densenetFCN.py 文件源码

def transition_down(inputs, n_filters, compression=1.0, dropout=0.,
                    weight_decay=1e-4, name=''):
    n_filters = int(n_filters*compression)
    l = bn_relu_conv(inputs, n_filters, 1, dropout, name=name+'_TD')
    l = AveragePooling2D((2, 2), strides=(2, 2), name=name+'_TD_pool')(l)
    return l, n_filters


# Build the DenseNet model