Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+import matplotlib.pyplot as plt
+
+# Load the pre-trained model
+age_classifier = pipeline("image-classification", model="nateraw/vit-age-classifier")
+
+# Function to classify age from an image
+def classify_age(image):
+    result = age_classifier(image)
+    predicted_age = result[0]['label']
+    confidence = result[0]['score']
+    return predicted_age, confidence
+
+# Streamlit UI
+st.title("Age Classification App")
+st.write("Upload an image to classify the person's age.")
+
+# File uploader
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+# Process the uploaded image
+if uploaded_file is not None:
+    image = Image.open(uploaded_file).convert("RGB")
+
+    # Display uploaded image
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Get prediction
+    predicted_age, confidence = classify_age(image)
+
+    # Show results
+    st.write(f"### Predicted Age: {predicted_age}")
+    st.write(f"**Confidence:** {confidence:.2f}")