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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import argparse | |
| import gradio as gr | |
| from model import Model | |
| TITLE = '# Anime Face Generation with [Diffusers](https://github.com/huggingface/diffusers)' | |
| DESCRIPTION = ''' | |
| Expected execution time on Hugging Face Spaces: 5s (DDIM, 20 steps), 6s (PNDM, 20 steps), 247s (DDPM, 1000 steps) | |
| ''' | |
| FOOTER = '<img id="visitor-badge" src="https://visitor-badge.glitch.me/badge?page_id=hysts.diffusers-anime-faces" alt="visitor badge" />' | |
| def get_sample_image_url(name: str) -> str: | |
| sample_image_dir = 'https://huggingface.co/spaces/hysts/diffusers-anime-faces/resolve/main/samples' | |
| return f'{sample_image_dir}/{name}.png' | |
| def get_sample_image_markdown(name: str) -> str: | |
| model_name = name.split()[0] | |
| url = get_sample_image_url(model_name) | |
| if name == 'ddpm-128-exp000 (DDPM)': | |
| text = f''' | |
| - size: 128x128 | |
| - seed: 0-99 | |
| - scheduler: DDPM | |
| ''' | |
| else: | |
| raise ValueError | |
| return text | |
| def update_scheduler_type(name: str) -> dict: | |
| visible = name != 'DDPM' | |
| if name == 'PNDM': | |
| minimum = 4 | |
| maximum = 100 | |
| else: | |
| minimum = 1 | |
| maximum = 200 | |
| return gr.Slider.update(visible=visible, | |
| minimum=minimum, | |
| maximum=maximum, | |
| value=20) | |
| def main(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--device', type=str, default='cpu') | |
| args = parser.parse_args() | |
| model = Model(args.device) | |
| with gr.Blocks(css='style.css') as demo: | |
| gr.Markdown(TITLE) | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Tabs(): | |
| with gr.TabItem('App'): | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Group(): | |
| model_name = gr.Dropdown( | |
| model.MODEL_NAMES, | |
| value=model.MODEL_NAMES[0], | |
| label='Model', | |
| interactive=False) | |
| scheduler_type = gr.Radio( | |
| choices=['DDPM', 'DDIM', 'PNDM'], | |
| value='DDIM', | |
| label='Scheduler') | |
| num_steps = gr.Slider(1, | |
| 200, | |
| step=1, | |
| value=20, | |
| label='Number of Steps') | |
| seed = gr.Slider(0, | |
| 100000, | |
| step=1, | |
| value=1234, | |
| label='Seed') | |
| run_button = gr.Button('Run') | |
| with gr.Column(): | |
| result = gr.Image(label='Result', elem_id='result') | |
| with gr.TabItem('Sample Images'): | |
| with gr.Row(): | |
| model_name2 = gr.Dropdown([ | |
| 'ddpm-128-exp000 (DDPM)', | |
| ], | |
| value='ddpm-128-exp000 (DDPM)', | |
| label='Model', | |
| interactive=False) | |
| with gr.Row(): | |
| text = get_sample_image_markdown(model_name2.value) | |
| sample_images = gr.Markdown(text) | |
| gr.Markdown(FOOTER) | |
| model_name.change(fn=model.set_pipeline, | |
| inputs=[ | |
| model_name, | |
| scheduler_type, | |
| ], | |
| outputs=None) | |
| scheduler_type.change(fn=update_scheduler_type, | |
| inputs=scheduler_type, | |
| outputs=num_steps, | |
| queue=False) | |
| scheduler_type.change(fn=model.set_pipeline, | |
| inputs=[ | |
| model_name, | |
| scheduler_type, | |
| ], | |
| outputs=None) | |
| run_button.click(fn=model.run, | |
| inputs=[ | |
| model_name, | |
| scheduler_type, | |
| num_steps, | |
| seed, | |
| ], | |
| outputs=result) | |
| model_name2.change(fn=get_sample_image_markdown, | |
| inputs=model_name2, | |
| outputs=sample_images) | |
| demo.launch(enable_queue=True, share=False) | |
| if __name__ == '__main__': | |
| main() | |