Commit

app.py

@@ -1,12 +1,11 @@
-import requests
-import torch
 import streamlit as st
-from transformers import pipeline, AutoProcessor, LlavaForConditionalGeneration
+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:
@@ -18,4 +17,4 @@ if file_name is not None:
 
     col2.header("Probabilities")
     for p in predictions:
-        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
+        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")