#!/usr/bin/env python

from __future__ import annotations

import gradio as gr
import numpy as np

from model import Model

DESCRIPTION = "# [StyleSwin](https://github.com/microsoft/StyleSwin)"


def get_sample_image_url(name: str) -> str:
    sample_image_dir = "https://huggingface.co/spaces/hysts/StyleSwin/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 == "celeba-hq":
        size = 1024
    elif name == "ffhq":
        size = 1024
    elif name == "lsun-church":
        size = 256
    else:
        raise ValueError
    seed = "0-99"
    return f"""
    - size: {size}x{size}
    - seed: {seed}
    ![sample images]({url})"""


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(model.MODEL_NAMES, value=model.MODEL_NAMES[3], label="Model")
                    seed = gr.Slider(0, np.iinfo(np.uint32).max, step=1, value=0, label="Seed")
                    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(
                    [
                        "celeba-hq",
                        "ffhq",
                        "lsun-church",
                    ],
                    value="celeba-hq",
                    label="Model",
                )
            with gr.Row():
                text = get_sample_image_markdown(model_name2.value)
                sample_images = gr.Markdown(text)

    run_button.click(fn=model.set_model_and_generate_image, inputs=[model_name, seed], outputs=result, api_name="run")
    model_name2.change(fn=get_sample_image_markdown, inputs=model_name2, outputs=sample_images)

if __name__ == "__main__":
    demo.queue(max_size=15).launch()