update fast mode

train.py

@@ -303,7 +303,7 @@ def train(hyp):
                                              model=ema.ema,
                                              single_cls=opt.single_cls,
                                              dataloader=testloader,
-                                             fast=ni < n_burn)
+                                             fast=epoch > epochs / 2)
 
         # Write
         with open(results_file, 'a') as f:

utils/utils.py

@@ -526,12 +526,11 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, fast=False, c
     time_limit = 10.0  # seconds to quit after
     redundant = True  # require redundant detections
     fast |= conf_thres > 0.001  # fast mode
+    multi_label = nc > 1  # multiple labels per box (adds 0.5ms/img)
     if fast:
         merge = False
-        multi_label = nc > 1  # multiple labels per box (adds 0.5ms/img)
     else:
         merge = True  # merge for best mAP (adds 0.5ms/img)
-        multi_label = nc > 1  # multiple labels per box (adds 0.5ms/img)
 
     t = time.time()
     output = [None] * prediction.shape[0]