add threshold for uncertain predictions

app.py

@@ -20,6 +20,7 @@ except Exception as e:
     print(f"CRITICAL ERROR: Failed to load model. {e}", file=sys.stderr)
 
 CLASS_NAMES = ['Mild Demented', 'Moderate Demented', 'Non Demented', 'Very Mild Demented']
+CONFIDENCE_THRESHOLD = 0.80
 
 def prepare_image(img_bytes):
     try:
@@ -61,24 +62,29 @@ def predict():
     
     try:
         file_bytes = file.read()
-        
         processed_img = prepare_image(file_bytes)
         
         prediction_tensor = model(processed_img, training=False)
-        
         prediction = prediction_tensor.numpy()
         
         class_index = np.argmax(prediction)
         confidence = float(np.max(prediction))
         
-        result_class = CLASS_NAMES[class_index]
-        
-        print(f"Prediction: {result_class} ({confidence:.2%})", file=sys.stderr)
+        if confidence < CONFIDENCE_THRESHOLD:
+            result_class = "Not Sure"
+            message = "Uncertain prediction. Please interpret with caution or upload a clearer image."
+            is_uncertain = True
+        else:
+            result_class = CLASS_NAMES[class_index]
+            message = "Prediction success."
+            is_uncertain = False
         
         result = {
             'result': result_class,
             'confidence': confidence,
-            'index': int(class_index)
+            'message': message,
+            'is_uncertain': is_uncertain,
+            'top_class_suggestion': CLASS_NAMES[class_index] 
         }
         
         return jsonify(result)