Create app.py

app.py

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+import pandas as pd
+from PIL import Image
+import streamlit as st
+from transformers import pipeline
+
+
+pipeline = pipeline(task="image-classification", model="nateraw/vit-age-classifier")
+
+def predict(image):
+    predictions = pipeline(image)
+    return {p["label"]: p["score"] for p in predictions}
+
+def main():
+    st.title("Age Classification From Image")
+    
+    with st.form("my_form"):
+        uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "jpeg", "png"])
+
+        if uploaded_file is not None:
+        # Display the uploaded image
+            image = Image.open(uploaded_file)
+            st.image(image, caption="Your uploaded Image", use_column_width=True)
+        clicked = st.form_submit_button("Press to predict")
+        if clicked:
+            results = predict(image)
+            k = [] 
+            v = []
+            for key, value in results.items():
+                value = round(value*100,2)
+                v.append(value)
+                k.append(key)
+            vp = [str(item) + '%' for item in v]
+            result = k[0]
+            st.success('The predicted age is {}'.format(result))
+            df = pd.DataFrame({'Prediction': k,'Accuracy':vp})
+            st.dataframe(df,hide_index=True)
+
+if __name__ == "__main__":
+    main()