diff --git a/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/eval.py b/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/eval.py
index ac379e530ca1dfad74adf3857cb9b3decefac3b0..88ec8c8915ff1b94521a569b433626caa6705827 100644
--- a/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/eval.py
+++ b/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/eval.py
@@ -17,6 +17,7 @@
 #!python3
 import argparse
 import os
+import sys
 import torch
 if torch.__version__ >= "1.8":
     import torch_npu
@@ -192,6 +193,7 @@ class Eval:
         with torch.no_grad():
             for _, data_loader in self.data_loaders.items():
                 raw_metrics = []
+                time_cost = sys.maxsize
                 for i, batch in tqdm(enumerate(data_loader.train_loader), total=len(data_loader.train_loader)):
                     if self.args['test_speed']:
                         time_cost = self.report_speed(model, batch, times=50)
@@ -202,8 +204,7 @@ class Eval:
                     if not os.path.isdir(self.args['result_dir']):
                         os.mkdir(self.args['result_dir'])
                     self.format_output(batch, output)
-                    time_cost = (time.time() - start)
-                    print("Time:",time_cost)
+                    time_cost = min((time.time() - start), time_cost)
                     raw_metric = self.structure.measurer.validate_measure(batch, output, is_output_polygon=self.args['polygon'], box_thresh=self.args['box_thresh'])
                     raw_metrics.append(raw_metric)
 
@@ -211,6 +212,8 @@ class Eval:
                         vis_image = self.structure.visualizer.visualize(batch, output, pred)
                         self.logger.save_image_dict(vis_image)
                         vis_images.update(vis_image)
+                    if i == len(data_loader.train_loader) - 1:
+                        print("Time:", time_cost)
                 metrics = self.structure.measurer.gather_measure(raw_metrics, self.logger)
                 for key, metric in metrics.items():
                     self.logger.info('%s : %f (%d)' % (key, metric.avg, metric.count))
diff --git a/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/test/eval.sh b/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/test/eval.sh
index 2be1e64ba71f2eb720a040fef35b0ea778f58fbe..2847075f3108b1d85b7229ec0c71f1f4d8d60b89 100644
--- a/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/test/eval.sh
+++ b/PyTorch/built-in/cv/detection/DB_ID0706_for_PyTorch/test/eval.sh
@@ -98,7 +98,7 @@ e2e_time=$(( $end_time - $start_time ))
 # 结果打印，不需要修改
 echo "------------------ Final result ------------------"
 # 输出性能FPS，需要模型审视修改
-FPS=`grep -a 'Time' ${test_path_dir}/output/${ASCEND_DEVICE_ID}/test_${ASCEND_DEVICE_ID}.log | tail -n 10 | awk '{print$2}' | awk '{sum+=$1} END {print ('$batch_size')/(sum/NR)}'`
+FPS=`grep -a 'Time' ${test_path_dir}/output/${ASCEND_DEVICE_ID}/test_${ASCEND_DEVICE_ID}.log | tail -n 1 | awk '{print$2}' | awk '{sum+=$1} END {print ('$batch_size')/(sum/NR)}'`
 FPS=${FPS#* }  # 去除前面的空格字符
 # 打印，不需要修改
 echo "Final Performance images/sec : $FPS"