Update README.md

README.md

@@ -4,22 +4,8 @@ Official code for CVPR 2021 paper 'Parser-Free Virtual Try-on via Distilling App
 ![image](https://github.com/geyuying/PF-AFN/blob/main/show/compare.jpg?raw=true)
 
 [[Checkpoints]](https://drive.google.com/file/d/1_a0AiN8Y_d_9TNDhHIcRlERz3zptyYWV/view?usp=sharing)
-## Installation
-conda create -n tryon python=3.6
-
-source activate tryon     or     conda activate tryon
-
-conda install pytorch=1.1.0 torchvision=0.3.0 cudatoolkit=9.0 -c pytorch
-
-conda install cupy     or     pip install cupy==6.0.0
-
-pip install opencv-python
-
-git clone [email protected]:geyuying/PF-AFN.git
-
-cd PF-AFN
 
-## Our Test Envirenment
+## Our Envirenment
 anaconda3
 
 pytorch 1.1.0
@@ -36,10 +22,24 @@ opencv-python 4.5.1
 
 python 3.6
 
-**In oder to test the model with our checkpoints, please make sure that your environment is the same as our test envirenment**.
+## Installation
+conda create -n tryon python=3.6
+
+source activate tryon     or     conda activate tryon
+
+conda install pytorch=1.1.0 torchvision=0.3.0 cudatoolkit=9.0 -c pytorch
+
+conda install cupy     or     pip install cupy==6.0.0
+
+pip install opencv-python
+
+git clone https://github.com/geyuying/PF-AFN.git
+
+cd PF-AFN
 
 ## Test With the Models
 1. First, you need to download the checkpoints from [google drive](https://drive.google.com/file/d/1_a0AiN8Y_d_9TNDhHIcRlERz3zptyYWV/view?usp=sharing) and put the models under the folder "checkpoints/PFAFN". 
 2. The "dataset" folder contains the images for test, and 'demo.txt' records the test pairs.
 3. To test with the models, run **test.sh** and the results will be saved in the folder "results".
 4. To reproduce our results from the saved model, your test environment should be the same as our test environment. 
+5. **In oder to test the model with our checkpoints, please make sure that your environment is the same as our test envirenment**.