Update app.py

app.py

@@ -1,16 +1,17 @@
 import gradio as gr
 import easyocr
 import re
+from PIL import Image
+import numpy as np
 
 # Initialize the EasyOCR reader for Hindi and English
 reader = easyocr.Reader(['hi', 'en'])
 
-# Step 1: Function to extract text using EasyOCR for both Hindi and English
-import numpy as np
-
-# Step 1: Function to extract text using EasyOCR for both Hindi and English with error handling
+# Function to extract text using EasyOCR for both Hindi and English with error handling
 def extract_text(image):
     try:
+        # Resize the image to speed up processing (optional)
+        image = image.resize((800, 800))  # Resize to 800x800 pixels
         # Convert PIL image to NumPy array
         image_np = np.array(image)
         # Extract text using EasyOCR
@@ -21,9 +22,7 @@ def extract_text(image):
         # Return the error message if an exception occurs
         return f"Error occurred: {str(e)}"
 
-
-
-# Step 2: Function to search and highlight the keyword in the extracted text
+# Function to search and highlight the keyword in the extracted text
 def search_keyword(extracted_text, keyword):
     if keyword.lower() in extracted_text.lower():
         # Highlight the keyword in the text using re for case-insensitive replacement
@@ -47,10 +46,10 @@ with gr.Blocks() as demo:
     
     highlighted_output = gr.Textbox(label="Result", interactive=False)
 
-    # Step 1: When the user clicks the extract button, extract the text
+    # When the user clicks the extract button, extract the text
     extract_button.click(fn=extract_text, inputs=image_input, outputs=extracted_text_output)
 
-    # Step 2: When the user clicks the search button, search for the keyword
+    # When the user clicks the search button, search for the keyword
     search_button.click(fn=search_keyword, inputs=[extracted_text_output, keyword_input], outputs=highlighted_output)
 
 # Launch the web app with sharing enabled