Update app.py

app.py

@@ -81,8 +81,34 @@ def predict_with_sliding_window(audio_path, onnx_model_path, window_size=64600,
     return majority_class, avg_probability
 
 # Streamlit app
-st.title("Audio Spoof Detection with ONNX Model")
-st.write("Upload an audio file to detect if it is Real or Fake.")
+st.set_page_config(page_title="Audio Spoof Detection", page_icon="🎵", layout="centered")
+
+# Header Section
+st.markdown("<h1 style='text-align: center; color: blue;'>Audio Spoof Detection</h1>", unsafe_allow_html=True)
+st.markdown(
+    """
+    <p style='text-align: center;'>
+    Detect whether an uploaded audio file is <strong>Real</strong> or <strong>Fake</strong> using an ONNX model.
+    </p>
+    """,
+    unsafe_allow_html=True,
+)
+
+# Sidebar
+st.sidebar.header("Instructions")
+st.sidebar.write(
+    """
+    - Upload an audio file in WAV or MP3 format.
+    - Wait for the model to process the file.
+    - View the prediction result and confidence score.
+    """
+)
+st.sidebar.markdown("### About the Model")
+st.sidebar.info(
+    """
+    The model is trained to classify audio as Real or Fake using a RawNet-based architecture.
+    """
+)
 
 # File uploader
 uploaded_file = st.file_uploader("Upload your audio file (WAV or MP3)", type=["wav", "mp3"])
@@ -94,18 +120,30 @@ onnx_model_url = "https://huggingface.co/Mrkomiljon/DeepVoiceGuard/resolve/main/
 onnx_model_path = download_model(onnx_model_url)
 
 if uploaded_file is not None:
+    st.markdown("<h3 style='text-align: center;'>Processing Your File...</h3>", unsafe_allow_html=True)
+
     # Save uploaded file temporarily
     with open("temp_audio_file.wav", "wb") as f:
         f.write(uploaded_file.read())
 
     # Perform prediction
-    with st.spinner("Processing..."):
+    with st.spinner("Running the model..."):
         result, avg_probability = predict_with_sliding_window("temp_audio_file.wav", onnx_model_path)
 
     # Display results
     st.success(f"Prediction: {result}")
-    st.info(f"Confidence: {avg_probability:.2f}%")
+    st.metric(label="Confidence", value=f"{avg_probability:.2f}%", delta=None)
 
     # Clean up temporary file
     os.remove("temp_audio_file.wav")
 
+# Footer
+st.markdown(
+    """
+    <hr>
+    <p style='text-align: center; font-size: small;'>
+    Created with ❤️ using Streamlit.
+    </p>
+    """,
+    unsafe_allow_html=True,
+)