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 = tensorflow.keras.layers.Input(shape)
>>> model = keras_resnet.models.ResNet50(x, classes=classes)
>>> model.compile("adam", "categorical_crossentropy", ["accuracy"])
>>> (training_x, training_y), (_, _) = tensorflow.keras.datasets.cifar10.load_data()
>>> training_y = tensorflow.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.