update app.py

app.py

@@ -1,9 +1,9 @@
+
 import streamlit as st
 from transformers import pipeline
 from PIL import Image
 
 st.set_page_config(page_title="ViT Image Classifier")
-
 st.title("ViT Image Classification")
 
 @st.cache_resource
@@ -17,15 +17,10 @@ uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
 if uploaded_file is not None:
     image = Image.open(uploaded_file).convert("RGB")
     st.image(image, caption="Uploaded Image", use_column_width=True)
-
+    
     with st.spinner("Classifying..."):
         preds = pipe(image)
-
+        
     st.subheader("Predictions")
     for i, pred in enumerate(preds):
-        st.write(f"{i+1}. {pred['label']} ({pred['score']:.3f})")
-
-# This is optional but sometimes helps initialization on some platforms
-if __name__ == "__main__":
-    import streamlit.web.bootstrap
-    streamlit.web.bootstrap.run()
+        st.write(f"{i+1}. {pred['label']} ({pred['score']:.3f})")