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("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)
+	predictions = pipeline(image)
+
+	col2.header("Probabilities")
+	for p in predictions:
+		col2.subheader(f"{p['label']}:{round(p['score']*100,1)}%")