Update app.py

app.py

@@ -67,7 +67,7 @@ def predict_image(img, confidence_threshold):
     try:
         prediction_1 = clf_1(img_pil)
         result_1 = {pred['label']: pred['score'] for pred in prediction_1}
-        result_1output = [1, result_1['artificial'], result_1['real']]
+        result_1output = [1, result_1['real'], result_1['artificial']]
         print(result_1output)
         # Ensure the result dictionary contains all class names
         for class_name in class_names_1:
@@ -87,7 +87,8 @@ def predict_image(img, confidence_threshold):
     try:
         prediction_2 = clf_2(img_pil)
         result_2 = {pred['label']: pred['score'] for pred in prediction_2}
-        print(result_2)
+        result_2output = [2, result_2['real'], result_2['artificial']]
+        print(result_2output)
         # Ensure the result dictionary contains all class names
         for class_name in class_names_2:
             if class_name not in result_2:
@@ -113,7 +114,8 @@ def predict_image(img, confidence_threshold):
             labels_3[1]: float(probabilities_3[1]),   # Real
             labels_3[0]: float(probabilities_3[0])  # AI
         }
-        print(result_3)
+        result_3output = [3, float(probabilities_3[1]), float(probabilities_3[0])]
+        print(result_3output)
         # Ensure the result dictionary contains all class names
         for class_name in labels_3:
             if class_name not in result_3:
@@ -139,6 +141,7 @@ def predict_image(img, confidence_threshold):
             labels_4[1]: float(probabilities_4[1]),   # Real
             labels_4[0]: float(probabilities_4[0])  # AI
         }
+        result_4output = [4, float(probabilities_4[1]), float(probabilities_4[0])]
         print(result_4)
         # Ensure the result dictionary contains all class names
         for class_name in labels_4: