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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import pathlib | |
| import gradio as gr | |
| import numpy as np | |
| from model import Model | |
| DESCRIPTION = '# [Self-Distilled StyleGAN](https://github.com/self-distilled-stylegan/self-distilled-internet-photos)' | |
| def get_sample_image_url(name: str) -> str: | |
| sample_image_dir = 'https://huggingface.co/spaces/hysts/Self-Distilled-StyleGAN/resolve/main/samples' | |
| return f'{sample_image_dir}/{name}.jpg' | |
| def get_sample_image_markdown(name: str) -> str: | |
| url = get_sample_image_url(name) | |
| size = name.split('_')[1] | |
| truncation_type = '_'.join(name.split('_')[2:]) | |
| return f''' | |
| - size: {size}x{size} | |
| - seed: 0-99 | |
| - truncation: 0.7 | |
| - truncation type: {truncation_type} | |
| ''' | |
| 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'' | |
| model = Model() | |
| with gr.Blocks(css='style.css') as demo: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Tabs(): | |
| with gr.TabItem('App'): | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Group(): | |
| model_name = gr.Dropdown(label='Model', | |
| choices=model.MODEL_NAMES, | |
| value=model.MODEL_NAMES[0]) | |
| seed = gr.Slider(label='Seed', | |
| minimum=0, | |
| maximum=np.iinfo(np.uint32).max, | |
| step=1, | |
| value=0) | |
| psi = gr.Slider(label='Truncation psi', | |
| minimum=0, | |
| maximum=2, | |
| step=0.05, | |
| value=0.7) | |
| truncation_type = gr.Dropdown( | |
| label='Truncation Type', | |
| choices=model.TRUNCATION_TYPES, | |
| value=model.TRUNCATION_TYPES[0]) | |
| run_button = gr.Button('Run') | |
| with gr.Column(): | |
| result = gr.Image(label='Result', elem_id='result') | |
| with gr.TabItem('Sample Images'): | |
| with gr.Row(): | |
| paths = sorted(pathlib.Path('samples').glob('*')) | |
| names = [path.stem for path in paths] | |
| model_name2 = gr.Dropdown(label='Type', | |
| choices=names, | |
| value='dogs_1024_multimodal_lpips') | |
| 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(label='Model', | |
| choices=model.MODEL_NAMES, | |
| value=model.MODEL_NAMES[0]) | |
| with gr.Row(): | |
| text = get_cluster_center_image_markdown(model_name3.value) | |
| cluster_center_images = gr.Markdown(value=text) | |
| model_name.change(fn=model.set_model, inputs=model_name) | |
| run_button.click(fn=model.set_model_and_generate_image, | |
| inputs=[ | |
| model_name, | |
| seed, | |
| psi, | |
| truncation_type, | |
| ], | |
| 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.queue(max_size=10).launch() | |