diff --git a/utils/tester.py b/utils/tester.py
index 333625b..f2be261 100644
--- a/utils/tester.py
+++ b/utils/tester.py
@@ -371,7 +371,7 @@ class ModelTester:
 
         return
 
-    def slam_segmentation_test(self, net, test_loader, config, num_votes=100, debug=False):
+    def slam_segmentation_test(self, net, test_loader, config, num_votes=100, debug=True):
         """
         Test method for slam segmentation models
         """
@@ -502,12 +502,13 @@ class ModelTester:
                     if test_loader.dataset.set == 'validation':
 
                         # Insert false columns for ignored labels
+                        frame_probs_uint8_bis = frame_probs_uint8.copy()
                         for l_ind, label_value in enumerate(test_loader.dataset.label_values):
                             if label_value in test_loader.dataset.ignored_labels:
-                                frame_probs_uint8 = np.insert(frame_probs_uint8, l_ind, 0, axis=1)
+                                frame_probs_uint8_bis = np.insert(frame_probs_uint8_bis, l_ind, 0, axis=1)
 
                         # Predicted labels
-                        frame_preds = test_loader.dataset.label_values[np.argmax(frame_probs_uint8,
+                        frame_preds = test_loader.dataset.label_values[np.argmax(frame_probs_uint8_bis,
                                                                                  axis=1)].astype(np.int32)
 
                         # Save some of the frame pots
@@ -528,6 +529,15 @@ class ModelTester:
                                           [frame_points[:, :3], frame_labels, frame_preds],
                                           ['x', 'y', 'z', 'gt', 'pre'])
 
+                            # Also Save lbl probabilities
+                            probpath = join(test_path, folder, filename[:-4] + '_probs.ply')
+                            lbl_names = [test_loader.dataset.label_to_names[l]
+                                         for l in test_loader.dataset.label_values
+                                         if l not in test_loader.dataset.ignored_labels]
+                            write_ply(probpath,
+                                      [frame_points[:, :3], frame_probs_uint8],
+                                      ['x', 'y', 'z'] + lbl_names)
+
                         # keep frame preds in memory
                         all_f_preds[s_ind][f_ind] = frame_preds
                         all_f_labels[s_ind][f_ind] = frame_labels
@@ -575,8 +585,8 @@ class ModelTester:
                     last_display = t[-1]
                     message = 'e{:03d}-i{:04d} => {:.1f}% (timings : {:4.2f} {:4.2f} {:4.2f}) / pots {:d} => {:.1f}%'
                     min_pot = int(torch.floor(torch.min(test_loader.dataset.potentials)))
-                    pot_num = torch.sum(test_loader.dataset.potentials > min_pot).type(torch.int32).item()
-                    current_num = pot_num + (i0 + 1 - config.validation_size) * config.val_batch_num
+                    pot_num = torch.sum(test_loader.dataset.potentials > min_pot + 0.5).type(torch.int32).item()
+                    current_num = pot_num + (i + 1 - config.validation_size) * config.val_batch_num
                     print(message.format(test_epoch, i,
                                          100 * i / config.validation_size,
                                          1000 * (mean_dt[0]),