Update app.py

app.py

@@ -10,8 +10,13 @@ def predict(input_dict):
     if not input_dict or "composite" not in input_dict:
         return {str(i): 0.0 for i in range(10)}
 
+
     image = input_dict["composite"]
 
+    MAX_INTENSITY_SUM = 0.005272861870622912
+
+    
+
     # Remove alpha channel (RGBA → RGB)
     image = image[:, :, :3]
 
@@ -26,6 +31,9 @@ def predict(input_dict):
     image = image / 255.0
     image = image.numpy().reshape(-1, 28, 28, 1)
 
+    if np.sum(image) > MAX_INTENSITY_SUM:
+        return "Please try Again"
+
     # Predict
     prediction = model.predict(image)
     probs = tf.nn.softmax(prediction[0]).numpy()