Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+st.title("Image classification : Hot Dog? Or Not?")
+file_name = st.file_uploader("Upload a hot dog candidate image")
+
+if file_name is not None:
+  col1, col2 = st.columns(2)
+  image = Image.open(file_name)
+  col1.image(image, use_column_width=True)
+  # make predictions for the uploaded image 
+  predictions = pipeline(image)
+  col2.header("Probabilities/result")
+  for p in predictions:
+    col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")