New Photo Model Training about waifu2x

[nagadomi]

I think resolution of image is not so important. For example, models/ukbench is trained on ukbench dataset. This dataset contains 640x480 images. In my benchmark, ukbench model's performance is very close to photo model's performance.
If you trying to train a denoising model, be careful of JPEG setting of dataset. chroma-subsampling=4:4:4 and quality>95 is may be required.

[djdjoko]

Thanks! How do you measure model performance?

If I understand correctly the feature set is more important then image size. Lets say we train a model_portrait for portraits (5000 images), one model_nature for nature (5000 images) and a model_portrait_nature (superset of 10000 images). Would model_portrait_nature have same/ better/ worse performance as the individual models?

Also would you expect e.g. model_portrait that is specificallyl trained on portraits to be significantly better in upscaling portraits compared to ukbench?

[nagadomi]

I used tools/benchmark.lua for benchmark. It shows PSNR and MSE. baseline is Bicubic.

$ th tools/benchmark.lua -model1_dir models/ukbench -model2_dir models/photo -method scale -dir  /path/to/benchmark/dataset
99/99; baseline_rmse=13.559323, model1_rmse=9.934793, model2_rmse=9.884656, baseline_psnr=26.851980, model1_psnr=30.009167, model2_psnr=30.056692 

At the very least, models/anime_style_art_rgb makes obviously different result from models/photo.