Create app.py

app.py

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+# Import necessary libraries
+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+# Function to classify age from an image
+def classify_age(image_path):
+    # Load the age classification model
+    age_classifier = pipeline("image-classification", model="nateraw/vit-age-classifier")
+    # Predict age
+    result = age_classifier(image_path)
+    return result
+
+# Main part of the app
+st.set_page_config(page_title="Age Classifier", page_icon="👶")
+st.header("Age Classification using nateraw/vit-age-classifier")
+uploaded_file = st.file_uploader("Upload an image of a person...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Save the uploaded file temporarily
+    with open(uploaded_file.name, "wb") as file:
+        file.write(uploaded_file.getvalue())
+    
+    # Display the uploaded image
+    st.image(uploaded_file, caption="Uploaded Image", use_container_width=True)
+    
+    # Classify age
+    st.text('Classifying age...')
+    age_result = classify_age(uploaded_file.name)
+    
+    # Display the result
+    st.write("Age Classification Result:")
+    for res in age_result:
+        st.write(f"{res['label']}: {res['score']:.2f}")