Spaces:
Running
on
T4
Running
on
T4
added duration option
Browse files
app.py
CHANGED
@@ -11,8 +11,12 @@ model_id = "riffusion/riffusion-model-v1"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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def predict(prompt):
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print(spec)
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wav = wav_bytes_from_spectrogram_image(spec)
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with open("output.wav", "wb") as f:
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@@ -132,6 +136,7 @@ with gr.Blocks(css=css) as demo:
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gr.HTML(title)
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prompt_input = gr.Textbox(placeholder="a cat diva singing in a New York jazz club", label="Musical prompt", elem_id="prompt-in")
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send_btn = gr.Button(value="Get a new spectrogram ! ", elem_id="submit-btn")
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with gr.Column(elem_id="col-container-2"):
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@@ -146,7 +151,7 @@ with gr.Blocks(css=css) as demo:
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gr.HTML(article)
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send_btn.click(predict, inputs=[prompt_input], outputs=[spectrogram_output, sound_output, share_button, community_icon, loading_icon])
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share_button.click(None, [], [], _js=share_js)
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demo.queue(max_size=250).launch(debug=True)
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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def predict(prompt, duration):
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if duration == 5:
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width_duration=512
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else :
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width_duration = int(512 + ((duration-5) * 128))
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spec = pipe(prompt, height=512, width=width_duration).images[0]
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print(spec)
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wav = wav_bytes_from_spectrogram_image(spec)
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with open("output.wav", "wb") as f:
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gr.HTML(title)
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prompt_input = gr.Textbox(placeholder="a cat diva singing in a New York jazz club", label="Musical prompt", elem_id="prompt-in")
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duration_input = gr.Slider(label="Duration in seconds", minimum=5, maximum=20, step=1, value=8, elem_id="duration-slider")
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send_btn = gr.Button(value="Get a new spectrogram ! ", elem_id="submit-btn")
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with gr.Column(elem_id="col-container-2"):
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gr.HTML(article)
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send_btn.click(predict, inputs=[prompt_input, duration_input], outputs=[spectrogram_output, sound_output, share_button, community_icon, loading_icon])
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share_button.click(None, [], [], _js=share_js)
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demo.queue(max_size=250).launch(debug=True)
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