- Install yacs:
conda install -c conda-forge yacs
- Install natsort:
pip install natsort
- Install skimage:
pip install scikit-image
- Install tqdm:
pip install tqdm
- Install cv2:
conda install -c conda-forge opencv
- Install warmup scheduler
cd pytorch-gradual-warmup-lr; python setup.py install; cd ..
TBD
- Carefully modify
training.yml
and then run:
python3 train.py
-
Download images of validation set and place them in
datasets/VP9BandingDataset/val/
-
Run:
python test.py --input_dir datasets/ --model_file "UNet.py" --model_variant "UNet-32" --result_dir results/test_figure5_AdaDeband_UNet/ --dataset FFMPEG --weights checkpoints/Debanding/models/UNet32_epochs300_l1loss_train256x256/model_latest.pth --gpus='0,1' --crop_size=0
This code is based on MPRNet