diff --git a/src/predict/predict_monoloco.py b/src/predict/predict_monoloco.py
index 42657ab..e46d618 100644
--- a/src/predict/predict_monoloco.py
+++ b/src/predict/predict_monoloco.py
@@ -57,19 +57,25 @@ class PredictMonoLoco:
         try:
             with open(args.path_gt, 'r') as f:
                 self.dic_names = json.load(f)
+                print('-' * 120 + "\nMonoloco: Ground-truth file opened\n")
         except FileNotFoundError:
             self.dic_names = None
-            print('-' * 120 + "\nMonoloco: ground truth file not found\n" + '-' * 120)
+            print('-' * 120 + "\nMonoloco: ground-truth file not found\n")
 
     def run(self):
         # Extract calibration matrix if ground-truth file is present or use a default one
         cnt = 0
         name = os.path.basename(self.image_path)
-        if self.dic_names:
+        try:
             kk = self.dic_names[name]['K']
-        else:
-            # kk = [[1266.4, 0., 816.27], [0, 1266.4, 491.5], [0., 0., 1.]]
-            kk = [[718.3351, 0., 600.3891], [0., 718.3351, 181.5122], [0., 0., 1.]]
+            print("Monoloco: matched ground-truth file!\n" + '-' * 120)
+        except (KeyError, TypeError):
+            self.dic_names = None
+            # kk = [[718.3351, 0., 600.3891], [0., 718.3351, 181.5122], [0., 0., 1.]]  # Kitti standard
+            #kk = [[1266.4, 0., 816.27], [0, 1266.4, 491.5], [0., 0., 1.]]  # Nuscenes standard
+            kk = [[1266.4, 0., 816.27], [0, 1266.4, 491.5], [0., 0., 1.]]
+            print("Ground-truth annotations for the image not found\n"
+                  "Using a standard calibration matrix...\n" + '-' * 120)
 
         (inputs_norm, xy_kps), (uv_kps, uv_boxes, uv_centers, uv_shoulders) = \
             get_input_data(self.boxes, self.keypoints, kk, left_to_right=True)
@@ -101,8 +107,9 @@ class PredictMonoLoco:
                 outputs = self.model(inputs)
                 outputs = unnormalize_bi(outputs)
                 end = time.time()
-                print("Total Forward pass time = {:.2f} ms".format((end-start) * 1000))
-                print("Single pass time = {:.2f} ms".format((end - start_single) * 1000))
+                print("Total Forward pass time with {} forward passes = {:.2f} ms"
+                      .format(self.n_dropout, (end-start) * 1000))
+                print("Single forward pass time = {:.2f} ms".format((end - start_single) * 1000))
 
         # Print image and save json
         dic_out = defaultdict(list)