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license: cc-by-nc-sa-4.0
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# CAMELYON16 patch embeddings made with UNI

This repository contains patch embeddings for CAMELYON16 made with the UNI foundation model.

Patches are 128x128 micrometers. Tissue segmentation and patching was done with a modified version of the CLAM toolkit.
The toolkit was modified to extract constant physical size patches.

The `patches` directory contains HDF5 files with patch coordinates. The attribute `patch_size` on the `/coords` dataset
contains the patch size in pixels. This is equivalent to the physical size of 128 micrometers.

The `embeddings` directory contains PyTorch files with embeddings. Each specimen in CAMELYON16 is in a separate file,
and each file contains a 2D tensor of shape `(n_patches, n_features)`. The value of `n_patches` can differ across specimens.

The order of the patches is the same between the patch HDF5 file and the features PyTorch file.

# Intended use cases

This dataset is intended for training weakly-supervised neural networks on CAMELYON16. 
It is also intended to help others reproduce the experiments in the HIPPO manuscript.

# Links

- CAMELYON16: https://camelyon16.grand-challenge.org/
- CLAM: https://github.com/mahmoodlab/CLAM