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mobilenet-v3-small-1.0-224-tf

Use Case and High-Level Description

mobilenet-v3-small-1.0-224-tf is one of MobileNets V3 - next generation of MobileNets, based on a combination of complementary search techniques as well as a novel architecture design. mobilenet-v3-small-1.0-224-tf is targeted for low resource use cases. For details see paper.

Specification

Metric

Value

Type

Classification

GFlops

0.11682

MParams

2.537

Source framework

TensorFlow*

Accuracy

Metric

Original model

Converted model

Top 1

67.36%

67.36%

Top 5

87.44%

87.44%

Input

Original Model

Image, name: input_1, shape: 1, 224, 224, 3, format: B, H, W, C, where:

  • B - batch size

  • H - image height

  • W - image width

  • C - number of channels

Expected color order: RGB.

Converted Model

Image, name: input_1, shape: 1, 224, 224, 3, format: B, H, W, C, where:

  • B - batch size

  • H - image height

  • W - image width

  • C - number of channels

Expected color order: BGR.

Output

Original Model

Object classifier according to ImageNet classes, name - StatefulPartitionedCall/MobilenetV3small/Predictions/Softmax, shape - 1, 1000, output data format is B, C where:

  • B - batch size

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

Converted Model

The converted model has the same parameters as the original model.

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:

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