We made a tool to generate caffe prototxt for DenseNet from https://github.com/liuzhuang13/DenseNet.
For details of these networks, please read the original paper:
1. Specify the network configuration, dense block, trainsition layer, and classification layer
DENSE_NET_121_CFG = [
{'Type': 'DenseBlock', 'LayerNum':6, 'KernelNum':128},
{'Type': 'Transition', 'KernelNum': 128},
{'Type': 'DenseBlock', 'LayerNum': 12, 'KernelNum': 128},
{'Type': 'Transition', 'KernelNum': 256},
{'Type': 'DenseBlock', 'LayerNum': 24, 'KernelNum': 128},
{'Type': 'Transition', 'KernelNum': 512},
{'Type': 'DenseBlock', 'LayerNum': 16, 'KernelNum': 128},
{'Type': 'Classification', 'OutputNum':1000},
]
2. Call build_model() to generate the deploy and train_val prototxt
xnet = DenseNet()
xnet.build_model(DENSE_NET_121_CFG)
3. The generated DenseNet121 can be viewed in [DenseNet121](http://ethereon.github.io/netscope/#/gist/6af541e7afd34b505fd1bfae53da7040)