diff --git a/lib/utils/evaluation.py b/lib/utils/evaluation.py
index fba16af..1fdc7e3 100644
--- a/lib/utils/evaluation.py
+++ b/lib/utils/evaluation.py
@@ -57,7 +57,7 @@ def identification(data, dataset, metric='euc'):
         raise KeyError("DataSet %s hasn't been supported !" % dataset)
     num_rank = 5
     acc = np.zeros([len(probe_seq_dict[dataset]),
-                   view_num, view_num, num_rank]) - 1.
+                    view_num, view_num, num_rank]) - 1.
     for (p, probe_seq) in enumerate(probe_seq_dict[dataset]):
         for gallery_seq in gallery_seq_dict[dataset]:
             for (v1, probe_view) in enumerate(view_list):
@@ -93,9 +93,9 @@ def identification(data, dataset, metric='euc'):
                 de_diag(acc[0, :, :, i]),
                 de_diag(acc[1, :, :, i]),
                 de_diag(acc[2, :, :, i])))
-        result_dict["scalar/test_accuracy/NM"] = acc[0, :, :, i]
-        result_dict["scalar/test_accuracy/BG"] = acc[1, :, :, i]
-        result_dict["scalar/test_accuracy/CL"] = acc[2, :, :, i]
+        result_dict["scalar/test_accuracy/NM"] = de_diag(acc[0, :, :, i])
+        result_dict["scalar/test_accuracy/BG"] = de_diag(acc[1, :, :, i])
+        result_dict["scalar/test_accuracy/CL"] = de_diag(acc[2, :, :, i])
         np.set_printoptions(precision=2, floatmode='fixed')
         for i in range(1):
             msg_mgr.log_info(
@@ -107,9 +107,8 @@ def identification(data, dataset, metric='euc'):
         msg_mgr.log_info('===Rank-1 (Include identical-view cases)===')
         msg_mgr.log_info('NM: %.3f ' % (np.mean(acc[0, :, :, 0])))
         msg_mgr.log_info('===Rank-1 (Exclude identical-view cases)===')
-        msg_mgr.log_info('NM: %.3f ' % (np.mean(de_diag(acc[0, :, :, 0]))))
-        result_dict["scalar/test_accuracy/NM"] = np.mean(
-            de_diag(acc[0, :, :, 0]))
+        msg_mgr.log_info('NM: %.3f ' % (de_diag(acc[0, :, :, 0])))
+        result_dict["scalar/test_accuracy/NM"] = de_diag(acc[0, :, :, 0])
     return result_dict