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from __future__ import annotations |
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import pathlib |
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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 = "# [Self-Distilled StyleGAN](https://github.com/self-distilled-stylegan/self-distilled-internet-photos)" |
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def get_sample_image_url(name: str) -> str: |
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sample_image_dir = "https://huggingface.co/spaces/hysts/Self-Distilled-StyleGAN/resolve/main/samples" |
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return f"{sample_image_dir}/{name}.jpg" |
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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 = name.split("_")[1] |
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truncation_type = "_".join(name.split("_")[2:]) |
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return f""" |
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- size: {size}x{size} |
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- seed: 0-99 |
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- truncation: 0.7 |
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- truncation type: {truncation_type} |
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""" |
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def get_cluster_center_image_url(model_name: str) -> str: |
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cluster_center_image_dir = ( |
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"https://huggingface.co/spaces/hysts/Self-Distilled-StyleGAN/resolve/main/cluster_center_images" |
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) |
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return f"{cluster_center_image_dir}/{model_name}.jpg" |
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def get_cluster_center_image_markdown(model_name: str) -> str: |
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url = get_cluster_center_image_url(model_name) |
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return f"" |
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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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with gr.Group(): |
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model_name = gr.Dropdown(label="Model", choices=model.MODEL_NAMES, value=model.MODEL_NAMES[0]) |
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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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psi = gr.Slider(label="Truncation psi", minimum=0, maximum=2, step=0.05, value=0.7) |
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truncation_type = gr.Dropdown( |
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label="Truncation Type", choices=model.TRUNCATION_TYPES, value=model.TRUNCATION_TYPES[0] |
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) |
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run_button = gr.Button("Run") |
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with gr.Column(): |
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result = gr.Image(label="Result", elem_id="result") |
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with gr.TabItem("Sample Images"): |
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with gr.Row(): |
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paths = sorted(pathlib.Path("samples").glob("*")) |
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names = [path.stem for path in paths] |
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model_name2 = gr.Dropdown(label="Type", choices=names, value="dogs_1024_multimodal_lpips") |
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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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with gr.TabItem("Cluster Center Images"): |
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with gr.Row(): |
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model_name3 = gr.Dropdown(label="Model", choices=model.MODEL_NAMES, value=model.MODEL_NAMES[0]) |
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with gr.Row(): |
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text = get_cluster_center_image_markdown(model_name3.value) |
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cluster_center_images = gr.Markdown(value=text) |
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model_name.change( |
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fn=model.set_model, |
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inputs=model_name, |
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) |
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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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psi, |
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truncation_type, |
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], |
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outputs=result, |
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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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) |
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model_name3.change( |
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fn=get_cluster_center_image_markdown, |
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inputs=model_name3, |
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outputs=cluster_center_images, |
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) |
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if __name__ == "__main__": |
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demo.queue(max_size=10).launch() |
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