#!/usr/bin/env python

from __future__ import annotations

import gradio as gr
import numpy as np

from model import Model

DESCRIPTION = "# [Projected GAN](https://github.com/autonomousvision/projected_gan)"


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


def get_sample_image_markdown(name: str) -> str:
    url = get_sample_image_url(name)
    return f"""
    - size: 256x256
    - seed: 0-99
    - truncation: 0.7
    ![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(label="Model", choices=model.MODEL_NAMES, value=model.MODEL_NAMES[8])
                    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)
                    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=model.MODEL_NAMES, value=model.MODEL_NAMES[0])
            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,
            psi,
        ],
        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()