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: