#!/usr/bin/env python

from __future__ import annotations

import pathlib

import gradio as gr

from model import Model

DESCRIPTION = """# ĐÂY LÀ ỨNG DỤNG ĐANG THỬ NGHIỆM CỦA TDNM
"""


def load_hairstyle_list() -> list[str]:
    with open("HairCLIP/mapper/hairstyle_list.txt") as f:
        lines = [line.strip() for line in f.readlines()]
        lines = [line[:-10] for line in lines]
    return lines


def set_example_image(example: list) -> dict:
    return gr.Image(value=example[0])


def update_step2_components(choice: str) -> tuple[dict, dict]:
    return (
        gr.Dropdown(visible=choice in ["hairstyle", "both"]),
        gr.Textbox(visible=choice in ["color", "both"]),
    )


model = Model()

with gr.Blocks(css="style.css") as demo:
    gr.Markdown(DESCRIPTION)
    with gr.Group():
        gr.Markdown("## Bước 1")
        with gr.Row():
            with gr.Column():
                with gr.Row():
                    input_image = gr.Image(label="Input Image", type="filepath")
                with gr.Row():
                    preprocess_button = gr.Button("Preprocess")
            with gr.Column():
                aligned_face = gr.Image(label="Aligned Face", type="pil", interactive=False)
            with gr.Column():
                reconstructed_face = gr.Image(label="Reconstructed Face", type="numpy")
                latent = gr.State()

        with gr.Row():
            paths = sorted(pathlib.Path("images").glob("*.jpg"))
            gr.Examples(examples=[[path.as_posix()] for path in paths], inputs=input_image)

    with gr.Group():
        gr.Markdown("## Step 2")
        with gr.Row():
            with gr.Column():
                with gr.Row():
                    editing_type = gr.Radio(
                        label="Chọn loại thay đổi", choices=["Kiểu tóc", "Màu tóc", "Cả hai"], value="both", type="value"
                    )
                with gr.Row():
                    hairstyles = load_hairstyle_list()
                    hairstyle_index = gr.Dropdown(label="Kiểu tóc", choices=hairstyles, value="afro", type="index")
                with gr.Row():
                    color_description = gr.Textbox(label="Màu tóc", value="red")
                with gr.Row():
                    run_button = gr.Button("Run")

            with gr.Column():
                result = gr.Image(label="Result")

    preprocess_button.click(fn=model.detect_and_align_face, inputs=input_image, outputs=aligned_face)
    aligned_face.change(fn=model.reconstruct_face, inputs=aligned_face, outputs=[reconstructed_face, latent])
    editing_type.change(fn=update_step2_components, inputs=editing_type, outputs=[hairstyle_index, color_description])
    run_button.click(
        fn=model.generate,
        inputs=[
            editing_type,
            hairstyle_index,
            color_description,
            latent,
        ],
        outputs=result,
    )

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