Update app.py

app.py

@@ -5,9 +5,6 @@ from transformers import pipeline
 # Create an image classification pipeline with scores
 pipe = pipeline("image-classification", model="trpakov/vit-face-expression", top_k=None)
 
-# Define emotion labels
-##emotion_labels = ["Neutral", "Sad", "Angry", "Surprised", "Happy"]
-
 # Streamlit app
 st.title("Emotion Recognition with vit-face-expression")
 
@@ -39,12 +36,14 @@ if st.button("Predict Emotions") and uploaded_images:
 
         # Display the keys and values of all results
         st.write("Keys and Values of all results:")
+        col1, col2 = st.columns(2)
         for i, result in enumerate(results):
-            st.write(f"Keys and Values of results[{i}]:")
+            col = col1 if i == 0 else col2
+            col.write(f"Keys and Values of results[{i}]:")
             for res in result:
                 label = res["label"]
                 score = res["score"]
-                st.write(f"{label}: {score:.4f}")
+                col.write(f"{label}: {score:.4f}")
             
     else:
         # Open the uploaded images