README.md

MobileNet v2

A Keras 2 implementation of MobileNet V2.

According to the paper:Inverted Residuals and Linear Bottlenecks Mobile Networks for Classification, Detection and Segmentation

Currently only the network structure is defined, and the training function will be updated later.

Requirement

• Python 3.5
• Tensorflow-gpu 1.2.0
• Keras 2.1.3

MobileNet v2 and inverted residual block architectures

MobileNet v2:

Each line describes a sequence of 1 or more identical (modulo stride) layers, repeated n times. All layers in the same sequence have the same number c of output channels. The first layer of each sequence has a stride s and all others use stride 1. All spatial convolutions use 3 X 3 kernels. The expansion factor t is always applied to the input size.

Residual Block Architectures:

Architectures of this implementation with (224, 224, 3) inputs and 1000 output:

##Reference

• Inverted Residuals and Linear Bottlenecks Mobile Networks for Classification, Detection and Segmentation

##Copyright See LICENSE for details.