Dual Path Networks in Keras

Dual Path Networks are highly efficient networks which combine the strength of both ResNeXt Aggregated Residual Transformations for Deep Neural Networks and DenseNets Densely Connected Convolutional Networks.

Note: Weights have not been ported over yet.

Dual Path Connections

Usage

Several of the standard Dual Path Network models have been included. They can be initialized as :

from dual_path_network import DPN92, DPN98, DPN107, DPN137

model = DPN92(input_shape=(224, 224, 3)) # same for the others

To create a custom DualPathNetwork, use the DualPathNetwork builder method :

from dual_path_network import DualPathNetwork

model = DualPathNetwork(input_shape=(224, 224, 3),
                        initial_conv_filters=64,
                        depth=[3, 4, 20, 3],
                        filter_increment=[16, 32, 24, 128],
                        cardinality=32,
                        width=3,
                        weight_decay=0,
                        include_top=True,
                        weights=None,
                        input_tensor=None,
                        pooling=None,
                        classes=1000)

Performance

Support