Keras-ResNet is the Keras package for deep residual networks. It's fast and flexible.
A tantalizing preview of Keras-ResNet simplicity:
>>> 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:
$ pip install keras-resnet
- Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug. There is a Contributor Friendly tag for issues that should be ideal for people who are not very familiar with the codebase yet.
- Fork the repository on GitHub to start making your changes to the master branch (or branch off of it).
- Write a test which shows that the bug was fixed or that the feature works as expected.
- Send a pull request and bug the maintainer until it gets merged and published. :) Make sure to add yourself to AUTHORS.