Update app.py
Browse files
app.py
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@@ -80,7 +80,7 @@ def predict(music_prompt, melody, duration, model):
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return file.name
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css="""
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#col-container {max-width:
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a {text-decoration-line: underline; font-weight: 600;}
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"""
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@@ -96,31 +96,32 @@ with gr.Blocks(css=css) as demo:
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for longer sequences, more control and no queue.</p>
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"""
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load_sound_btn.click(split_process, inputs=[uploaded_sound, chosen_track], outputs=[melody])
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submit.click(predict, inputs=[music_prompt, melody, duration, model], outputs=[output])
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return file.name
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css="""
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#col-container {max-width: 910px; margin-left: auto; margin-right: auto;}
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a {text-decoration-line: underline; font-weight: 600;}
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"""
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for longer sequences, more control and no queue.</p>
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"""
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)
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with gr.Row():
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with gr.Column():
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uploaded_sound = gr.Audio(type="numpy", label="Input", source="upload")
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chosen_track = gr.Radio(["vocals", "bass", "drums", "other", "all-in"], label="Track", info="Which track from your audio do you want to mashup ?", value="vocals")
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load_sound_btn = gr.Button('Load your sound')
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#split_vocals = gr.Audio(type="filepath", label="Vocals")
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#split_bass = gr.Audio(type="filepath", label="Bass")
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#split_drums = gr.Audio(type="filepath", label="Drums")
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#split_others = gr.Audio(type="filepath", label="Other")
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with gr.Column():
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with gr.Row():
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music_prompt = gr.Textbox(label="Musical Prompt", info="Describe what kind of music you wish for", interactive=True)
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melody = gr.Audio(source="upload", type="numpy", label="Track Condition (from previous step)", interactive=False)
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with gr.Row():
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model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
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with gr.Row():
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duration = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="Generated Music Duration", interactive=True)
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with gr.Row():
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submit = gr.Button("Submit")
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#with gr.Row():
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# topk = gr.Number(label="Top-k", value=250, interactive=True)
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# topp = gr.Number(label="Top-p", value=0, interactive=True)
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# temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
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# cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
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output = gr.Audio(label="Generated Music")
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load_sound_btn.click(split_process, inputs=[uploaded_sound, chosen_track], outputs=[melody])
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submit.click(predict, inputs=[music_prompt, melody, duration, model], outputs=[output])
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