done

app.py

@@ -26,8 +26,16 @@ def predict_from_csv(file_path):
     # Predict using the model
     predictions = model.predict(input_data)
     
-    # Process predictions to readable format if needed
-    return str(predictions)
+      # Determine the predicted class and confidence
+    predicted_class = np.argmax(predictions, axis=1)[0]
+    confidence = np.max(predictions, axis=1)[0]
+
+    # Map numeric class to label
+    class_labels = {0: "Normal", 1: "Anomaly"}
+    label = class_labels[predicted_class]
+    output = f"Predicted Class: {label}, Confidence: {confidence:.4f}"
+    
+    return output
 
 def interface_func(uploaded_file):
     # Use the prediction function on the uploaded file path