Update app.py

app.py

@@ -1,10 +1,33 @@
 import streamlit as st
 from transformers import pipeline
-pipe = pipeline ( 'sentiment-analysis')
-text = st.text_area('Enter some text ')
-if text :
-    out = pipe(text)
-    st.json(out)
+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)}%")
+
+# Second app
+# import streamlit as st
+# from transformers import pipeline
+# pipe = pipeline ( 'sentiment-analysis')
+# text = st.text_area('Enter some text ')
+# if text :
+#     out = pipe(text)
+#     st.json(out)
+
+# First app
 # x = st.slider('Select a value')
 # st.write(x, 'squared is', x * x)