Contents

1. Installation
2. Datasets
3. Models
4. Training
5. Testing
6. Results
7. Citation
8. Acknowledgements

Installation

• Python 3.9
• PyTorch 1.9.0
• NVIDIA GPU + CUDA

cd HI-Diff
conda create -n hi_diff python=3.9
conda activate hi_diff
pip install -r requirements.txt

Installation

按照train_test_val_split.py划分数据集，确保同一仿体不会同时出现在训练集和测试集中，避免数据泄露

Training

Stage-1 (S1)

python train.py -opt options/train/Simu_S1.yml

Stage-2 (S2)

python train.py -opt options/train/Simu_S2.yml

• 训练结果在 in experiments/.

Testing

• 测试的配置在 options/test/RealData.yml中，根据第84行指定的目录配置放置训练好的模型.

  python test.py -opt options/test/RealData.yml

• The output is in results/.

Results

To do

Citation

If you find the code helpful in your resarch or work, please cite the following paper(s).

@inproceedings{chen2023hierarchical,
  title={Hierarchical Integration Diffusion Model for Realistic Image Deblurring}, 
  author={Chen, Zheng and Zhang, Yulun and Ding, Liu and Bin, Xia and Gu, Jinjin and Kong, Linghe and Yuan, Xin},
  booktitle={NeurIPS},
  year={2023}
}

Acknowledgements

This code is built on BasicSR, Restormer, and DiffIR.