Nithya commited on
Commit
9272247
·
1 Parent(s): 60db161

updated interface

Browse files
Files changed (1) hide show
  1. app.py +15 -14
app.py CHANGED
@@ -291,8 +291,8 @@ with gr.Blocks(css=css) as demo:
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  gr.Markdown("""
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  ## Instructions
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  In this demo you can interact with the model in two ways:
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- 1. **Call and response**: The model will try to continue the idea that you input. This is similar to 'primed generation' discussed in the paper. The last 4 s of the audio will be considered as a 'prime' for the model to continue. <br><br>
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- 2. **Melodic reinterpretation**: Akin to the idea of 'coarse pitch conditioning' presented in the paper, you can input a pitch contour and the model will generate audio that is similar to but not exactly the same. <br><br>
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  ### Upload an audio file or record your voice to get started!
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  """)
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  gr.Markdown("""
@@ -309,12 +309,22 @@ with gr.Blocks(css=css) as demo:
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  """)
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  model_dropdown = gr.Dropdown(["Diffusion Pitch Generator"], label="Select a model type")
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  task_dropdown = gr.Dropdown(label="Select a task", choices=["Call and Response", "Melodic Reinterpretation"])
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- sbmt = gr.Button()
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  with gr.Row(equal_height=True):
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  with gr.Column():
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  audio = gr.Audio(label="Input")
 
 
 
 
 
 
 
 
 
 
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  with gr.Column():
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- generated_audio = gr.Audio(label="Generated Audio")
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  with gr.Row():
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  with gr.Column():
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  with gr.Accordion("View Pitch Plot"):
@@ -322,16 +332,7 @@ with gr.Blocks(css=css) as demo:
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  with gr.Column():
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  with gr.Accordion("View Pitch Plot"):
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  generated_pitch = gr.Plot(label="Generated Pitch")
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- examples = gr.Examples(
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- examples=[
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- ["examples/ex1.wav"],
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- ["examples/ex2.wav"],
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- ["examples/ex3.wav"],
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- ["examples/ex4.wav"],
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- ["examples/ex5.wav"]
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- ],
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- inputs=audio
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- )
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  sbmt.click(container_generate, inputs=[model_dropdown, task_dropdown, audio], outputs=[generated_audio, user_input, generated_pitch])
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  def main(argv):
 
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  gr.Markdown("""
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  ## Instructions
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  In this demo you can interact with the model in two ways:
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+ 1. **[Call and response](https://snnithya.github.io/gamadhani-samples/5primed_generation/)**: The model will try to continue the idea that you input. This is similar to 'primed generation' discussed in the paper. The last 4 s of the audio will be considered as a 'prime' for the model to continue. <br><br>
295
+ 2. **[Melodic reinterpretation](https://snnithya.github.io/gamadhani-samples/6coarsepitch/)**: Akin to the idea of 'coarse pitch conditioning' presented in the paper, you can input a pitch contour and the model will generate audio that is similar to but not exactly the same. <br><br>
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  ### Upload an audio file or record your voice to get started!
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  """)
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  gr.Markdown("""
 
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  """)
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  model_dropdown = gr.Dropdown(["Diffusion Pitch Generator"], label="Select a model type")
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  task_dropdown = gr.Dropdown(label="Select a task", choices=["Call and Response", "Melodic Reinterpretation"])
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+
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  with gr.Row(equal_height=True):
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  with gr.Column():
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  audio = gr.Audio(label="Input")
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+ examples = gr.Examples(
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+ examples=[
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+ ["examples/ex1.wav"],
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+ ["examples/ex2.wav"],
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+ ["examples/ex3.wav"],
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+ ["examples/ex4.wav"],
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+ ["examples/ex5.wav"]
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+ ],
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+ inputs=audio
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+ )
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  with gr.Column():
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+ generated_audio = gr.Audio(label="Generated Audio", elem_id="audio")
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  with gr.Row():
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  with gr.Column():
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  with gr.Accordion("View Pitch Plot"):
 
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  with gr.Column():
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  with gr.Accordion("View Pitch Plot"):
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  generated_pitch = gr.Plot(label="Generated Pitch")
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+ sbmt = gr.Button()
 
 
 
 
 
 
 
 
 
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  sbmt.click(container_generate, inputs=[model_dropdown, task_dropdown, audio], outputs=[generated_audio, user_input, generated_pitch])
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  def main(argv):