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("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)}%")