| ## Training | |
| 1. To download Rain13K training and testing data, run | |
| ``` | |
| python download_data.py --data train-test | |
| ``` | |
| 2. To train Restormer with default settings, run | |
| ``` | |
| cd Restormer | |
| ./train.sh Deraining/Options/Deraining_Restormer.yml | |
| ``` | |
| **Note:** The above training script uses 8 GPUs by default. To use any other number of GPUs, modify [Restormer/train.sh](../train.sh) and [Deraining/Options/Deraining_Restormer.yml](Options/Deraining_Restormer.yml) | |
| ## Evaluation | |
| 1. Download the pre-trained [model](https://drive.google.com/drive/folders/1ZEDDEVW0UgkpWi-N4Lj_JUoVChGXCu_u?usp=sharing) and place it in `./pretrained_models/` | |
| 2. Download test datasets (Test100, Rain100H, Rain100L, Test1200, Test2800), run | |
| ``` | |
| python download_data.py --data test | |
| ``` | |
| 3. Testing | |
| ``` | |
| python test.py | |
| ``` | |
| #### To reproduce PSNR/SSIM scores of Table 1, run | |
| ``` | |
| evaluate_PSNR_SSIM.m | |
| ``` | |