Update app.py

app.py

@@ -87,12 +87,15 @@ def extract_text_qwen(image_file, model, processor):
 
 # Highlight keyword search
 def highlight_text(text, search_term):
-    if not search_term:
+    if not search_term:  # If no search term is provided, return the original text
         return text
+    # Use a regular expression to search for the term, case insensitive
     pattern = re.compile(re.escape(search_term), re.IGNORECASE)
+    # Highlight matched terms with yellow background
     return pattern.sub(lambda m: f'<span style="background-color: yellow;">{m.group()}</span>', text)
 
 # Title and UI
+st.title("DualTextOCRFusion - 🔍")
 st.title("OCR Application - Multimodel Support")
 st.write("Upload an image for OCR using various models, with support for English, Hindi, and Hinglish.")
 
@@ -161,11 +164,16 @@ if predict_button and uploaded_file:
         st.subheader("Extracted Text (Cleaned & Polished)")
         st.markdown(polished_text, unsafe_allow_html=True)
 
+        # Input box for real-time search
         search_query = st.text_input("Search in extracted text:", key="search_query", placeholder="Type to search...")
+        # Update results dynamically based on the search term
         if search_query:
+            # Highlight the search term in the text
             highlighted_text = highlight_text(polished_text, search_query)
             st.markdown("### Highlighted Search Results:")
+            # Render the highlighted text, allowing HTML rendering for the highlight
             st.markdown(highlighted_text, unsafe_allow_html=True)
         else:
+            # If no search term is provided, display the original text
             st.markdown("### Extracted Text:")
-            st.markdown(polished_text, unsafe_allow_html=True)
+            st.markdown(polished_text)