README.md

Train

Prepare training data in data/train directory as below:

  data
  └── train
      ├── video_1
            ├── hr
                    ├── hr0.png
                    ├── ...
                    └── hr30.png
            └── lr_x4_BI
                    ├── lr0.png
                    ├── ...
                    └── lr30.png
      ├── ...
      └── video_N

• Run on CPU:

python train.py --upscale_factor 4 --patch_size 32 --batch_size 16 --n_iters 300000

• Run on GPU:

python train.py --upscale_factor 4 --patch_size 32 --batch_size 16 --n_iters 300000 --gpu_mode True

Test

We provide the pretrained model for 4x SR on BI degradation model. Note that we made some modifications to the original code and it should produce comparable or even better results.

• Run on CPU:

python demo_Vid4.py --video_name calendar --upscale_factor 4

• Run on GPU:

python demo_Vid4.py --video_name calendar --upscale_factor 4 --gpu_mode True

• Run on GPU (memory efficient):

python demo_Vid4.py --video_name calendar --upscale_factor 4 --gpu_mode True --chop_forward True

You can download Vid4 dataset and unzip in data/test directory. Then you can test our network on other scenes.