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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import argparse | |
| import gradio as gr | |
| import numpy as np | |
| from model import Model | |
| TITLE = '# Self-Distilled StyleGAN' | |
| DESCRIPTION = '''This is an unofficial demo for [https://github.com/self-distilled-stylegan/self-distilled-internet-photos](https://github.com/self-distilled-stylegan/self-distilled-internet-photos). | |
| Expected execution time on Hugging Face Spaces: 2s''' | |
| FOOTER = '<img id="visitor-badge" src="https://visitor-badge.glitch.me/badge?page_id=hysts.self-distilled-stylegan" alt="visitor badge" />' | |
| def parse_args() -> argparse.Namespace: | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--device', type=str, default='cpu') | |
| parser.add_argument('--theme', type=str) | |
| parser.add_argument('--share', action='store_true') | |
| parser.add_argument('--port', type=int) | |
| parser.add_argument('--disable-queue', | |
| dest='enable_queue', | |
| action='store_false') | |
| return parser.parse_args() | |
| def get_sample_image_url(model_name: str) -> str: | |
| sample_image_dir = 'https://huggingface.co/spaces/hysts/Self-Distilled-StyleGAN/resolve/main/samples' | |
| return f'{sample_image_dir}/{model_name}.jpg' | |
| def get_sample_image_markdown(model_name: str) -> str: | |
| url = get_sample_image_url(model_name) | |
| size = model_name.split('_')[-1] | |
| return f''' | |
| - size: {size}x{size} | |
| - seed: 0-99 | |
| - truncation: 0.7 | |
| ''' | |
| def get_cluster_center_image_url(model_name: str) -> str: | |
| cluster_center_image_dir = 'https://huggingface.co/spaces/hysts/Self-Distilled-StyleGAN/resolve/main/cluster_center_images' | |
| return f'{cluster_center_image_dir}/{model_name}.jpg' | |
| def get_cluster_center_image_markdown(model_name: str) -> str: | |
| url = get_cluster_center_image_url(model_name) | |
| return f'' | |
| def main(): | |
| args = parse_args() | |
| model = Model(args.device) | |
| with gr.Blocks(theme=args.theme, 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') | |
| seed = gr.Slider(0, | |
| np.iinfo(np.uint32).max, | |
| value=0, | |
| step=1, | |
| label='Seed') | |
| psi = gr.Slider(0, | |
| 2, | |
| step=0.05, | |
| value=0.7, | |
| label='Truncation psi') | |
| multimodal_truncation = gr.Checkbox( | |
| label='Multi-modal Truncation', value=True) | |
| 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(model.MODEL_NAMES, | |
| value=model.MODEL_NAMES[0], | |
| label='Model') | |
| with gr.Row(): | |
| text = get_sample_image_markdown(model_name2.value) | |
| sample_images = gr.Markdown(text) | |
| with gr.TabItem('Cluster Center Images'): | |
| with gr.Row(): | |
| model_name3 = gr.Dropdown(model.MODEL_NAMES, | |
| value=model.MODEL_NAMES[0], | |
| label='Model') | |
| with gr.Row(): | |
| text = get_cluster_center_image_markdown(model_name3.value) | |
| cluster_center_images = gr.Markdown(value=text) | |
| gr.Markdown(FOOTER) | |
| model_name.change(fn=model.set_model, inputs=model_name, outputs=None) | |
| run_button.click(fn=model.set_model_and_generate_image, | |
| inputs=[ | |
| model_name, | |
| seed, | |
| psi, | |
| multimodal_truncation, | |
| ], | |
| outputs=result) | |
| model_name2.change(fn=get_sample_image_markdown, | |
| inputs=model_name2, | |
| outputs=sample_images) | |
| model_name3.change(fn=get_cluster_center_image_markdown, | |
| inputs=model_name3, | |
| outputs=cluster_center_images) | |
| demo.launch( | |
| enable_queue=args.enable_queue, | |
| server_port=args.port, | |
| share=args.share, | |
| ) | |
| if __name__ == '__main__': | |
| main() | |