Update app.py

app.py

@@ -2,8 +2,8 @@ import streamlit as st
 from PIL import Image
 from transformers import pipeline
 
-# Create an image classification pipeline
-pipe = pipeline("image-classification", model="trpakov/vit-face-expression")
+# Create an image classification pipeline with scores
+pipe = pipeline("image-classification", model="trpakov/vit-face-expression", return_all_scores=True)
 
 # Define emotion labels
 emotion_labels = ["Happy", "Sad", "Angry", "Surprised", "Neutral"]
@@ -28,9 +28,6 @@ if uploaded_image:
     st.image(image, caption=f"Predicted emotion: {predicted_emotion}", use_column_width=True)
 
     # Display scores for each category
-    if "scores" in results[0]:
-        st.write("Emotion Scores:")
-        for label, score in zip(emotion_labels, results[0]["scores"]):
-            st.write(f"{label}: {score:.4f}")
-    else:
-        st.write("Emotion scores not available for this prediction.")
+    st.write("Emotion Scores:")
+    for label, score in zip(emotion_labels, results[0]["scores"]):
+        st.write(f"{label}: {score:.4f}")