Depthwise Convolutional Layer

Introduction

This is a personal caffe implementation of mobile convolution layer. For details, please read the original paper:

• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

How to build

1. Merge the caffe folder in the repo with your own caffe.

   $ cp -r $REPO/caffe/* $YOURCAFFE/
   

2. Then make.

   $ cd $YOURCAFFE && make
   

Usage

Replacing the type of mobile convolution layer with "DepthwiseConvolution" is all. Please refer to the example/Withdw_MN_train_128_1_train.prototxt, which is altered from

• MobileNet-Caffe

GPUPerformance on example net

[^nocudnn]: When turn on cudnn, the memory consuming of mobilenet would increase to unbelievable level. You may try.

Transfer normal net to mobilenet

I write a script [transfer2Mobilenet.py] to convert normal net to mobilenet format. You may try too. Usage:

python ./transfer2Mobilenet.py sourceprototxt targetprototxt [--midbn nobn --weight_filler msra --activation ReLU]    ["--origin_type" means the depthwise convolution layer's type will be "Convolution" instead of "DepthwiseConvolution"]

The "transferTypeToDepthwiseConvolution.py" will be used for changing the depthwise convolution layer's type from "Convolution" to "DepthwiseConvolution".