--- license: cc-by-4.0 tags: - super-resolution pretty_name: DF2K_BHI size_categories: - 1K= 0.2 IC9600 >= 0.4 Which results in this DF2K_BHI dataset with 12'639 512x512 training tiles. ## Visualization Here is a visual example of the first few tiles that are in the dataset:
Visual example - first few tiles of the DF2K_BHI Dataset
## Training As can be seen in the following training validation tensorboard graphs (DIV2K validation dataset), this BHI-filtered version of the DF2K dataset is able to achieve higher or similiar metric scores while seeing a reduction of -40.9% in training tiles quantity. Here is the training validation metrics on the DIV2K validation dataset, using the plksr_tiny architecture option, in comparison to the tiled full DF2K dataset: Tiled DF2K dataset (here called X): 21'387 tiles DF2K_BHI dataset: 12'639 tiles
Tensorboard: SSIM validation scores of DF2K and DF2K_BHI
Tensorboard: PSNR validation scores of DF2K and DF2K_BHI
Tensorboard: DISTS validation scores of DF2K and DF2K_BHI