Fully Connected DenseNets for Semantic Segmentation

Fully Connected DenseNet for Image Segmentation implementation of the paper The One Hundred Layers Tiramisu : Fully Convolutional DenseNets for Semantic Segmentation

Differences

• Use of SubPixelConvolution instead of Deconvolution as default method for Upsampling.

Usage :

Simply import the densenet_fc.py script and call the create method:

import densenet_fc as dc

model = DenseNetFCN((32, 32, 3), nb_dense_block=5, growth_rate=16,
                        nb_layers_per_block=4, upsampling_type='upsampling', classes=1)

Requirements

Keras 1.2.2 Theano (master branch) / Tensorflow 1.0+ h5py