diff --git a/README.md b/README.md
index 0120d62..6ac8753 100644
--- a/README.md
+++ b/README.md
@@ -2,8 +2,6 @@
 
 The code for our CVPR paper [PISE: Person Image Synthesis and Editing with Decoupled GAN](https://arxiv.org/abs/2103.04023)
 
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 # Requirement
 
 ```
@@ -12,8 +10,6 @@ conda install pytorch=1.2 cudatoolkit=10.0 torchvision
 pip install scikit-image pillow pandas tqdm dominate natsort 
 ```
 
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 # Data
 
 Data preparation for images and keypoints can follow [Pose Transfer](https://github.com/tengteng95/Pose-Transfer)
@@ -28,7 +24,7 @@ Parsing data can be found from [baidu](https://pan.baidu.com/s/19boQPJnrq2wASSMq
 ```
 python train.py --name=fashion --model=painet --gpu_ids=0
 ```
-Note that if you want to train a pose transfer model as well as texture transfer and region editing, just comments the line 177 and 178, and uncomments line 162-176.  
+**Note that if you want to train a pose transfer model as well as texture transfer and region editing, just comments the line 177 and 178, and uncomments line 162-176. ** 
 
 
 # Test
@@ -36,7 +32,7 @@ Note that if you want to train a pose transfer model as well as texture transfer
 You can directly download our test results from [baidu](https://pan.baidu.com/s/16HiFP6hExXVSzbs9A_Bhbw) (fetch code: abcd) or [Google drive](https://drive.google.com/file/d/1u62gyQ46_qZGB6BlESpk0WLjcZ-NH8-F/view?usp=sharing). <br>
 Pre-trained checkpoint of human pose transfer reported in our paper can be found from [baidu](https://pan.baidu.com/s/14v3LaCCGCHJUoqQ_wlyNpA) (fetch code: abcd) or [Google drive](https://drive.google.com/file/d/1gcdzahJ-pE-bSQfcnrW__iXIViH_y-FB/view?usp=sharing) and put it in the folder (-->results-->fashion). 
 
-Pre-Trained checkpoint of texture transfe, region editing, style interpolation used in our paper can be found from [baidu](https://pan.baidu.com/s/1E025k57INvL0O8cdLi87og) or [Google drive](). Note that the model need to be changed.
+Pre-Trained checkpoint of texture transfe, region editing, style interpolation used in our paper can be found from [baidu](https://pan.baidu.com/s/1E025k57INvL0O8cdLi87og)(fetch code: abcd) or [Google drive](). Note that the model need to be changed.
 
 **Test by yourself** <br>
 
@@ -46,8 +42,6 @@ python test.py --name=fashion --model=painet --gpu_ids=0
 ```
 
 
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 # Citation
 
 If you use this code, please cite our paper.