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| #!/usr/bin/env python | |
| import gradio as gr | |
| from model import Model | |
| from settings import CACHE_EXAMPLES, MAX_SEED | |
| from utils import randomize_seed_fn | |
| def create_demo(model: Model) -> gr.Blocks: | |
| examples = [ | |
| 'A chair that looks like an avocado', | |
| 'An airplane that looks like a banana', | |
| 'A spaceship', | |
| 'A birthday cupcake', | |
| 'A chair that looks like a tree', | |
| 'A green boot', | |
| 'A penguin', | |
| 'Ube ice cream cone', | |
| 'A bowl of vegetables', | |
| ] | |
| def process_example_fn(prompt: str) -> str: | |
| return model.run_text(prompt, output_image_size=128) | |
| with gr.Blocks() as demo: | |
| with gr.Box(): | |
| with gr.Row(elem_id='prompt-container'): | |
| prompt = gr.Text( | |
| label='Prompt', | |
| show_label=False, | |
| max_lines=1, | |
| placeholder='Enter your prompt').style(container=False) | |
| run_button = gr.Button('Run').style(full_width=False) | |
| result = gr.Video(label='Result', elem_id='result-1') | |
| with gr.Accordion('Advanced options', open=False): | |
| seed = gr.Slider(label='Seed', | |
| minimum=0, | |
| maximum=MAX_SEED, | |
| step=1, | |
| value=0) | |
| randomize_seed = gr.Checkbox(label='Randomize seed', | |
| value=True) | |
| guidance_scale = gr.Slider(label='Guidance scale', | |
| minimum=1, | |
| maximum=20, | |
| step=0.1, | |
| value=15.0) | |
| num_inference_steps = gr.Slider( | |
| label='Number of inference steps', | |
| minimum=1, | |
| maximum=100, | |
| step=1, | |
| value=64) | |
| image_size = gr.Slider(label='Image size', | |
| minimum=64, | |
| maximum=256, | |
| step=64, | |
| value=128) | |
| render_mode = gr.Dropdown(label='Render mode', | |
| choices=['nerf', 'stf'], | |
| value='nerf', | |
| visible=False) | |
| gr.Examples(examples=examples, | |
| inputs=prompt, | |
| outputs=result, | |
| fn=process_example_fn, | |
| cache_examples=CACHE_EXAMPLES) | |
| inputs = [ | |
| prompt, | |
| seed, | |
| guidance_scale, | |
| num_inference_steps, | |
| image_size, | |
| render_mode, | |
| ] | |
| prompt.submit( | |
| fn=randomize_seed_fn, | |
| inputs=[seed, randomize_seed], | |
| outputs=seed, | |
| queue=False, | |
| ).then( | |
| fn=model.run_text, | |
| inputs=inputs, | |
| outputs=result, | |
| ) | |
| run_button.click( | |
| fn=randomize_seed_fn, | |
| inputs=[seed, randomize_seed], | |
| outputs=seed, | |
| queue=False, | |
| ).then( | |
| fn=model.run_text, | |
| inputs=inputs, | |
| outputs=result, | |
| ) | |
| return demo | |