Note: waifu2x's photo models was trained on kou's photo collection.
Note: PSNR in this benchmark uses a MATLAB's rgb2ycbcr compatible function (dynamic range [16 235], not [0 255]) for converting grayscale image. I think it's not correct PSNR. But many paper used this metric.
command:
th tools/benchmark.lua -dir <dataset_dir> -model1_dir <model_dir> -method scale -filter Catrom -color y -range_bug 1 -tta <0|1> -force_cudnn 1
BSD100: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/segbench/ (100 test images in BSDS300) Urban100: https://github.com/jbhuang0604/SelfExSR
| Dataset/Model | Bicubic | vgg_7/photo | upconv_7/photo | upconv_7l/photo | |---------------|---------------|---------------|------------------|------------------| | BSD100 | 29.558 | 31.427 | 31.640 | 31.749 | | Urban100 | 26.852 | 30.057 | 30.477 | 30.759 |
Note: TTA is an ensemble technique that is supported by waifu2x. TTA method is 8x slower than non TTA method but it improves PSNR (~+0.1 on photo, ~+0.4 on art).
| Dataset/Model | Bicubic | vgg_7/photo | upconv_7/photo | upconv_7l/photo | |---------------|---------------|---------------|------------------|------------------| | BSD100 | 29.558 | 31.474 | 31.705 | 31.812 | | Urban100 | 26.852 | 30.140 | 30.599 | 30.868 |
| Dataset/Model | vgg_7/photo | upconv_7/photo | upconv_7l/photo | |---------------|---------------|------------------|------------------| | BSD100 | 4.057 | 2.509 | 4.947 | | Urban100 | 16.349 | 7.083 | 14.178 |
| Dataset/Model | vgg_7/photo | upconv_7/photo | upconv_7l/photo | |---------------|---------------|------------------|------------------| | BSD100 | 36.611 | 20.219 | 42.486 | | Urban100 | 132.416 | 65.125 | 129.916 |
command:
th tools/benchmark.lua -dir <dataset_dir> -model1_dir <model_dir> -method scale -filter Lanczos -color y -range_bug 1 -tta <0|1> -force_cudnn 1
art_test: This dataset contains 85 various fan-arts. Sorry, This dataset is private.
| Dataset/Model | Bicubic | vgg_7/art | upconv_7/art | upconv_7l/art | |---------------|---------------|-------------|----------------|----------------| | art_test | 31.022 | 37.495 | 38.330 | 39.140 |
| Dataset/Model | Bicubic | vgg_7/art | upconv_7/art | upconv_7l/art | |---------------|---------------|-------------|----------------|----------------| | art_test | 31.022 | 37.777 | 38.677 | 39.510 |
| Dataset/Model | vgg_7/art | upconv_7/art | upconv_7l/art | |---------------|-------------|----------------|----------------| | art_test | 20.681 | 7.683 | 17.667 |
| Dataset/Model | vgg_7/art | upconv_7/art | upconv_7l/art | |---------------|-------------|----------------|----------------| | art_test | 174.674 | 77.716 | 163.932 |