mobilenet-v2

Use Case and High-Level Description

MobileNet V2 is image classification model.

Specification

Metric

Value

Type

Classification

GFLOPs

0.876

MParams

3.489

Source framework

Caffe*

Accuracy

Metric

Value

Top 1

71.218%

Top 5

90.178%

Input

Original Model

Image, name: data, shape: 1, 3, 224, 224, format: B, C, H, W, where:

  • B - batch size

  • C - channel

  • H - height

  • W - width

Channel order is BGR. Mean values: [103.94, 116.78, 123.68], scale value: 58.8235294117647.

Converted Model

Image, name: data, shape: 1, 3, 224, 224, format: B, C, H, W, where:

  • B - batch size

  • C - channel

  • H - height

  • W - width

Channel order is BGR.

Output

Original Model

Object classifier according to ImageNet classes, name: prob, shape: 1, 1000, output data format is B, C, where:

  • B - batch size

  • C - predicted probabilities for each class in a range [0, 1]

Converted Model

Object classifier according to ImageNet classes, name: prob, shape: 1, 1000, output data format is B, C, where:

  • B - batch size

  • C - predicted probabilities for each class in a range [0, 1]

Download a Model and Convert it into OpenVINO™ IR Format

You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

omz_downloader --name <model_name>

An example of using the Model Converter:

omz_converter --name <model_name>

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities: