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

0.121

MParams

2.537

Source framework

TensorFlow*

Accuracy

Metric

Original model

Converted model

Top 1

67.36%

67.36%

Top 5

87.45%

87.45%

Input

Original Model

Image, name: input, 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. Mean values: [127.5, 127.5, 127.5], scale factor for each channel: 127.5

Converted Model

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

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order: BGR.

Output

Original Model

Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax, shape: 1, 1001, format: B, C, where:

  • B - batch size

  • C - vector of probabilities.

Converted Model

Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax, shape: 1, 1001, format: B, C, where:

  • B - batch size

  • C - vector of probabilities.

Download a Model and Convert it into Inference Engine Format

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

An example of using the Model Downloader:

python3 <omz_dir>/tools/downloader/downloader.py --name <model_name>

An example of using the Model Converter:

python3 <omz_dir>/tools/downloader/converter.py --name <model_name>

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

0.121

MParams

2.537

Source framework

TensorFlow*

Accuracy

Metric

Original model

Converted model

Top 1

67.36%

67.36%

Top 5

87.45%

87.45%

Input

Original Model

Image, name: input, 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. Mean values: [127.5, 127.5, 127.5], scale factor for each channel: 127.5

Converted Model

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

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order: BGR.

Output

Original Model

Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax, shape: 1, 1001, format: B, C, where:

  • B - batch size

  • C - vector of probabilities.

Converted Model

Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax, shape: 1, 1001, format: B, C, where:

  • B - batch size

  • C - vector of probabilities.

Download a Model and Convert it into Inference Engine Format

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

An example of using the Model Downloader:

python3 <omz_dir>/tools/downloader/downloader.py --name <model_name>

An example of using the Model Converter:

python3 <omz_dir>/tools/downloader/converter.py --name <model_name>

Legal Information

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0-TF-Models.txt.