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from typing import List, Optional, Tuple | |
from PIL import Image | |
from playwright.sync_api import sync_playwright | |
import os | |
import gradio as gr | |
from gradio_client.client import DEFAULT_TEMP_DIR | |
from transformers import AutoProcessor, AutoModelForCausalLM | |
API_TOKEN = os.getenv("HF_AUTH_TOKEN") | |
# PROCESSOR = AutoProcessor.from_pretrained( | |
# "HuggingFaceM4/img2html", | |
# token=API_TOKEN, | |
# ) | |
IMAGE_GALLERY_PATHS = [ | |
f"example_images/{ex_image}" | |
for ex_image in os.listdir(f"example_images") | |
] | |
def add_file_gallery(selected_state: gr.SelectData, gallery_list: List[str]): | |
# return ( | |
# f"example_images/{gallery_list.root[selected_state.index].image.orig_name}", | |
# "", | |
# ) | |
return f"example_images/{gallery_list.root[selected_state.index].image.orig_name}" | |
def expand_layout(): | |
return gr.Column(scale=2), gr.Textbox() | |
def render_webpage( | |
html_css_code, | |
): | |
with sync_playwright() as p: | |
browser = p.chromium.launch(headless=True) | |
context = browser.new_context( | |
user_agent=( | |
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0" | |
" Safari/537.36" | |
) | |
) | |
page = context.new_page() | |
page.set_content(html_css_code) | |
page.wait_for_load_state("networkidle") | |
output_path_screenshot = f"{DEFAULT_TEMP_DIR}/{hash(html_css_code)}.png" | |
page.screenshot(path=output_path_screenshot, full_page=True) | |
context.close() | |
browser.close() | |
return Image.open(output_path_screenshot) | |
def model_inference( | |
image, | |
): | |
CAR_COMPNAY = """<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="UTF-8"> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
<title>XYZ Car Company</title> | |
<style> | |
body { | |
font-family: 'Arial', sans-serif; | |
margin: 0; | |
padding: 0; | |
background-color: #f4f4f4; | |
} | |
header { | |
background-color: #333; | |
color: #fff; | |
padding: 1em; | |
text-align: center; | |
} | |
nav { | |
background-color: #555; | |
color: #fff; | |
padding: 0.5em; | |
text-align: center; | |
} | |
nav a { | |
color: #fff; | |
text-decoration: none; | |
padding: 0.5em 1em; | |
margin: 0 1em; | |
} | |
section { | |
padding: 2em; | |
} | |
h2 { | |
color: #333; | |
} | |
.car-container { | |
display: flex; | |
flex-wrap: wrap; | |
justify-content: space-around; | |
} | |
.car-card { | |
width: 300px; | |
margin: 1em; | |
border: 1px solid #ddd; | |
border-radius: 5px; | |
overflow: hidden; | |
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); | |
} | |
.car-image { | |
width: 100%; | |
height: 150px; | |
object-fit: cover; | |
} | |
.car-details { | |
padding: 1em; | |
} | |
footer { | |
background-color: #333; | |
color: #fff; | |
text-align: center; | |
padding: 1em; | |
position: fixed; | |
bottom: 0; | |
width: 100%; | |
} | |
</style> | |
</head> | |
<body> | |
<header> | |
<h1>XYZ Car Company</h1> | |
</header> | |
<nav> | |
<a href="#">Home</a> | |
<a href="#">Models</a> | |
<a href="#">About Us</a> | |
<a href="#">Contact</a> | |
</nav> | |
<section> | |
<h2>Our Cars</h2> | |
<div class="car-container"> | |
<div class="car-card"> | |
<img src="car1.jpg" alt="Car 1" class="car-image"> | |
<div class="car-details"> | |
<h3>Model A</h3> | |
<p>Description of Model A.</p> | |
</div> | |
</div> | |
<div class="car-card"> | |
<img src="car2.jpg" alt="Car 2" class="car-image"> | |
<div class="car-details"> | |
<h3>Model B</h3> | |
<p>Description of Model B.</p> | |
</div> | |
</div> | |
<!-- Add more car cards as needed --> | |
</div> | |
</section> | |
<footer> | |
© 2024 XYZ Car Company. All rights reserved. | |
</footer> | |
</body> | |
</html>""" | |
rendered_page = render_webpage(CAR_COMPNAY) | |
return CAR_COMPNAY, rendered_page | |
# textbox = gr.Textbox( | |
# placeholder="Upload an image and ask the AI to create a meme!", | |
# show_label=False, | |
# value="Write a meme about this image.", | |
# visible=True, | |
# container=False, | |
# label="Text input", | |
# scale=8, | |
# max_lines=5, | |
# ) | |
generated_html = gr.Textbox( | |
label="IDEFICS Generated HTML", | |
elem_id="generated_html", | |
) | |
rendered_html = gr.Image( | |
) | |
css = """ | |
.gradio-container{max-width: 1000px!important} | |
h1{display: flex;align-items: center;justify-content: center;gap: .25em} | |
*{transition: width 0.5s ease, flex-grow 0.5s ease} | |
""" | |
with gr.Blocks(title="Img2html", theme=gr.themes.Base(), css=css) as demo: | |
with gr.Row(equal_height=True): | |
# scale=2 when expanded | |
with gr.Column(scale=4, min_width=250) as upload_area: | |
imagebox = gr.Image( | |
type="filepath", label="Image to HTML", height=272, visible=True, sources=["upload", "clipboard"], | |
) | |
with gr.Group(): | |
with gr.Row(): | |
submit_btn = gr.Button( | |
value="▶️ Submit", visible=True, min_width=120 | |
) | |
clear_btn = gr.ClearButton( | |
[imagebox, generated_html, rendered_html], value="🧹 Clear", min_width=120 | |
) | |
regenerate_btn = gr.Button( | |
value="🔄 Regenerate", visible=True, min_width=120 | |
) | |
with gr.Column(scale=5) as result_area: | |
rendered_html.render() | |
with gr.Row(): | |
generated_html.render() | |
with gr.Row(equal_height=True): | |
template_gallery = gr.Gallery( | |
value=IMAGE_GALLERY_PATHS, | |
label="Templates Gallery", | |
allow_preview=False, | |
columns=4, | |
elem_id="gallery", | |
show_share_button=False, | |
height=400, | |
) | |
gr.on( | |
triggers=[ | |
imagebox.upload, | |
submit_btn.click, | |
template_gallery.select, | |
regenerate_btn.click, | |
], | |
fn=model_inference, | |
inputs=[ | |
imagebox, | |
], | |
outputs=[generated_html, rendered_html], | |
queue=False, | |
) | |
regenerate_btn.click( | |
fn=model_inference, | |
inputs=[ | |
imagebox, | |
], | |
outputs=[generated_html, rendered_html], | |
queue=False, | |
) | |
template_gallery.select( | |
fn=add_file_gallery, | |
inputs=[template_gallery], | |
outputs=[imagebox], | |
queue=False, | |
) | |
demo.load( | |
# fn=choose_gallery, | |
# inputs=[gallery_type_choice], | |
# outputs=[template_gallery], | |
queue=False, | |
) | |
demo.queue(max_size=40, api_open=False) | |
demo.launch(max_threads=400) | |