| 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)}%") |
