add display function

Author: ZHANG Zhiwei

openunreid/apis/test.py

@@ -220,11 +220,9 @@ def final_test(cfg, model, cmc_topk=(1, 5, 10)):
             )
             all_cmc.append(cmc)
             all_mAP.append(mAP)
-    print("\n")
-    print("Mean AP: {:4.1%}".format(np.mean(all_mAP)))
-    print("CMC Scores:")
-    for k in cmc_topk:
-        print("  top-{:<4}{:12.1%}".format(k, np.mean(all_cmc, axis=0)[k - 1]))
+
+
+    display(cfg, all_mAP, all_cmc, cmc_topk)
 
     end_time = time.monotonic()
     print("Testing time: ", timedelta(seconds=end_time - start_time))

openunreid/core/metrics/rank.py

@@ -5,6 +5,8 @@
 
 import numpy as np
 
+from openunreid.utils.logger import display
+
 try:
     from .rank_cylib.rank_cy import evaluate_cy
 
@@ -202,16 +204,7 @@ def evaluate_rank(
             distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_metric_cuhk03
         )
 
-    if verbose and cfg.TRAIN.num_repeat == 10:
-        print("\n")
-        print("Mean AP: {:4.1%}".format(map))
-        print("CMC Scores:")
-        for k in cmc_topk:
-            print("  top-{:<4}{:12.1%}".format(k, cmc[k - 1]))
-    else:
-        print("\n")
-        print("CMC Scores:")
-        for k in cmc_topk:
-            print("  top-{:<4}{:12.1%}".format(k, cmc[k - 1]))
+    if verbose:
+        display(cfg, map, cmc, cmc_topk)
 
     return cmc, map

openunreid/utils/logger.py

@@ -1,6 +1,8 @@
 import os
 import sys
 
+import numpy as np
+
 from .dist_utils import get_dist_info, synchronize
 from .file_utils import mkdir_if_missing
 
@@ -42,3 +44,17 @@ def close(self):
         self.console.close()
         if self.file is not None:
             self.file.close()
+
+
+def display(cfg, map, cmc, cmc_topk=(1, 5, 10)):
+    if cfg.TRAIN.num_repeat == 10:
+        print("\n")
+        print("Mean AP: {:4.1%}".format(np.mean(map)))
+        print("CMC Scores:")
+        for k in cmc_topk:
+            print("  top-{:<4}{:12.1%}".format(k, np.mean(cmc, axis=0)[k - 1]))
+    else:
+        print("\n")
+        print("CMC Scores:")
+        for k in cmc_topk:
+            print("  top-{:<4}{:12.1%}".format(k, np.mean(cmc, axis=0)[k - 1]))