Update app.py

app.py

@@ -1,39 +1,43 @@
-import streamlit as st
-from PIL import Image
-from ocr_utils import extract_text
-
-import numpy as np
-# Streamlit application title
-st.title("OCR and Keyword Search Application")
-st.write("Upload an image containing Hindi and English text to extract and search within the text.")
-
-# File uploader for image
-uploaded_file = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])
-
-if uploaded_file is not None:
-    # Open the uploaded image using PIL
-    image = Image.open(uploaded_file)
-    st.image(image, caption='Uploaded Image', use_column_width=True)
-
-    # Convert the image to a NumPy array
-    image_np = np.array(image)
-
-    # Perform OCR on the uploaded image using the utility function
-    full_text = extract_text(image_np)
-
-    # Display the extracted text
-    st.subheader("Extracted Text")
-    st.write(full_text)
-
-    # Text input for keyword search
-    keyword = st.text_input("Enter Keyword to Search")
-
-# Highlight the keyword in the extracted text
-    if keyword:
-        highlighted_text = full_text.replace(
-            keyword, f"<mark style='background-color: yellow; color: black;'>{keyword}</mark>")
-        st.subheader("Highlighted Search Results")
-        st.markdown(highlighted_text, unsafe_allow_html=True)
-    else:
-        st.subheader("Highlighted Search Results")
-        st.write("No keyword entered for highlighting.")
+import streamlit as st
+from PIL import Image
+from ocr_utils import extract_text
+
+import numpy as np
+# Streamlit application title
+st.title("OCR and Keyword Search Application")
+st.write("Upload an image containing Hindi and English text to extract and search within the text.")
+
+# File uploader for image
+uploaded_file = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Open the uploaded image using PIL
+    image = Image.open(uploaded_file)
+    st.image(image, caption='Uploaded Image', use_column_width=True)
+
+    # Convert the image to a NumPy array
+    image_np = np.array(image)
+
+    # Perform OCR on the uploaded image using the utility function
+    full_text = extract_text(image_np)
+
+    # Display the extracted text
+    st.subheader("Extracted Text")
+    st.write(full_text)
+
+    # Text input for keyword search
+    keyword = st.text_input("Enter Keyword to Search")
+
+    #Highlight the keyword in the extracted text
+    if keyword:
+        if keyword in full_text:
+            highlighted_text = full_text.replace(
+                keyword, f"<mark style='background-color: yellow; color: black;'>{keyword}</mark>")
+            st.subheader("Highlighted Search Results")
+            st.markdown(highlighted_text, unsafe_allow_html=True)
+        else:
+            st.subheader("Highlighted Search Results")
+            st.write(f"The keyword '{keyword}' was not found in the text.")
+    else:
+        st.subheader("Highlighted Search Results")
+        st.write("No keyword entered for highlighting.")