diff --git a/test_IVF.py b/test_IVF.py
index 2bb4b7a..4b84b1f 100644
--- a/test_IVF.py
+++ b/test_IVF.py
@@ -8,7 +8,6 @@ import torch.nn as nn
 from utils.img_read_save import img_save,image_read_cv2
 import warnings
 import logging
-# 增加
 warnings.filterwarnings("ignore")
 logging.basicConfig(level=logging.CRITICAL)
 
@@ -26,7 +25,6 @@ for dataset_name in ["MSRS","TNO","RoadScene"]:
     device = 'cuda' if torch.cuda.is_available() else 'cpu'
     Encoder = nn.DataParallel(Restormer_Encoder()).to(device)
     Decoder = nn.DataParallel(Restormer_Decoder()).to(device)
-    # BaseFuseLayer = nn.DataParallel(BaseFeatureExtraction(dim=64, num_heads=8)).to(device)
     BaseFuseLayer = nn.DataParallel(BaseFeatureExtraction(dim=64)).to(device)
     DetailFuseLayer = nn.DataParallel(DetailFeatureExtraction(num_layers=1)).to(device)
 
@@ -43,12 +41,9 @@ for dataset_name in ["MSRS","TNO","RoadScene"]:
         for img_name in os.listdir(os.path.join(test_folder,"ir")):
 
             data_IR=image_read_cv2(os.path.join(test_folder,"ir",img_name),mode='GRAY')[np.newaxis,np.newaxis, ...]/255.0
-            # 改
             data_VIS = cv2.split(image_read_cv2(os.path.join(test_folder, "vi", img_name), mode='YCrCb'))[0][np.newaxis, np.newaxis, ...] / 255.0
-            # ycrcb, uint8
             data_VIS_BGR = cv2.imread(os.path.join(test_folder, "vi", img_name))
             _, data_VIS_Cr, data_VIS_Cb = cv2.split(cv2.cvtColor(data_VIS_BGR, cv2.COLOR_BGR2YCrCb))
-            # 改
 
             data_IR,data_VIS = torch.FloatTensor(data_IR),torch.FloatTensor(data_VIS)
             data_VIS, data_IR = data_VIS.cuda(), data_IR.cuda()
@@ -60,13 +55,10 @@ for dataset_name in ["MSRS","TNO","RoadScene"]:
             data_Fuse, _ = Decoder(data_VIS, feature_F_B, feature_F_D)
             data_Fuse=(data_Fuse-torch.min(data_Fuse))/(torch.max(data_Fuse)-torch.min(data_Fuse))
             fi = np.squeeze((data_Fuse * 255).cpu().numpy())
-            # 改
-            # float32 to uint8
             fi = fi.astype(np.uint8)
             ycrcb_fi = np.dstack((fi, data_VIS_Cr, data_VIS_Cb))
             rgb_fi = cv2.cvtColor(ycrcb_fi, cv2.COLOR_YCrCb2RGB)
             img_save(rgb_fi, img_name.split(sep='.')[0], test_out_folder)
-            # 改
 
     eval_folder=test_out_folder  
     ori_img_folder=test_folder
@@ -92,4 +84,4 @@ for dataset_name in ["MSRS","TNO","RoadScene"]:
             +str(np.round(metric_result[6], 2))+'\t'
             +str(np.round(metric_result[7], 2))
             )
-    print("="*80)
\ No newline at end of file
+    print("="*80)