Update app.py

app.py

@@ -0,0 +1,33 @@
+from transformers import pipeline
+import gradio as gr
+from PIL import Image
+
+# Prediction function
+def predict(input_img):
+    # Get the predictions from the pipeline
+    predictions = pipe(input_img)
+    
+    result = {p["label"]: p["score"] for p in predictions}
+    
+    # Return the image and the top predictions as a string
+    top_labels = [f"{label}: {score:.2f}" for label, score in result.items()]
+    return input_img, "\n".join(top_labels)
+
+# Create the Gradio interface
+gradio_app = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(label="Select Image", sources=['upload', 'webcam'], type="pil"),
+    outputs=[
+        gr.Image(label="Processed Image"),
+        gr.Textbox(label="Result", placeholder="Top predictions here")
+    ],
+    title="Age Classification",
+    description="Upload or capture an image to classify age using the SigLIP2 model."
+)
+
+# Launch the app
+gradio_app.launch()
+
+
+if _name=="main_":
+  gradio_app.launch()