.. image:: https://travis-ci.org/broadinstitute/keras-resnet.svg?branch=master :target: https://travis-ci.org/broadinstitute/keras-resnet
Keras-ResNet is the Keras package for deep residual networks. It's fast and flexible.
A tantalizing preview of Keras-ResNet simplicity:
.. code-block:: python
>>> import keras
>>> import keras_resnet.models
>>> shape, classes = (32, 32, 3), 10
>>> x = keras.layers.Input(shape)
>>> model = keras_resnet.models.ResNet50(x, classes=classes)
>>> model.compile("adam", "categorical_crossentropy", ["accuracy"])
>>> (training_x, training_y), (_, _) = keras.datasets.cifar10.load_data()
>>> training_y = keras.utils.np_utils.to_categorical(training_y)
>>> model.fit(training_x, training_y)
Installation couldn’t be easier:
.. code-block:: bash
$ pip install keras-resnet
Contributor Friendly
_ tag for issues that should be ideal for people who are not very familiar with the codebase yet.the repository
_ on GitHub to start making your changes to the master branch (or branch off of it)... _the repository
: http://github.com/0x00b1/keras-resnet
.. _AUTHORS: https://github.com/0x00b1/keras-resnet/blob/master/AUTHORS.rst
.. _Contributor Friendly: https://github.com/0x00b1/keras-resnet/issues?direction=desc&labels=Contributor+Friendly&page=1&sort=updated&state=open