This repository is the official NTIRE 2024 implementation of Team GoodGame in Stereo Image Super-Resolution Challenge - Track 2 Constrained SR & Realistic Degradation. The restoration results of the testing images can be downloaded from here. Our pretrained models can be downloaded from here.
Installation environment
python 3.8
pytorch 1.11.0
cuda 11.3
git clone [email protected]:Yuqi-Miao/NTIRE_GoodGame_track2.git
cd NTIRE_GoodGame_track2
pip install -r requirements.txt
python setup.py develop --no_cuda_ext
Modify the configuration file options/train/CVHSSR_Sx4.yml and options/test/CVHSSR_Sx4.yml as follows:
Train
dataroot_gt: ./data/Flickr1024/trainx4 # replace your dataset path
dataroot_lq: ./data/Flickr1024/trainx4 # replace your dataset path
Test
dataroot_gt: ./data/Flickr1024/Stereo_test/KITTI2012/hr # replace your dataset path
dataroot_lq: ./data/Flickr1024/Stereo_test/KITTI2012/lr_x4 # replace your dataset path
python -m torch.distributed.launch --nproc_per_node=2 --master_port=4329 basicsr/train.py -opt options/train/CVHSSR_Sx4.yml --launcher pytorch
Modify the configuration file options/test/CVHSSR_Sx4.yml as follows:
pretrain_network_g: ../pretrain/besk_ckpt.pth # replace your model checkpoint path
Then you can infer
python basicsr/demo_ssr.py -opt options/test/CVHSSR_Sx4.yml --img_pair_paths ntire_test_stereo_image_path --output_dir output_image_path
python basicsr/models/archs/CVHSSR_arch.py
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