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inception-resnet-v2-tf

Use Case and High-Level Description

The inception-resnet-v2 model is one of the Inception family of models designed to perform image classification. For details about this family of models, check out the paper.

Specification

Metric

Value

Type

Classification

GFlops

22.227

MParams

30.223

Source framework

TensorFlow*

Accuracy

Metric

Value

Top 1

77.82%

Top 5

94.03%

Input

Original Model

Image, name: input, shape: 1, 299, 299, 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, 299, 299, 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

Probabilities for all dataset classes (0 class is background). Probabilities are represented in logits format. Name: InceptionResnetV2/AuxLogits/Logits/BiasAdd.

Converted Model

Probabilities for all dataset classes (0 class is background). Probabilities are represented in logits format. Name: InceptionResnetV2/AuxLogits/Logits/MatMul, shape: 1, 1001 in B, C format, where:

  • B - batch size

  • C - vector of probabilities.

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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