app.py

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)}%")