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keras-resnet is the Keras package for deep residual networks. It’s fast and flexible.
A tantalizing preview of keras-resnet simplicity:
>>> shape, classes = (32, 32, 3), 10 >>> x = keras.layers.Input(shape) >>> y = keras_resnet.ResNet50(x) >>> y = keras.layers.Dense(classes)(y) >>> y = keras.layers.Flatten()(y.output) >>> model = keras.models.Model(x, y) >>> 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.
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