Update README.md

README.md

@@ -3,10 +3,10 @@ tags:
 - HiT-SR
 - image super-resolution
 - transformer
+- efficient transformer
 ---
-
 <h1>
- HiT-SR: Hierarchical Transformer <br> for Efficient Image Super-Resolution
+ HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution
  </h1>
 
 <h3><a href="https://github.com/XiangZ-0/HiT-SR">[Github]</a> | <a href="https://1drv.ms/b/c/de821e161e64ce08/EVsrOr1-PFFMsXxiRHEmKeoBSH6DPkTuN2GRmEYsl9bvDQ?e=f9wGUO">[Paper]</a> | <a href="https://1drv.ms/b/c/de821e161e64ce08/EYmRy-QOjPdFsMRT_ElKQqABYzoIIfDtkt9hofZ5YY_GjQ?e=2Iapqf">[Supp]</a> | <a href="https://www.youtube.com/watch?v=9rO0pjmmjZg">[Video]</a> | <a href="https://1drv.ms/f/c/de821e161e64ce08/EuE6xW-sN-hFgkIa6J-Y8gkB9b4vDQZQ01r1ZP1lmzM0vQ?e=aIRfCQ">[Visual Results]</a> </h3>
@@ -14,65 +14,6 @@ tags:
 
 HiT-SR is a general strategy to improve transformer-based SR methods. We apply our HiT-SR approach to improve [SwinIR-Light](https://github.com/JingyunLiang/SwinIR), [SwinIR-NG](https://github.com/rami0205/NGramSwin) and [SRFormer-Light](https://github.com/HVision-NKU/SRFormer), corresponding to our HiT-SIR, HiT-SNG, and HiT-SRF. Compared with the original structure, our improved models achieve better SR performance while reducing computational burdens.
 
-## 🚀 Models
-For each HiT-SR model, we provide 2x, 3x, 4x upscaling versions:
-| Repo Name         |   | Model   |   | Upscale |
-|-------------------|---|---------|---|---------|
-| `XiangZ/hit-sir-2x` |   | HiT-SIR |   | 2x      |
-| `XiangZ/hit-sir-3x` |   | HiT-SIR |   | 3x      |
-| `XiangZ/hit-sir-4x` |   | HiT-SIR |   | 4x      |
-| `XiangZ/hit-sng-2x` |   | HiT-SNG |   | 2x      |
-| `XiangZ/hit-sng-3x` |   | HiT-SNG |   | 3x      |
-| `XiangZ/hit-sng-4x` |   | HiT-SNG |   | 4x      |
-| `XiangZ/hit-srf-2x` |   | HiT-SNG |   | 2x      |
-| `XiangZ/hit-srf-3x` |   | HiT-SRF |   | 3x      |
-| `XiangZ/hit-srf-4x` |   | HiT-SRF |   | 4x      |
-
-
-## 🛠️ Setup
-Install the dependencies under the working directory (use hit-srf-4x as an example):
-```
-git clone https://huggingface.co/XiangZ/hit-srf-4x
-cd hit-srf-4x
-pip install -r requirements.txt
-```
-
-## 🚀 Usage
-
-To test the model:
-```
-from hit_sir_arch import HiT_SIR
-from hit_sng_arch import HiT_SNG
-from hit_srf_arch import HiT_SRF
-import cv2
-
-# use GPU (True) or CPU (False)
-cuda_flag = True
-
-# initialize model (change model and upscale according to your setting)
-model = HiT_SRF(upscale=4) 
-
-# load model (change repo_name according to your setting)
-repo_name = "XiangZ/hit-srf-4x"
-model = model.from_pretrained(repo_name)
-if cuda_flag:
-    model.cuda()
-
-## test and save results
-image_path = "path-to-input-image"
-sr_results = model.infer_image(image_path, cuda=cuda_flag)
-cv2.imwrite("path-to-output-location", sr_results)
-```
-
-## 📎 Citation
 
-If you find the code helpful in your research or work, please consider citing the following paper.
+🤗 Please refer to https://huggingface.co/XiangZ/hit-sr for usage.
 
-```
-@inproceedings{zhang2024hitsr,
-    title={HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution},
-    author={Zhang, Xiang and Zhang, Yulun and Yu, Fisher},
-    booktitle={ECCV},
-    year={2024}
-}
-```