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print("Hello")
# 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)}%")
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