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# Stripformer: Strip Transformer for Fast Image Deblurring (ECCV 2022 Oral)
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Pytorch Implementation of "[Stripformer: Strip Transformer for Fast Image Deblurring](https://arxiv.org/abs/2204.04627)"
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# Stripformer (ECCV 2022)
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Pytorch Implementation of "[Stripformer: Strip Transformer for Fast Image Deblurring](https://arxiv.org/abs/2204.04627)" (ECCV 2022 Oral)
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<img src="./Figure/Intra_Inter.PNG" width = "800" height = "200" div align=center />
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@@ -19,41 +19,41 @@ pip install albumentations==1.1.0
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## Training
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Download "[GoPro](https://drive.google.com/drive/folders/1BdV2l7A5MRXLWszGonMxR88eV27geb_n?usp=sharing)" dataset into './datasets' </br>
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For example: './datasets/GoPro/train/blur/\*\*/\*.png'
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For example: './datasets/GoPro'
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**We train our Stripformer in two stages:** </br>
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* We pre-train Stripformer for 3000 epochs with patch size 256x256 </br>
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* Run the following commands
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* Run the following command
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```
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python train_Stripformer_pretrained.py
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```
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* After 3000 epochs, we keep training Stripformer for 1000 epochs with patch size 512x512 </br>
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* Run the following commands
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* Run the following command
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```
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python train_Stripformer_gopro.py
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```
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## Testing
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For reproducing our results on GoPro and HIDE dataset, download the "[Stripformer_gopro.pth](https://drive.google.com/drive/folders/1YcIwqlgWQw_dhy_h0fqZlnKGptq1eVjZ?usp=sharing)"
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For reproducing our results on GoPro and HIDE datasets, download "[Stripformer_gopro.pth](https://drive.google.com/drive/folders/1YcIwqlgWQw_dhy_h0fqZlnKGptq1eVjZ?usp=sharing)"
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For reproducing our results on RealBlur dataset, download "[Stripformer_realblur_J.pth](https://drive.google.com/drive/folders/1YcIwqlgWQw_dhy_h0fqZlnKGptq1eVjZ?usp=sharing)" and "[Stripformer_realblur_R.pth](https://drive.google.com/drive/folders/1YcIwqlgWQw_dhy_h0fqZlnKGptq1eVjZ?usp=sharing)"
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**For testing on GoPro dataset** </br>
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* Download "[GoPro](https://drive.google.com/drive/folders/1BdV2l7A5MRXLWszGonMxR88eV27geb_n?usp=sharing)" full dataset or test set into './datasets' (For example: './datasets/GoPro/test/blur/\*\*/\*.png') </br>
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* Run the following commands
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* Download "[GoPro](https://drive.google.com/drive/folders/1BdV2l7A5MRXLWszGonMxR88eV27geb_n?usp=sharing)" full dataset or test set into './datasets' (For example: './datasets/GoPro/test') </br>
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* Run the following command
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```
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python predict_GoPro_test_results.py --weights_path ./Stripformer_gopro.pth
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```
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**For testing on HIDE dataset** </br>
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* Download "[HIDE](https://drive.google.com/drive/folders/1BdV2l7A5MRXLWszGonMxR88eV27geb_n?usp=sharing)" into './datasets' </br>
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* Run the following commands
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* Run the following command
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```
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python predict_HIDE_results.py --weights_path ./Stripformer_gopro.pth
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```
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**For testing on RealBlur test sets** </br>
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* Download "[RealBlur_J](https://drive.google.com/drive/folders/1BdV2l7A5MRXLWszGonMxR88eV27geb_n?usp=sharing)" and "[RealBlur_R](https://drive.google.com/drive/folders/1BdV2l7A5MRXLWszGonMxR88eV27geb_n?usp=sharing)" into './datasets' </br>
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* Run the following commands
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* Run the following command
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```
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python predict_RealBlur_J_test_results.py --weights_path ./Stripformer_realblur_J.pth
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```
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@@ -82,3 +82,12 @@ python evaluate_RealBlur_J.py
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```
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python evaluate_RealBlur_R.py
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```
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## Citation
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```
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@inproceedings{Tsai2022Stripformer,
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author = {Fu-Jen Tsai and Yan-Tsung Peng and Yen-Yu Lin and Chung-Chi Tsai and Chia-Wen Lin},
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title = {Stripformer: Strip Transformer for Fast Image Deblurring},
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booktitle = {ECCV},
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year = {2022}
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}
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```
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Copyright (c) 2022 Fu-Jen Tsai
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software with non-commercial usage, including non-commercial usage
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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--------------------------- LICENSE FOR DeblurGANv2 --------------------------------
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BSD License
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For DeblurGANv2 software
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Copyright (c) 2019, Orest Kupyn, Tetiana Martyniuk, Junru Wu and Zhangyang Wang
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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