DAN-Basd-on-Openmmlab
DAN: Unfolding the Alternating Optimization for Blind Super Resolution
We reproduce DAN via mmediting based on open-sourced code.
Requirements
- PyTorch >= 1.3
- mmediting >= 0.9
DataSets
We use DIV2K and Flickr2K as our training datasets. For evaluation of Setting 2, we use DIV2KRK datasets,
Usages
How to run this repo: copy the file to the mmediting workspace and run the program directly based on the commands in mmediting
- Copy files to MMEditing workspace.
cd DAN-Basd-on-Openmmlab/
mv ./mmedit/models/restorers/dan.py ${mmediting_workspace}/mmedit/models/restorers/
mv ./mmedit/models/backbones/sr_backbones/dan_net.py ${mmediting_workspace}/mmedit/models/backbones/sr_backbones/
mv ./mmedit/models/common/DANpreprocess.py ${mmediting_workspace}/mmedit/models/common
mv ./configs/restorers/dan ${mmediting_workspace}/configs/restorers/
mv ./tools/data/super-resolution/dan_datasets ${mmediting_workspace}/tools/data/super-resolution/
- Modify the configuration file as follows:
pca_matrix_path='${mmediting_workspace}/tools/data/super-resolution/div2k/pca_matrix/pca_aniso_matrix_x4.pth' # your pca_matrix path
# Training
gt_folder='${dataset_workspace}/dataset/DF2K_train_HR_sub' # your train data path
# Testing
lq_folder='${dataset_workspace}/dataset/DIV2KRK/lr_x4' # your test data LR path
gt_folder='${dataset_workspace}/dataset/DIV2KRK/gt' # your test data HR path
- Add script to init file, as follows:
- modify the
mmedit/models/backbones/sr_backbones/__init__.py:
from .dan_net import DAN
# add DAN into __all__ list.
- modify the
mmedit/models/commons/__init__.py:
from .dan_preprocess import SRMDPreprocessing
# add SRMDreprocessing into __all__ list.
- modify the
mmedit/models/restorers/__init__.py:
from .dan import DAN
# add DAN into __all__ list.
- Training/Test
Before using it, please download and process the dataset and set the path in the configuration file.
- Train
# Single GPU
python tools/train.py configs/restorers/dan/dan_setting2.py --work_dir ${YOUR_WORK_DIR}
# Multiple GPUs
./tools/dist_train.sh configs/restorers/dan/dan_setting2.py ${GPU_NUM} --work_dir ${YOUR_WORK_DIR}
- Test
# Single GPU
python tools/test.py configs/restorers/dan/dan_setting2.py ${CHECKPOINT_FILE} [--metrics ${METRICS}] [--out ${RESULT_FILE}]
# Multiple GPUs
./tools/dist_test.sh configs/restorers/dan/dan_setting2.py ${CHECKPOINT_FILE} ${GPU_NUM} [--metrics ${METRICS}] [--out ${RESULT_FILE}]
Result
DIV2KRK
The passwds of download links are all 'ta2o'
| Method | scale | Datasets | PSNR | Download |
|---|---|---|---|---|
| DAN | x4 | DIV2KRK | 27.41 | model / test_pkl |
4 Aug 03, 2022
182 Dec 29, 2022
578 Dec 30, 2022
263 Jan 07, 2023
226 Jan 05, 2023
273 Jan 03, 2023
24 Dec 28, 2022
253 Dec 21, 2022
42 Nov 16, 2022
255 Nov 23, 2022
435 Dec 30, 2022
242 Dec 20, 2022
0 Feb 07, 2022
10 Nov 30, 2022
10 Nov 02, 2022
2.3k Jan 09, 2023
25 Oct 14, 2022
115 Jan 02, 2023
226 Dec 29, 2022
247 Dec 16, 2022