efficientnet-v2-b0#

Use Case and High-Level Description#

The efficientnet-v2-b0 model is a variant of the EfficientNetV2 pre-trained on ImageNet dataset for image classification task. EfficientNetV2 is a new family of convolutional networks that have faster training speed and better parameter efficiency than previous models. A combination of training-aware neural architecture search and scaling were used in the development to jointly optimize training speed and parameter efficiency.

More details provided in the paper and repository.

Specification#

Metric

Value

Type

Classification

GFlops

1.4641

MParams

7.1094

Source framework

PyTorch*

Accuracy#

Metric

Value

Top 1

78.36%

Top 5

94.02%

Input#

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

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#

Object classifier according to ImageNet classes, name: logits, shape: 1, 1000, output data format is B, C, where:

  • B - batch size

  • C - vector of probabilities for all dataset classes in logits format

Converted Model#

Object classifier according to ImageNet classes, name: logits, shape: 1, 1000, output data format is B, C, where:

  • B - batch size

  • C - vector of probabilities for all dataset classes in logits format

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: