Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 from transformers import AutoModel, AutoTokenizer
 import os
-import re  # Import regular expressions module
+import re  
 
 # Load the OCR model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
@@ -12,47 +12,47 @@ model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2_0',
                                   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
+    for line in extracted_text.splitlines():  
+        if re.search(pattern, line):  
+            highlighted_line = re.sub(pattern, highlight, line)  
             highlighted_text.append(highlighted_line)
     
     if highlighted_text:
-        return '<br>'.join(highlighted_text)  # Join the lines with HTML <br> for line breaks
+        return '<br>'.join(highlighted_text)  
     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)")
@@ -64,7 +64,7 @@ with gr.Blocks() as demo:
                          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")
     
@@ -74,5 +74,5 @@ with gr.Blocks() as demo:
                         inputs=[text_output, keyword_input], 
                         outputs=search_result)
 
-# Launch the Gradio app
+
 demo.launch(share=True)