Added references

README.md

@@ -87,7 +87,8 @@ For problems and questions not fit for a github issue, please email [Bas Veeling
 ## Citing PCam
 If you use PCam in a scientific publication, we would appreciate references to the following paper:
 
-**[1] <TODO> [arXiv:<todo>](http://arxiv.org/abs/<todo>)**
+
+**[1] B. S. Veeling, J. Linmans, J. Winkens, T. Cohen, M. Welling. "Rotation Equivariant CNNs for Digital Pathology". [arXiv:1806.03962](http://arxiv.org/abs/1806.03962)**
 
 A citation of the original Camelyon16 dataset paper is appreciated as well:
 
@@ -96,7 +97,16 @@ A citation of the original Camelyon16 dataset paper is appreciated as well:
 
 Biblatex entry:
 ```latex
-Coming...
+@ARTICLE{Veeling2018-qh,
+  title         = "Rotation Equivariant {CNNs} for Digital Pathology",
+  author        = "Veeling, Bastiaan S and Linmans, Jasper and Winkens, Jim and
+                   Cohen, Taco and Welling, Max",
+  month         =  jun,
+  year          =  2018,
+  archivePrefix = "arXiv",
+  primaryClass  = "cs.CV",
+  eprint        = "1806.03962"
+}
 ```
 
 <!-- [Who is citing PCam?](https://scholar.google.de/scholar?hl=en&as_sdt=0%2C5&q=pcam&btnG=&oq=fas) -->
@@ -117,8 +127,8 @@ Contributions with example scripts for other frameworks are welcome!
 ## License
 The data is provided under the [CC0 License](https://choosealicense.com/licenses/cc0-1.0/), following the license of Camelyon16.
 
-The rest of this repository is under the [MIT License](https://choosealicense.com/licenses/mit/)
+The rest of this repository is under the [MIT License](https://choosealicense.com/licenses/mit/).
 
 ## Acknowledgements
 * Babak Ehteshami Bejnordi, Geert Litjens, Jeroen van der Laak for their input on the configuration of this dataset.
-* README derived from [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist)
+* README derived from [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist).

keras_pcam/dataset/pcam.py

@@ -0,0 +1,69 @@
+"""PatchCamelyon(PCam) dataset
+Small 96x96 patches from histopathology slides from the Camelyon16 dataset.
+
+Please consider citing [1] when used in your publication:
+- [1] B. S. Veeling, J. Linmans, J. Winkens, T. Cohen, M. Welling. "Rotation Equivariant CNNs for Digital Pathology". arXiv [cs.CV] (2018), (available at http://arxiv.org/abs/1806.03962).
+
+
+Author: Bastiaan Veeling
+Source: https://github.com/basveeling/pcam
+"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+
+import pandas as pd
+from keras.utils import HDF5Matrix
+from keras.utils.data_utils import get_file
+from keras import backend as K
+
+
+def get_unzip_file(fname,
+             origin,
+             untar=False,
+             md5_hash=None,
+             file_hash=None,
+             cache_subdir='datasets',
+             hash_algorithm='auto',
+             extract=False,
+             archive_format='auto',
+             cache_dir=None):
+    import gzip
+    import shutil
+    get_file()
+    with open('file.txt', 'rb') as f_in, gzip.open('file.txt.gz', 'wb') as f_out:
+        shutil.copyfileobj(f_in, f_out)
+
+def load_data():
+    """Loads PCam dataset.
+
+    # Returns
+        Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
+    """
+    dirname = os.path.join('datasets', 'pcam')
+    base = 'https://drive.google.com/uc?export=download&id='
+    try:
+        y_train = HDF5Matrix(get_file('camelyonpatch_level_2_split_train_y.h5', origin= base+ '1269yhu3pZDP8UYFQs-NYs3FPwuK-nGSG', cache_subdir=dirname, archive_format='gzip'), 'y')
+        x_valid = HDF5Matrix(get_file('camelyonpatch_level_2_split_valid_x.h5', origin= base+ '1hgshYGWK8V-eGRy8LToWJJgDU_rXWVJ3', cache_subdir=dirname, archive_format='gzip'), 'x')
+        y_valid = HDF5Matrix(get_file('camelyonpatch_level_2_split_valid_y.h5', origin= base+ '1bH8ZRbhSVAhScTS0p9-ZzGnX91cHT3uO', cache_subdir=dirname, archive_format='gzip'), 'y')
+        x_test = HDF5Matrix(get_file('camelyonpatch_level_2_split_test_x.h5', origin= base+ '1qV65ZqZvWzuIVthK8eVDhIwrbnsJdbg_', cache_subdir=dirname, archive_format='gzip'), 'x')
+        y_test = HDF5Matrix(get_file('camelyonpatch_level_2_split_test_y.h5', origin= base+ '17BHrSrwWKjYsOgTMmoqrIjDy6Fa2o_gP', cache_subdir=dirname, archive_format='gzip'), 'y')
+
+        meta_train = pd.read_csv(get_file('camelyonpatch_level_2_split_train_meta.csv', origin= base+ '1XoaGG3ek26YLFvGzmkKeOz54INW0fruR', cache_subdir=dirname))
+        meta_valid = pd.read_csv(get_file('camelyonpatch_level_2_split_valid_meta.csv', origin= base+ '16hJfGFCZEcvR3lr38v3XCaD5iH1Bnclg', cache_subdir=dirname))
+        meta_test = pd.read_csv(get_file('camelyonpatch_level_2_split_test_meta.csv', origin= base+ '19tj7fBlQQrd4DapCjhZrom_fA4QlHqN4', cache_subdir=dirname))
+        x_train = HDF5Matrix(get_file('camelyonpatch_level_2_split_train_x.h5', origin= base+ '1Ka0XfEMiwgCYPdTI-vv6eUElOBnKFKQ2', cache_subdir=dirname, archive_format='gzip'), 'x')
+    except OSError:
+        raise NotImplementedError('Direct download currently not working. Please go to https://drive.google.com/drive/folders/1gHou49cA1s5vua2V5L98Lt8TiWA3FrKB and press download all. Then place files (ungzipped) in ~/.keras/datasets/pcam.')
+
+    if K.image_data_format() == 'channels_first':
+        raise NotImplementedError()
+
+    return (x_train, y_train, meta_train), (x_valid, y_valid, meta_valid), (x_test, y_test, meta_test)
+
+
+if __name__ == '__main__':
+    (x_train, y_train, meta_train), (x_valid, y_valid, meta_valid), (x_test, y_test, meta_test) = load_data()
+    print(len(x_train))