Code for TIP 2021 paper: Real-Time Deep Image Retouching Based on Learnt Semantics Dependent Global Transforms
- Python 3 (Recommend to use Anaconda)
- PyTorch >= 1.0
- NVIDIA GPU + CUDA
- Python packages:
pip install numpy opencv-python lmdb pyyaml
- TensorBoard:
- PyTorch >= 1.1:
pip install tb-nightly future
- PyTorch == 1.0:
pip install tensorboardX
- PyTorch >= 1.1:
We also recommand to use the preprocessed datasets MIT-Adobe FiveK preprocessed dataset (kindly shared by Jingwen He, author of CSRNet)
- Modify the configuration file
options/test/test_Meta_Y_UV_Para.json
. - Run command:
python test.py -opt options/test/test_Meta_Y_UV_Para.json
- This code is based on mmsr.
@article{gao2021real,
title={Real-time deep image retouching based on learnt semantics dependent global transforms},
author={Gao, Qifan and Wu, Xiaolin},
journal={IEEE Transactions on Image Processing},
volume={30},
pages={7378--7390},
year={2021},
publisher={IEEE}
}