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Update app.py
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app.py
CHANGED
@@ -15,10 +15,7 @@ pipe = AudioLDMControlNetPipeline.from_pretrained("cvssp/audioldm-m-full", contr
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pipe = pipe.to(device)
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def predict(midi_file=None, prompt="", negative_prompt="", audio_length_in_s=5, controlnet_conditioning_scale=1, num_inference_steps=20, guess_mode=False):
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midi_file = midi_file.name
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else:
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midi_file = "test.mid"
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midi = PrettyMIDI(midi_file)
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audio = pipe(
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prompt,
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@@ -35,9 +32,9 @@ demo = gr.Interface(fn=predict, inputs=[
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gr.File(file_types=[".mid"]),
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"text",
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gr.Textbox(label="negative prompt"),
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gr.Slider(0, 30, value=
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gr.Slider(0.0, 1.0, value=1.0, step=0.1, label="conditioning scale"),
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gr.Slider(0, 50, value=20, step=0.1, label="inference steps"),
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gr.Checkbox(label="guess mode")
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], outputs="audio")
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demo.launch()
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pipe = pipe.to(device)
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def predict(midi_file=None, prompt="", negative_prompt="", audio_length_in_s=5, controlnet_conditioning_scale=1, num_inference_steps=20, guess_mode=False):
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midi_file = midi_file.name
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midi = PrettyMIDI(midi_file)
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audio = pipe(
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prompt,
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gr.File(file_types=[".mid"]),
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"text",
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gr.Textbox(label="negative prompt"),
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gr.Slider(0, 30, value=10, step=5, label="duration (seconds)"),
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gr.Slider(0.0, 1.0, value=1.0, step=0.1, label="conditioning scale"),
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gr.Slider(0, 50, value=20, step=0.1, label="inference steps"),
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gr.Checkbox(label="guess mode")
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], outputs="audio", examples=["test.mid", "piano"], cache_examples=True)
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demo.launch()
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