import gradio as gr
import numpy as np
# from audioldm import text_to_audio
def text2audio(text, length):
# waveform = text_to_audio(text, n_gen=1) # [bs, 1, samples]
# waveform = [(16000, wave[0]) for wave in waveform]
waveform = [(16000, np.random.randn(16000)), (16000, np.random.randn(16000))]
return waveform
# iface = gr.Interface(fn=greet, inputs="text", outputs=["audio", "audio"])
# iface.launch()
block = gr.Blocks()
with block:
gr.HTML(
"""
"""
)
with gr.Group():
with gr.Box():
textbox = gr.Textbox(value="A man is speaking in a huge room")
length = gr.Slider(1.0, 30.0, value=5.0, step=0.5, label="Audio length in seconds")
# model = gr.Dropdown(choices=["harmonai/maestro-150k"], value="harmonai/maestro-150k",type="value", label="Model")
out = [gr.Audio(label="Output", type="numpy"), gr.Audio(label="Output", type="numpy")]
btn = gr.Button("Submit").style(full_width=True)
btn.click(text2audio, inputs=[textbox, length], outputs=out)
gr.HTML('''
''')
block.launch(debug=True)