megcup-feedback
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RAW-based blind denoising, 1st place in MegCup 2022 (Team Feedback)
MegCup 2022 Team Feedback
This repository is the 1st place solution (Team Feedback) in 2022 MegCup RAW image denoising. Here is the 3rd place solution, FeedBack-based Restormer.
Members
- Ling-Hao Han
- Zuo-Liang Zhu
- Weilei Wen
- Adviser : Chunle Guo
Overview
Click for more illustration
Environment
git clone https://github.com/hlh981029/megcup-feedback.git
cd megcup-feedback
conda env create -f environment.yaml
conda activate feedback
Dataset
Please download the dataset to ./data
,
and refer to options/feedback.yaml
to modify the data path.
|--data
|--competition_train_input.0.2.bin
|--competition_train_gt.0.2.bin
|--competition_test_input.0.2.bin
Evaluation
# evaluate on dataset
# log and config file will be saved to ./output/feedback
python test.py
# generate result bin file
# result will be saved to ./output/feedback/submit/model_best_result.bin
python test.py --submit
Acknowledgement
This project is based on Global2Local, Swin-Transformer, Restormer, and BasicSR.