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import gradio as gr
from transformers import AutoModel, AutoTokenizer
import os
import re # Import regular expressions module
# Load the OCR model and tokenizer
tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2_0',
trust_remote_code=True,
low_cpu_mem_usage=True,
device_map='cuda',
use_safetensors=True,
pad_token_id=tokenizer.eos_token_id).eval().cuda()
# Define the function to process images and extract text
def extract_text_from_image(image):
# Save the uploaded image temporarily
image_path = "temp_image.jpg"
image.save(image_path)
# Call the model to perform OCR
extracted_text = model.chat(tokenizer, image_path, ocr_type='ocr')
# Remove the temporary image file
os.remove(image_path)
return extracted_text
# Function to search for the keyword in extracted text and highlight it
def search_and_highlight_keyword(extracted_text, keyword):
if not keyword:
return "<p>Please provide a keyword for searching.</p>"
# Case-insensitive search and replace keyword with <mark> tag for highlighting
def highlight(match):
# Custom background color and text color for highlighting
return f"<mark style='background-color: #ffcc00; color: black;'>{match.group(0)}</mark>"
# Use regular expression to find the keyword in a case-insensitive manner
pattern = re.compile(re.escape(keyword), re.IGNORECASE)
highlighted_text = []
for line in extracted_text.splitlines(): # Split text into lines
if re.search(pattern, line): # If keyword is found in the line
highlighted_line = re.sub(pattern, highlight, line) # Highlight keyword
highlighted_text.append(highlighted_line)
if highlighted_text:
return '<br>'.join(highlighted_text) # Join the lines with HTML <br> for line breaks
else:
return f"<p>Keyword '{keyword}' not found in the text.</p>"
# Gradio interface components
with gr.Blocks() as demo:
# Image upload and OCR
gr.Markdown("# OCR and Keyword Search App with Highlighting")
image_input = gr.Image(type="pil", label="Upload an Image (JPEG format)")
text_output = gr.Textbox(label="Extracted Text", placeholder="Text will appear here after OCR.")
extract_button = gr.Button("Extract Text")
extract_button.click(fn=extract_text_from_image,
inputs=image_input,
outputs=text_output)
# Keyword search and highlight
keyword_input = gr.Textbox(label="Enter Keyword to Search and Highlight")
search_result = gr.HTML(label="Highlighted Text with Keyword")
search_button = gr.Button("Search and Highlight Keyword")
search_button.click(fn=search_and_highlight_keyword,
inputs=[text_output, keyword_input],
outputs=search_result)
# Launch the Gradio app
demo.launch(share=True)
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