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9781a06
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1 Parent(s): 8778797

Update app.py

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Files changed (1) hide show
  1. app.py +9 -18
app.py CHANGED
@@ -353,10 +353,10 @@ class AudioUpscaler:
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  print(f"File created: {output_file}")
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  # Cleanup
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- del waveform
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  gc.collect()
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  torch.cuda.empty_cache()
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- return output_file
 
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@@ -386,7 +386,7 @@ def inference(audio_file, model_name, guidance_scale, ddim_steps, seed):
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  return (48000, waveform)
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-
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  def upscale_audio(
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  input_file,
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  output_folder,
@@ -415,10 +415,13 @@ def upscale_audio(
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  Returns:
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  tuple: Upscaled audio data and sample rate.
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  """
 
 
 
 
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  upscaler = AudioUpscaler()
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  upscaler.setup()
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-
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- output_file = upscaler.predict(
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  input_file,
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  output_folder,
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  ddim_steps=ddim_steps,
@@ -435,7 +438,7 @@ def upscale_audio(
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  gc.collect()
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- return output_file
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  os.getcwd()
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  gr.Textbox
@@ -453,18 +456,6 @@ iface = gr.Interface(
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  gr.Checkbox(label="Multiband Ensemble", value=False, info="Enhance high frequencies"),
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  gr.Slider(500, 15000, value=9000, step=500, label="Crossover Frequency (Hz)", info="For multiband processing", visible=True)
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  ],
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-
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-
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-
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- iface = gr.Interface(
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- fn=inference,
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- inputs=[
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- gr.Audio(type="filepath", label="Input Audio"),
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- gr.Dropdown(["basic", "speech"], value="basic", label="Model"),
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- gr.Slider(1, 10, value=3.5, step=0.1, label="Guidance Scale", info="Guidance scale (Large => better quality and relavancy to text; Small => better diversity)"),
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- gr.Slider(1, 100, value=50, step=1, label="DDIM Steps", info="The sampling step for DDIM"),
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- gr.Number(value=42, precision=0, label="Seed", info="Changing this value (any integer number) will lead to a different generation result, put 0 for a random one.")
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- ],
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  outputs=gr.Audio(type="numpy", label="Output Audio"),
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  title="AudioSR",
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  description="Audio Super Resolution with AudioSR"
 
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  print(f"File created: {output_file}")
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  # Cleanup
 
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  gc.collect()
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  torch.cuda.empty_cache()
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+ return waveform
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+ # return output_file
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  return (48000, waveform)
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+ @spaces.GPU
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  def upscale_audio(
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  input_file,
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  output_folder,
 
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  Returns:
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  tuple: Upscaled audio data and sample rate.
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  """
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+ if torch.cuda.is_avaible():
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+ torch.cuda.empty_cache()
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+
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+ gc.collect()
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  upscaler = AudioUpscaler()
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  upscaler.setup()
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+ waveform = upscaler.predict(
 
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  input_file,
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  output_folder,
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  ddim_steps=ddim_steps,
 
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  gc.collect()
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+ return waveform
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  os.getcwd()
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  gr.Textbox
 
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  gr.Checkbox(label="Multiband Ensemble", value=False, info="Enhance high frequencies"),
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  gr.Slider(500, 15000, value=9000, step=500, label="Crossover Frequency (Hz)", info="For multiband processing", visible=True)
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  ],
 
 
 
 
 
 
 
 
 
 
 
 
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  outputs=gr.Audio(type="numpy", label="Output Audio"),
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  title="AudioSR",
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  description="Audio Super Resolution with AudioSR"