Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+# Load the pre-trained fast food classifier model from Hugging Face
+classifier = pipeline(task="image-classification", model="AryanKaushik/fastfood-classifier")
+
+st.title("🍔 Fast Food Classifier")
+st.write("Upload an image and find out if it's a burger, pizza, cupcake, fries, or waffle!")
+
+# Upload an image
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    col1, col2 = st.columns(2)
+
+    # Show the image
+    image = Image.open(uploaded_file)
+    col1.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Run prediction
+    predictions = classifier(image)
+
+    # Show results
+    col2.header("Prediction Results")
+    for p in predictions:
+        col2.subheader(f"{p['label']}: {round(p['score'] * 100, 2)}%")