import os
import time
import gradio as gr
from client1 import inference

title = "Dreamoving-Phantom"
img_urls=['https://public-vigen-video.oss-cn-shanghai.aliyuncs.com/public/dashscope/show3.png']
description = f""" Gradio demo for [Dreamoving-Phantom](https://github.com/dreamoving/Phantom)  
  
DreaMoving-Phantom is a general and automatic image enhancement and super resolution framework.  
  
**No need to adjust parameters or select models, just run with one click.** The demo can be adapted to a variety of scenarios.  
  
🔥 New feature: We added text super-resolution module so that the demo can better handle text scenes. This module will still be updated iteratively.  
  
🧭 Instructions: Input resolution: 64<=short_side<=2160, long_side<=3840, aspect ratio<=4; best input resolution: no larger than 1080p.  
"""


examples=[['examples/3.png'],['examples/4.png'],['examples/5.png'],['examples/6.png'],
            ['examples/7.png'],['examples/8.png'],['examples/1.png'],['examples/9.jpg'],['examples/10.png'],
            ['examples/12.png'],['examples/13.png'],['examples/14.png']]
# result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery").style(grid=2)

with gr.Blocks(css="style.css") as demo:

    gr.Markdown(f"<h1 style='text-align: center; font-size: 2em;'>{title}</h1>")
    gr.Markdown(description, elem_id='description')

    with gr.Row():
        with gr.Column(scale=0.67):
            input_image = gr.Image(type="pil", label="Input Image", image_mode="RGBA")
            upsample_scale = gr.Slider(label="Upsample Scale", minimum=1, maximum=4, value=2, step=1, elem_id='slider')

            btn = gr.Button("Run", elem_id='button_param')
        
        with gr.Column():
            output_gallery = gr.Gallery(label="Output", elem_id="output_gallery")
            # output_gallery = gr.Image(type="pil", label="Output", elem_id="output_gallery", image_mode="RGBA")
            output_text = gr.Textbox(label="Log", elem_id="output_text")

    btn.click(
        inference, 
        inputs=[input_image, upsample_scale], 
        outputs=[output_gallery, output_text]
    )
    
    with gr.Row():
        with gr.Column(scale=2):
            gr.Markdown('**Examples**', elem_id='example')
            gr.Examples(label='', examples=examples, inputs=[input_image, upsample_scale], outputs=[output_gallery, output_text], examples_per_page=15, elem_id='examples')
        
        with gr.Column(scale=3):
            additional_text = "**Gallery**"
            gr.Markdown(additional_text, elem_id='additional_text')
            gr.HTML(
                f"""
                <div style='text-align: center;'>
                    <img src='{img_urls[0]}' alt='gallery' style='max-width: 100%; height: auto; margin-top: 5px;'>
                </div>
                """,
                elem_id='html_image'
            )


# concurrency_count, concurrency_limit, max_threads
demo.queue(api_open=False, max_size=1000).launch(
    server_name="0.0.0.0", # if os.getenv('GRADIO_LISTEN', '') != '' else "127.0.0.1",
    share=True,
    server_port=7860,
    root_path=f"/{os.getenv('GRADIO_PROXY_PATH')}" if os.getenv('GRADIO_PROXY_PATH') else ""
)