app.py

#!/usr/bin/env python

from __future__ import annotations

import json

import gradio as gr
import numpy as np

from model import Model

DESCRIPTION = "# [StyleGAN2](https://github.com/NVlabs/stylegan3)"


def update_class_index(name: str) -> dict:
    if name == "CIFAR-10":
        return gr.Slider(maximum=9, visible=True)
    else:
        return gr.Slider(visible=False)


def get_sample_image_url(name: str) -> str:
    sample_image_dir = "https://huggingface.co/spaces/hysts/StyleGAN2/resolve/main/samples"
    return f"{sample_image_dir}/{name}.jpg"


def get_sample_image_markdown(name: str) -> str:
    url = get_sample_image_url(name)
    if name == "cifar10":
        size = 32
        class_index = "0-9"
        seed = "0-9"
    else:
        class_index = "N/A"
        seed = "0-99"
        if name == "afhq-cat":
            size = 512
        elif name == "afhq-dog":
            size = 512
        elif name == "afhq-wild":
            size = 512
        elif name == "afhqv2":
            size = 512
        elif name == "brecahad":
            size = 256
        elif name == "celebahq":
            size = 1024
        elif name == "ffhq":
            size = 1024
        elif name == "ffhq-u":
            size = 1024
        elif name == "lsun-dog":
            size = 256
        elif name == "metfaces":
            size = 1024
        elif name == "metfaces-u":
            size = 1024
        else:
            raise ValueError

    return f"""
    - size: {size}x{size}
    - class_index: {class_index}
    - seed: {seed}
    - truncation: 0.7
    ![sample images]({url})"""


def load_class_names(name: str) -> list[str]:
    with open(f"labels/{name}_classes.json") as f:
        names = json.load(f)
    return names


def get_class_name_df(name: str) -> list:
    names = load_class_names(name)
    return list(map(list, enumerate(names)))  # type: ignore


CIFAR10_NAMES = load_class_names("cifar10")


def update_class_name(model_name: str, index: int) -> dict:
    if model_name == "CIFAR-10":
        value = CIFAR10_NAMES[index]
        return gr.Textbox(value=value, visible=True)
    else:
        return gr.Textbox(visible=False)


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():
                    model_name = gr.Dropdown(
                        label="Model", choices=list(model.MODEL_NAME_DICT.keys()), value="FFHQ-1024"
                    )
                    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)
                    class_index = gr.Slider(label="Class Index", minimum=0, maximum=9, step=1, value=0, visible=False)
                    class_name = gr.Textbox(
                        label="Class Label", value=CIFAR10_NAMES[class_index.value], interactive=False, visible=False
                    )
                    run_button = gr.Button()
                with gr.Column():
                    result = gr.Image(label="Result")

        with gr.TabItem("Sample Images"):
            with gr.Row():
                model_name2 = gr.Dropdown(
                    label="Model",
                    choices=[
                        "afhq-cat",
                        "afhq-dog",
                        "afhq-wild",
                        "afhqv2",
                        "brecahad",
                        "celebahq",
                        "cifar10",
                        "ffhq",
                        "ffhq-u",
                        "lsun-dog",
                        "metfaces",
                        "metfaces-u",
                    ],
                    value="afhq-cat",
                )
            with gr.Row():
                text = get_sample_image_markdown(model_name2.value)
                sample_images = gr.Markdown(text)

    model_name.change(
        fn=update_class_index,
        inputs=model_name,
        outputs=class_index,
        queue=False,
        api_name=False,
    )
    model_name.change(
        fn=update_class_name,
        inputs=[
            model_name,
            class_index,
        ],
        outputs=class_name,
        queue=False,
        api_name=False,
    )
    class_index.change(
        fn=update_class_name,
        inputs=[
            model_name,
            class_index,
        ],
        outputs=class_name,
        queue=False,
        api_name=False,
    )
    run_button.click(
        fn=model.set_model_and_generate_image,
        inputs=[
            model_name,
            seed,
            psi,
            class_index,
        ],
        outputs=result,
        api_name="run",
    )
    model_name2.change(
        fn=get_sample_image_markdown,
        inputs=model_name2,
        outputs=sample_images,
        queue=False,
        api_name=False,
    )

if __name__ == "__main__":
    demo.queue(max_size=10).launch()