Code for the paper: "Troublemaker Learning for Low-Light Image Enhancement"
torch == 1.7.1
torchvision == 0.8.2
timm == 0.6.13
We use python 3.7. Higher version is possible, but ensure that the above environment dependency versions match. For example, a higher version of timm may require a higher version of python.
We provide pretrained Predicting Model (PM) and Enhancing Model (EM) weights (i.e. Pred.pth.tar and Enhance.pth.tar). You can download here.
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Download the pretrained PM and EM model parameters (i.e. Pred.pth.tar and Enhance.pth.tar) and place them in the ckpt folder.
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Put some low-light images in the test folder and run:
python evaluate.py --save_dir ./output/ --resume-Pred ./ckpt/Pred.pth.tar --resume-Enhance ./ckpt/Enhance.pth.tar ./test/
The results will be saved in the output folder.