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README.md | 1 year ago |
TensorFlow Datasets provides many public datasets as tf.data.Datasets
.
To install and use TFDS, we strongly encourage to start with our
getting started guide. Try
it interactively in a
Colab notebook.
Our documentation contains:
# !pip install tensorflow-datasets
import tensorflow_datasets as tfds
import tensorflow as tf
# Construct a tf.data.Dataset
ds = tfds.load('mnist', split='train', as_supervised=True, shuffle_files=True)
# Build your input pipeline
ds = ds.shuffle(1000).batch(128).prefetch(10).take(5)
for image, label in ds:
pass
TFDS has been built with these principles in mind:
If those use cases are not satisfied, please send us
feedback.
Adding a dataset is really straightforward by following
our guide.
Request a dataset by opening a
Dataset request GitHub issue.
And vote on the current
set of requests
by adding a thumbs-up reaction to the issue.
Please include the following citation when using tensorflow-datasets
for a
paper, in addition to any citation specific to the used datasets.
@misc{TFDS,
title = {{TensorFlow Datasets}, A collection of ready-to-use datasets},
howpublished = {\url{https://www.tensorflow.org/datasets}},
}
This is a utility library that downloads and prepares public datasets. We do
not host or distribute these datasets, vouch for their quality or fairness, or
claim that you have license to use the dataset. It is your responsibility to
determine whether you have permission to use the dataset under the dataset's
license.
If you're a dataset owner and wish to update any part of it (description,
citation, etc.), or do not want your dataset to be included in this
library, please get in touch through a GitHub issue. Thanks for your
contribution to the ML community!
If you're interested in learning more about responsible AI practices, including
fairness, please see Google AI's Responsible AI Practices.
tensorflow/datasets
is Apache 2.0 licensed. See the
LICENSE
file.
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