Pytorch implementation of paper "Learned Image Downscaling for Upscaling using Content Adaptive Resampler"
# get CAR-pytorch source
git clone https://github.com/sunwj/CAR.git
cd CAR
# compile the code of the resampler
cd adaptive_gridsampler
python3 setup.py build_ext --inplace
Currently, the code only supports python3 and machine with NVIDIA GPU (and the CUDA development toolkit) installed
- numpy
- scipy
- pytorch (== 1.3.1)
- Pillow
- tqdm
You can download the pre-trained models for 2x and 4x downscaling and super-resolution from here.
python3 run.py --scale 4 --img_dir path_to_images --model_dir path_to_pretrained_models \
--output_dir path_to_output
You can download HR images of benchmark datasets, i.e., the Set5, Set14, B100 and Urban100 from here.
If you find our work useful in your research or publication, please cite our work:
Wanjie Sun, Zhenzhong Chen. "Learned Image Downscaling for Upscaling using Content Adaptive Resampler". arXiv preprint arXiv:1907.12904, 2019.
@misc{1907.12904,
Author = {Wanjie Sun and Zhenzhong Chen},
Title = {Learned Image Downscaling for Upscaling using Content Adaptive Resampler},
Year = {2019},
Eprint = {arXiv:1907.12904}
}
EDSR code is provided by thstkdgus35/EDSR-PyTorch.