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Running
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Running
on
Zero
Fabrice-TIERCELIN
commited on
Commit
•
675b308
1
Parent(s):
20c103d
Format choice
Browse filesAllow the user to choose between wav or mp3
app.py
CHANGED
@@ -7,6 +7,7 @@ from huggingface_hub import snapshot_download
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from models import AudioDiffusion, DDPMScheduler
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from audioldm.audio.stft import TacotronSTFT
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from audioldm.variational_autoencoder import AutoencoderKL
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from gradio import Markdown
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import spaces
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@@ -83,12 +84,16 @@ tango.stft.to(device_type)
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tango.model.to(device_type)
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@spaces.GPU(duration=60)
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def gradio_generate(prompt, steps, guidance):
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output_wave = tango.generate(prompt, steps, guidance)
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# output_filename = f"{prompt.replace(' ', '_')}_{steps}_{guidance}"[:250] + ".wav"
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output_filename = "temp.wav"
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wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)
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return output_filename
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# description_text = """
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@@ -118,6 +123,7 @@ Generate audio using Tango2 by providing a text prompt. Tango2 was built from Ta
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"""
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# Gradio input and output components
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input_text = gr.Textbox(lines=2, label="Prompt")
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output_audio = gr.Audio(label="Generated Audio", type="filepath")
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denoising_steps = gr.Slider(minimum=100, maximum=200, value=100, step=1, label="Steps", interactive=True)
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guidance_scale = gr.Slider(minimum=1, maximum=10, value=3, step=0.1, label="Guidance Scale", interactive=True)
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@@ -125,7 +131,7 @@ guidance_scale = gr.Slider(minimum=1, maximum=10, value=3, step=0.1, label="Guid
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# Gradio interface
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gr_interface = gr.Interface(
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fn=gradio_generate,
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inputs=[input_text, denoising_steps, guidance_scale],
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outputs=[output_audio],
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title="Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimization",
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description=description_text,
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from models import AudioDiffusion, DDPMScheduler
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from audioldm.audio.stft import TacotronSTFT
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from audioldm.variational_autoencoder import AutoencoderKL
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from pydub import AudioSegment
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from gradio import Markdown
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import spaces
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tango.model.to(device_type)
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@spaces.GPU(duration=60)
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def gradio_generate(prompt, output_format, steps, guidance):
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output_wave = tango.generate(prompt, steps, guidance)
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# output_filename = f"{prompt.replace(' ', '_')}_{steps}_{guidance}"[:250] + ".wav"
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output_filename = "temp.wav"
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wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)
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if (output_format == "mp3"):
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AudioSegment.from_wav("temp.wav").export("temp.mp3", format = "mp3")
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output_filename = "temp.mp3"
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return output_filename
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# description_text = """
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"""
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# Gradio input and output components
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input_text = gr.Textbox(lines=2, label="Prompt")
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output_format = gr.Radio(label = "Output format", info = "The file you can dowload", choices = ["mp3", "wav"], value = "wav")
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output_audio = gr.Audio(label="Generated Audio", type="filepath")
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denoising_steps = gr.Slider(minimum=100, maximum=200, value=100, step=1, label="Steps", interactive=True)
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guidance_scale = gr.Slider(minimum=1, maximum=10, value=3, step=0.1, label="Guidance Scale", interactive=True)
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# Gradio interface
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gr_interface = gr.Interface(
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fn=gradio_generate,
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inputs=[input_text, output_format, denoising_steps, guidance_scale],
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outputs=[output_audio],
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title="Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimization",
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description=description_text,
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