Data guide

GAN-Engine welcomes datasets from medical scanners, satellites, drones, microscopes, and consumer cameras. The goal is to define how low-resolution (LR) inputs and high-resolution (HR) references are paired, normalised, and sampled without editing code. This guide explains the dataset abstractions, built-in loaders, and ways to extend them.

The datasets are not implemented here, taking care of the data is your task. What you need to provide are Pytorch-Dataloaders in order to make the interface with the model work.