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from __future__ import annotations |
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import gradio as gr |
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import numpy as np |
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from model import Model |
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DESCRIPTION = "# [AvantGAN](https://github.com/ellemcfarlane/AvantGAN)" |
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def get_sample_image_url(name: str) -> str: |
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sample_image_dir = "https://huggingface.co/spaces/ellemac/avantGAN/resolve/main/samples" |
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return f"{sample_image_dir}/{name}.png" |
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def get_sample_image_markdown(name: str) -> str: |
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url = get_sample_image_url(name) |
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size = 128 if ("stylegan3" in name or "original" in name) else 64 |
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return f""" |
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- size: {size}x{size} |
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""" |
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model = Model() |
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with gr.Blocks(css="style.css") as demo: |
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gr.Markdown(DESCRIPTION) |
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with gr.Tabs(): |
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with gr.TabItem("App"): |
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with gr.Row(): |
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with gr.Column(): |
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model_name = gr.Dropdown( |
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label="Model", choices=list(model.MODEL_DICT.keys()), value="stylegan3-abstract" |
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) |
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seed = gr.Slider(label="Seed", minimum=0, maximum=np.iinfo(np.uint32).max, step=1, value=0) |
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run_button = gr.Button() |
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with gr.Column(): |
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result = gr.Image(label="Result", elem_id="result", width=300, height=300) |
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with gr.TabItem("Sample Images"): |
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with gr.Row(): |
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model_name2 = gr.Dropdown( |
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[ |
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"stylegan3-abstract", |
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"stylegan3-high-fidelity", |
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"ada-dcgan", |
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"original-training-data", |
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], |
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value="stylegan3-abstract", |
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label="Model", |
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) |
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with gr.Row(): |
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text = get_sample_image_markdown(model_name2.value) |
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sample_images = gr.Markdown(text) |
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run_button.click( |
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fn=model.set_model_and_generate_image, |
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inputs=[ |
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model_name, |
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seed, |
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], |
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outputs=result, |
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api_name="run", |
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) |
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model_name2.change( |
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fn=get_sample_image_markdown, |
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inputs=model_name2, |
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outputs=sample_images, |
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queue=False, |
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api_name=False, |
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) |
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if __name__ == "__main__": |
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demo.queue(max_size=20).launch() |
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