PART2/Restormer/Defocus_Deblurring/README.md

## Training

- To download DPDD training data, run
```

python download_data.py --data train

```

- Generate image patches from full-resolution training images, run
```

python generate_patches_dpdd.py 

```

- To train Restormer on **single-image** defocus deblurring task, run
```

cd Restormer

./train.sh Defocus_Deblurring/Options/DefocusDeblur_Single_8bit_Restormer.yml

```

- To train Restormer on **dual-pixel** defocus deblurring task, run
```

cd Restormer

./train.sh Defocus_Deblurring/Options/DefocusDeblur_DualPixel_16bit_Restormer.yml

```

**Note:** The above training scripts use 8 GPUs by default. To use any other number of GPUs, modify [Restormer/train.sh](../train.sh) and [DefocusDeblur_Single_8bit_Restormer.yml](Options/DefocusDeblur_Single_8bit_Restormer.yml) 


## Evaluation

- Download the pre-trained [models](https://drive.google.com/drive/folders/1bRBG8DG_72AGA6-eRePvChlT5ZO4cwJ4?usp=sharing) and place them in `./pretrained_models/`

- Download test dataset, run
```

python download_data.py --data test

```

- Testing on **single-image** defocus deblurring task, run
```

python test_single_image_defocus_deblur.py --save_images

```

- Testing on **dual-pixel** defocus deblurring task, run
```

python test_dual_pixel_defocus_deblur.py --save_images

```

The above testing scripts will reproduce image quality scores of Table 3 in the paper.