README.md

---
license: cc0-1.0
size_categories:
- 100K<n<1M
task_categories:
- image-classification
pretty_name: ' PatchCamelyon (PCam)'
tags:
- medical
- biology
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': '0'
          '1': '1'
  splits:
  - name: train
    num_bytes: 1152417815.736
    num_examples: 262144
  - name: validation
    num_bytes: 146182832.56
    num_examples: 32768
  - name: test
    num_bytes: 141718983.176
    num_examples: 32768
  download_size: 1386391969
  dataset_size: 1440319631.4720001
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---
# PatchCamelyon (PCam)

This is a reupload of the PatchCamelyon (PCam) dataset in jpeg/csv format instead of H5 files. The original can be found on [Github](https://github.com/basveeling/pcam).

If you use this dataset, please cite the original paper:
```bibtex
@inproceedings{veeling2018rotation,
  title={Rotation Equivariant CNNs for Digital Pathology},
  author={Veeling, Bastiaan S and Linmans, Jasper and Winkens, Jim and Cohen, Taco and Welling, Max},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II 11},
  pages={210--218},
  year={2018},
  organization={Springer}
}
```