A package of Wide Residual Networks for image recognition in Keras.
keras-wrn is the Keras package for Wide Residual Networks. It's fast and flexible.
Wide ResNets are faster to train and more accurate than traditional ResNets, even when pre-activation structure is used.
```python import keras
shape, classes = (32, 32, 3), 10
model = keras_wrn.build_model(shape, classes, 16, 4)
model.compile("adam", "categorical_crossentropy", ["accuracy"])
(x_train, y_train), (, ) = keras.datasets.cifar10.load_data()
y_train = keras.utils.np_utils.to_categorical(y_train)
model.fit(x_train, y_train, epochs=10) ```
Hey there! New ideas are welcome: open/close issues, fork the repo and share your code with a Pull Request.
Clone this project to your computer:
git clone https://github.com/EricAlcaide/keras-wrn
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