 Deep learning has revolutionised the field of digital pathology, allowing for faster and more accurate diagnoses of diseases. However, this technology is not without its challenges. Preparing images for deep learning models involves extensive pre- and post-processing, including artefact detection, colour normalisation, image subsampling and removing erroneous predictions. Additionally, the sheer size of the images can make them difficult to process, requiring them to be tiled and split up into multiple smaller files. This article was authored by Byron Smith, Mac Hulmson, Elizabeth Lesser, and others.