Update README.md

README.md

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 This repo contains the official implementation of the ACM MM 2024 paper
 
-### MFRGN: Multi-scale Feature Representation Generalization Network for Ground-to-Aerial Geo-localization
+## MFRGN: Multi-scale Feature Representation Generalization Network for Ground-to-Aerial Geo-localization
 
 <center>Yuntao Wang, Jinpu Zhang, Ruonan Wei, Wenbo Gao, Yuehuan Wang*</center>
 
@@ -14,15 +14,15 @@ This code is based on the [Sample4Geo](https://github.com/Skyy93/Sample4Geo) fra
 
 
 
-#### Dataset Preparation
+### Dataset Preparation
 
 To accelerate training/test time, you can run `data_preparation.py`， which  implements  image transformation (from '.jpg'/'.png' to '.pt') and cropping (similar to  [SAFA](https://github.com/shiyujiao/cross_view_localization_SAFA)). 
 
 When you process images from '.jpg'/'.png' to '.pt', you should set `ext='pt'` in `sample4geo/dataset/*.py`
 
 Also, if you are experiencing network errors about the backbone, you may need to download the backbone weights offline and put them into the `pretrained` folder.
 
-#### Results
+### Results
 
 We provide our pretrained results: [MFRGN-pretained.zip](https://pan.baidu.com/s/1LMYpQVHeV99u4u28jtlrjw) [BaiduYun, Password: 1234], which contains pretrained weight files or files necessary to train certain network configurations (e.g. distance_dict, convnext backbone weights).