Update app.py

app.py

@@ -1,14 +1,20 @@
 import streamlit as st
 from transformers import pipeline
+from PIL import Image
 
-pipeline = pipeline(task="conversational", model="lmsys/vicuna-7b-v1.5")
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-st.title("Conversational AI with FastChat")
+st.title("Hot Dog? Or Not?")
 
-query = st.text_input("Enter your query:")
+file_name = st.file_uploader("Upload a hot dog candidate image")
 
-if query is not None:
-    response = pipeline(query)
+if file_name is not None:
+    col1, col2 = st.columns(2)
 
-    st.subheader("Response:")
-    st.write(response["text"])
+    image = Image.open(file_name)
+    col1.image(image, use_column_width=True)
+    predictions = pipeline(image)
+
+    col2.header("Probabilities")
+    for p in predictions:
+        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")