Git Product home page Git Product logo

datasets's Introduction

TensorFlow Datasets

TensorFlow Datasets provides many public datasets as tf.data.Datasets.

Kokoro PyPI version Tutorial API Catalog

Documentation

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 core values

TFDS has been built with these principles in mind:

  • Simplicity: Standard use-cases should work out-of-the box
  • Performance: TFDS follows best practices and can achieve state-of-the-art speed
  • Determinism/reproducibility: All users get the same examples in the same order
  • Customisability: Advanced users can have fine-grained control

If those use cases are not satisfied, please send us feedback.

Want a certain dataset?

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.

Citation

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}},
}

Disclaimers

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.

datasets's People

Contributors

acharles7 avatar adarob avatar afrozenator avatar ageron avatar annxingyuan avatar captain-pool avatar chanchalkumarmaji avatar conchylicultor avatar cyfra avatar eshan-agarwal avatar f1recracker avatar gen-ko avatar harsh020 avatar iswariyam avatar jackd avatar jpuigcerver avatar lgeiger avatar nikhilbartwal avatar pierrot0 avatar rickwierenga avatar ronw avatar sharanramjee avatar soumyadeepjana avatar tonywz avatar us avatar vijayphoenix avatar vvkio avatar williamhyzhang avatar yaozhaogoogle avatar yashk2810 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.