mobilenet-v3-large-1.0-224-paddle

Use Case and High-Level Description

mobilenet-v3-large-1.0-224-paddle 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-large-1.0-224-paddle is pretrained in Paddle* framework and targeted for high resource use cases. For details see paper and repository.

Specification

Metric

Value

Type

Classification

GFlops

0.4565

MParams

5.468

Source framework

Paddle*

Accuracy

Metric

Result

Top 1

75.248%

Top 5

92.32%

Input

Original Model

Image, name: x, 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: RGB. Mean values - [123.675,116.28,103.53], scale values - [58.395, 57.12, 57.375].

Converted Model

Image, name: x, 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

Object classifier according to ImageNet classes, name - softmax_1.tmp_0, 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: