'''
Author: [egrt]
Date: 2022-08-05 15:30:04
LastEditors: [egrt]
LastEditTime: 2022-08-17 20:58:37
Description: 
'''
import os
os.system('pip install requirements.txt')
import gradio as gr
from AutoML import Classification

classfication = Classification()

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            name_box    = gr.Textbox(label="艺术家姓名")
            date_box    = gr.Number(label="艺术品创作时间(年)")
            classification_box = gr.CheckboxGroup(label="艺术品类型", choices=["中国山水画", "中国花鸟画", "风景油画",
                "水粉画", "油画", "布面油画", "没骨画", "中国画"])
            level_box   = gr.CheckboxGroup(label="艺术家级别", choices=["国家级"])
            height_box  = gr.Number(label="艺术品高度(cm)")
            width_box   = gr.Number(label="艺术品宽度(cm)")
            
        with gr.Column():
            title_box   = gr.Markdown("## 艺术品价值预测Demo")
            image_box   = gr.Image(label="艺术品照片", type='pil')
            with gr.Row():
                submit_btn = gr.Button("开始预测")
            error_box   = gr.Textbox(label="错误", visible=False)
            with gr.Row(visible=False) as output_col:
                prices_box = gr.Number(label="预测的艺术品价格(￥)")
                

    def submit(name, date, classification, level, height, width, image):
        # 填写信息错误则显示报错提示框
        if len(name)==0 or len(classification)==0 or len(level) == 0 or image==None:
            return {error_box: gr.update(value="请填写所有信息", visible=True)}
        else:
            # 正确预测之后则去除报错提示框
            error_box: gr.update(visible=False)
            prices = classfication.detect_one(name, date, level[0], classification[0], height, width)
            return {
                output_col: gr.update(visible=True),
                prices_box: int(prices),
            }

    submit_btn.click(
        submit,
        [name_box, date_box, classification_box, level_box, height_box, width_box, image_box],
        [error_box, prices_box, output_col],
    )

demo.launch()