Update README.md

README.md

@@ -12,6 +12,7 @@ The Pytorch implementation of _Learning from Future: A Novel Self-Training Frame
 <img width="1046" alt="image" src="https://user-images.githubusercontent.com/83934424/190574312-20421c04-1aa5-48a9-ac63-afffaeb83bce.png">
 
 
+
 ## Preparation
 
 ### Envs
@@ -40,8 +41,8 @@ Prepare datasets follow the instructions below:
 
 <details>
   <summary>For Cityscapes</summary>
-For UDA, download leftImg8bit_trainvaltest.zip and gt_trainvaltest.zip from [here](https://www.cityscapes-dataset.com/downloads/) and extract them to `data/cityscapes`.
-For SSL, Next, unzip the files to folder ```data``` and make the dictionary structures as follows:
+  For UDA, download leftImg8bit_trainvaltest.zip and gt_trainvaltest.zip from [here](https://www.cityscapes-dataset.com/downloads/) and extract them to `data/cityscapes`.
+  For SSL, Next, unzip the files to folder ```data``` and make the dictionary structures as follows:
   ```angular2html
   data/cityscapes
   ├── gtFine
@@ -53,53 +54,53 @@ For SSL, Next, unzip the files to folder ```data``` and make the dictionary stru
       ├── train
       └── val
   ```
-<\details>  
+</details>
 
-<details>
+  <details>
   <summary>For GTA5</summary>
-Download all image and label packages from [here](https://download.visinf.tu-darmstadt.de/data/from_games/) and extract them to `data/gta`. The UDA data folder structure should look like this:
-<\details>
+  Download all image and label packages from [here](https://download.visinf.tu-darmstadt.de/data/from_games/) and extract them to `data/gta`.
+</details>
 
 <details>
   <summary>For SYNTHIA</summary>
 Download SYNTHIA-RAND-CITYSCAPES from [here](http://synthia-dataset.net/downloads/) and extract it to `data/synthia`.
-```none
-.
-├── ...
-├── data
-│   ├── cityscapes
-│   │   ├── leftImg8bit
-│   │   │   ├── train
-│   │   │   ├── val
-│   │   ├── gtFine
-│   │   │   ├── train
-│   │   │   ├── val
-│   ├── gta
-│   │   ├── images
-│   │   ├── labels
-│   ├── synthia (optional)
-│   │   ├── RGB
-│   │   ├── GT
-│   │   │   ├── LABELS
-├── ...
-```
-<\details>
+The UDA data folder structure should look like this:
+  ```angular2html
+  .
+  ├── ...
+  ├── data
+  │   ├── cityscapes
+  │   │   ├── leftImg8bit
+  │   │   │   ├── train
+  │   │   │   ├── val
+  │   │   ├── gtFine
+  │   │   │   ├── train
+  │   │   │   ├── val
+  │   ├── gta
+  │   │   ├── images
+  │   │   ├── labels
+  │   ├── synthia (optional)
+  │   │   ├── RGB
+  │   │   ├── GT
+  │   │   │   ├── LABELS
+  ├── ...
+  ```
+</details>
 
-
 <details>
   <summary>For VOC 2012</summary>
 Refer to [this link](https://github.com/zhixuanli/segmentation-paper-reading-notes/blob/master/others/Summary of the semantic segmentation datasets.md) and download `PASCAL VOC 2012 augmented with SBD` dataset.
 Then unzip the files to folder ```data``` and make the dictionary structures as follows:
-```angular2html
-data/VOC2012
-├── Annotations
-├── ImageSets
-├── JPEGImages
-├── SegmentationClass
-├── SegmentationClassAug
-└── SegmentationObject
-```
-<\details>
+  ```angular2html
+  data/VOC2012
+  ├── Annotations
+  ├── ImageSets
+  ├── JPEGImages
+  ├── SegmentationClass
+  ├── SegmentationClassAug
+  └── SegmentationObject
+  ```
+</details>