Update app.py

app.py

@@ -9,11 +9,27 @@ import joblib
 KNN_MODEL_PATH = './knn_pharyngitis_model.pkl'
 EXTRACTOR_PATH = './mobilenetv2_feature_extractor.h5'
 
+# Display a welcome message and note
+st.title("Pharyngitis Classification App")
+st.write("""
+**Please wait while the models are being loaded.**
+""")
+
 # Load the saved models
-st.write("Loading models...")
-knn = joblib.load(KNN_MODEL_PATH)
-feature_extractor = load_model(EXTRACTOR_PATH)
-st.write("Models loaded successfully!")
+with st.spinner("Please wait for a while..."):
+    knn = joblib.load(KNN_MODEL_PATH)
+    feature_extractor = load_model(EXTRACTOR_PATH)
+
+st.success("Models loaded successfully!")
+
+# Display additional information
+st.markdown("""
+### Note:
+- This application predicts whether the uploaded throat image shows signs of *pharyngitis* or not.
+- **Accuracy:** Approximately 80%.
+- **Disclaimer:** This tool is not a substitute for a medical professional's advice. 
+  Please consult a physician if you experience any throat-related issues.
+""")
 
 # Function to preprocess the uploaded image
 def preprocess_image(image):
@@ -30,8 +46,7 @@ def classify_image(image):
     return "Pharyngitis" if prediction[0] == 1 else "No Pharyngitis"
 
 # Streamlit app UI
-st.title("Pharyngitis Classification App")
-st.write("Upload an image to classify it as 'Pharyngitis' or 'No Pharyngitis'.")
+st.write("### Upload an image to classify it as 'Pharyngitis' or 'No Pharyngitis'.")
 
 uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "jpeg", "png"])
 
@@ -41,6 +56,13 @@ if uploaded_file is not None:
     st.image(image, caption="Uploaded Image", use_column_width=True)
 
     # Classify the image
-    st.write("Classifying...")
-    prediction = classify_image(image)
-    st.write(f"Prediction: **{prediction}**")
+    st.write("### Classifying...")
+    with st.spinner("Analyzing the image..."):
+        prediction = classify_image(image)
+    st.success(f"Prediction: **{prediction}**")
+
+# Footer with a link to your LinkedIn profile
+st.markdown("""
+---
+Made with ❤️ by [Haris](https://www.linkedin.com/in/h4r1s)
+""")