Update app.py

app.py

@@ -43,20 +43,20 @@ def predict_teeth_health(image):
     # Get the probability of being 'Good'
     probability_good = prediction[0][0]  # Assuming it's a binary classification
 
-     # Return the predicted class name
-    if probability_good > 0.5:
-        return "Predicted: Your Teeth are Good & You Don't Need To Visit Doctor"
-    else:
-        return "Predicted: Your Teeth are Bad & You Need To Visit Doctor"
+    # Define the prediction result
+    result = {
+        "prediction": "Your Teeth are Good & You Don't Need To Visit Doctor" if probability_good > 0.5 else "Your Teeth are Bad & You Need To Visit Doctor"
+    }
+
+    return result
 
 # Define the Gradio interface
 iface = gr.Interface(
     fn=predict_teeth_health,
     inputs=gr.Image(type="pil"),
-    outputs="text",
-    title="<h1 style='color: lightgreen; text-align: center;'>Dentella</h1><p style='text-align: center; color: skyblue; font-size: 25px;'>Please Enter Your Teeth Here...</p>",
+    outputs="json",
+    title="<h1 style='color: lightgreen; text-align: center;'>Dentella</h1><p style='text-align: center; color: skyblue; font-size: 30px;'>Please Enter Your Teeth Here...</p>",
 )
 
-
 # Deploy the Gradio interface using Gradio's hosting service
 iface.launch(share=True)