Code adapted from [Camelyon17] (https://github.com/Camelyon17/camelyon17)

• torch
• torchvision
• openslide
• opencv
• matplotlib

• First download the label data lesion_annotations.zip, unzip it, and you will find the label data lesion_annotations/patient###_node_#.xml (where each # represents a digit) for the image data files centre_#/patient###_node_#.tif you will download.
• From folders centre_0 ... centre_4, only download the patient###.zip files that have label files in the above folder lesion_annotations, since otherwise you will to download a much larger number of hugh image data files that cannot be used in training due to lacking of labels.

• python3 unzip_sh.py > unzip_all.sh
• chmod +x unzip_all.sh
• mkdir tif
• ./unzip_all.sh

• python3 make_patch.py

• python3 get_thumbnail.py

• python3 make_manifest.py

• python3 train.py --train_epoch=10

• python3 main.py