.wav
return "./output.wav"
card = ModelCard(
name='AudioLDM Variations',
description='AudioLDM Variation Generator, operates on region selected in track.',
author='Team Audio',
tags=['AudioLDM', 'Variations', 'audio-to-audio']
)
with gr.Blocks() as webapp:
# Define your Gradio interface
inputs = [
gr.Audio(
label="Audio Input",
type="filepath"
),
gr.Text(
label="Prompt",
interactive=True
),
gr.Slider(
label="seed",
minimum="0",
maximum="65535",
value="43534",
step="1"
),
gr.Slider(
minimum=0, maximum=10,
step=0.1, value=2.5,
label="Guidance Scale"
),
gr.Slider(
minimum=1, maximum=500,
step=1, value=200,
label="Inference Steps"
),
gr.Slider(
minimum=1, maximum=10,
step=1, value=1,
label="Candidates"
),
gr.Slider(
minimum=2.5, maximum=10.0,
step=2.5, value=5,
label="Duration"
),
gr.Slider(
minimum=0, maximum=1.0,
value=0.5,
label="Transfer Strength"
),
]
output = gr.Audio(label="Audio Output", type="filepath")
ctrls_data, ctrls_button, process_button, cancel_button = build_endpoint(inputs, output, process_fn, card)
# queue the webapp: https://www.gradio.app/guides/setting-up-a-demo-for-maximum-performance
#webapp.queue()
webapp.launch(share=True) |