Upload app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+import io
+
+# Load the Hugging Face image classification model
+classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
+
+# Streamlit UI
+st.title("Image Classifier with Hugging Face 🤗")
+st.write("Upload an image, and the model will predict its content!")
+
+# Upload file
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
+
+if uploaded_file is not None:
+    # Display the uploaded image
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Run classification
+    st.write("Classifying...")
+    results = classifier(image)
+
+    # Display results
+    for result in results:
+        st.write(f"**{result['label']}**: {result['score']:.4f}")