Update app.py

app.py

@@ -44,4 +44,32 @@ def predict_emotion_onnx(model, image_input):
     input_name = model.get_inputs()[0].name
     output_name = model.get_outputs()[0].name
     # Run the model
-    prediction = model.run([out
+    prediction = model.run([output_name], {input_name: image_input})
+    return prediction[0]
+
+# Streamlit UI
+st.title("Emotion Detection")
+
+# Upload an image
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Open and display the uploaded image
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Load model
+    onnx_model = load_model()
+
+    # Preprocess the image
+    image_input = preprocess_image(image)
+
+    # Get emotion prediction
+    emotion_prediction = predict_emotion_onnx(onnx_model, image_input)
+
+    # Get the emotion label and confidence
+    emotion_label, confidence = get_emotion_from_output(emotion_prediction)
+
+    # Display the predicted emotion and confidence
+    st.write(f"Predicted Emotion: {emotion_label}")
+    st.write(f"Confidence: {confidence:.2f}")