Update app.py

app.py

@@ -24,11 +24,16 @@ def predict(image):
     
     return {'label': label, 'confidence': float(confidence)}  # Convert confidence to float
 
+# Custom post-processing function to sort by confidence
+def custom_postprocess(output):
+    sorted_output = sorted(output.items(), key=lambda x: x[1], reverse=True)
+    return f"{sorted_output[0][0]} ({sorted_output[0][1] * 100:.2f}%)"
+
 examples = [["benign.jpg"], ["malignant.jpg"]]
 
 # Define input and output components
 image_input = gr.inputs.Image(shape=(150, 150))
-label_output = gr.outputs.Label()
+label_output = gr.outputs.Label(postprocess=custom_postprocess)
 
 # Define a Gradio interface for user interaction
 iface = gr.Interface(