- Description:
Classification of textures in colorectal cancer histology. Each example is a 150 x 150 x 3 RGB image of one of 8 classes.
Source code:
tfds.image_classification.ColorectalHistology
Versions:
2.0.0
(default): New split API (https://tensorflow.org/datasets/splits)
Download size:
246.14 MiB
Dataset size:
Unknown size
Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'train' |
5,000 |
- Features:
FeaturesDict({
'filename': Text(shape=(), dtype=tf.string),
'image': Image(shape=(150, 150, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=8),
})
Supervised keys (See
as_supervised
doc):('image', 'label')
Citation:
@article{kather2016multi,
title={Multi-class texture analysis in colorectal cancer histology},
author={Kather, Jakob Nikolas and Weis, Cleo-Aron and Bianconi, Francesco and Melchers, Susanne M and Schad, Lothar R and Gaiser, Timo and Marx, Alexander and Z{"o}llner, Frank Gerrit},
journal={Scientific reports},
volume={6},
pages={27988},
year={2016},
publisher={Nature Publishing Group}
}
- Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):