Update app.py

app.py

@@ -8,6 +8,7 @@ import nltk
 from nltk.tokenize import word_tokenize
 from nltk.corpus import stopwords
 from nltk.stem import WordNetLemmatizer
+
 # Download necessary resources
 nltk.download('punkt_tab')
 nltk.download('stopwords')
@@ -16,8 +17,8 @@ nltk.download('wordnet')
 import tensorflow
 import keras
 from keras.utils import pad_sequences
-
 import pickle
+import base64
 
 # Streamlit UI
 st.set_page_config(page_title="News Category Classifier", page_icon="📰", layout="centered")
@@ -29,15 +30,17 @@ def set_background(image_path):
     bg_image_style = f"""
     <style>
         .stApp {{
-            background: url("data:image/png;base64,{encoded_img}") no-repeat center center fixed;
+            background-image: url("data:image/png;base64,{encoded_img}");
             background-size: cover;
+            background-repeat: no-repeat;
+            background-attachment: fixed;
         }}
     </style>
     """
     st.markdown(bg_image_style, unsafe_allow_html=True)
 
 # Update the image path
-set_background("page/News image 2.png")  # Ensure the image is in the correct folder
+set_background("page/Images/bkg4.jpg")  # Ensure the image is in the correct folder
 
 # Initialize stopwords and lemmatizer
 stop_words = set(stopwords.words('english')).union({"pm"})
@@ -156,4 +159,4 @@ if st.button("Analyze 🏷️"):
         category = predict_category(user_input)
         st.markdown(f"<div class='result-box'><span class='result-text'>🗂️ Predicted Category: <strong>{category}</strong></span></div>", unsafe_allow_html=True)
     else:
-        st.warning("⚠️ Please enter some text to analyze.")
+        st.warning("⚠️ Please enter some text to analyze.")