File size: 619 Bytes
a9e8aa2 13d68fe a9e8aa2 13d68fe a9e8aa2 13d68fe a9e8aa2 1bb2b01 a9e8aa2 13d68fe a9e8aa2 13d68fe 0bce3e9 13d68fe a9e8aa2 13d68fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | 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(
label="Upload a hot dog candidate image",
type=["jpg", "jpeg", "png", "webp"])
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)}%") |