MobileNetv2_TF

Introduction

This is a Tensorflow implementation of Google's MobileNetv2. MobileNet is a general architecture and can be used for multiple use cases. Depending on the use case, it can use different input layer size and different head (for example: embeddings, localization and classification). for details, please reference the following paper:

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

MobileNetv2 and inverted residual block architectures

The difference between residual block and inverted residual:

MobileNetv2 Neural Network:

Bottleneck Architectures:

Requirement

• python >= 2.7
• tensorflow >= r1.2

References

• Mobilenet_v2 on arxiv
• Mobilenet_v1 on slim

Copyright

See LICENSE for details.