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import gradio as gr |
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from model import Model |
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from settings import CACHE_EXAMPLES, MAX_SEED |
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from utils import randomize_seed_fn |
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def create_demo(model: Model) -> gr.Blocks: |
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with gr.Blocks() as demo: |
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with gr.Box(): |
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with gr.Row(elem_id='prompt-container'): |
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image_init = gr.Image(type="filepath", source="upload") |
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prompt = gr.Text( |
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label='Prompt', |
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show_label=False, |
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max_lines=1, |
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placeholder='Enter your prompt', |
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visible=False).style(container=False) |
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run_button = gr.Button('Run').style(full_width=False) |
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caption = gr.Textbox(label="Caption from CoCa") |
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result = gr.Model3D(label='Result', show_label=False) |
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with gr.Accordion('Advanced options', open=False): |
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seed = gr.Slider(label='Seed', |
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minimum=0, |
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maximum=MAX_SEED, |
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step=1, |
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value=0) |
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randomize_seed = gr.Checkbox(label='Randomize seed', |
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value=True) |
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guidance_scale = gr.Slider(label='Guidance scale', |
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minimum=1, |
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maximum=20, |
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step=0.1, |
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value=15.0) |
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num_inference_steps = gr.Slider( |
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label='Number of inference steps', |
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minimum=1, |
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maximum=100, |
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step=1, |
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value=64) |
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inputs = [ |
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image_init, |
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seed, |
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guidance_scale, |
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num_inference_steps, |
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] |
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run_button.click( |
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fn=randomize_seed_fn, |
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inputs=[seed, randomize_seed], |
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outputs=seed, |
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queue=False, |
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).then( |
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fn=model.run_text, |
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inputs=inputs, |
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outputs=[caption, result], |
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api_name='text-to-3d', |
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) |
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return demo |
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