Update app.py

app.py

@@ -29,7 +29,7 @@ def tumor_detection(img, model):
     return "Tumor Detected" if res else "No Tumor"
 
 # Streamlit App
-st.title("Deep Prediction Models")
+st.title("Multimodel Prediction")
 
 # Choose between tasks
 task = st.radio("Select Task", ("Sentiment Classification", "Tumor Detection"))
@@ -54,9 +54,9 @@ if task == "Sentiment Classification":
         elif model_option == "DNN":
             model = load_model('DNN_model.keras')
         elif model_option == "RNN":
-            model = load_model('RNN_imdb.keras')
+            model = load_model('RN.keras')
         elif model_option == "LSTM":
-            model = load_model('lstm_imdb.keras')
+            model = load_model('imdb_model.h5')
 
         if st.button("Classify Sentiment"):
             result = sentiment_classification(new_review_text, model)
@@ -69,7 +69,7 @@ elif task == "Tumor Detection":
 
     if uploaded_file is not None:
         # Load the tumor detection model
-        model = load_model('CN.h5')
+        model = load_model('tumor_model.h5')
         st.image(uploaded_file, caption="Uploaded Image.", use_column_width=False, width=200)
         st.write("")