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efficientnet-v2-s

Use Case and High-Level Description

The efficientnet-v2-s model is a small variant of the EfficientNetV2 pre-trained on ImageNet-21k dataset and fine-tuned on ImageNet-1k 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 16.9406
MParams 21.3816
Source framework PyTorch*

Accuracy

Metric Value
Top 1 84.29%
Top 5 97.26%

Input

Original Model

Image, name: input, shape: 1, 3, 384, 384, 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 - [127.5, 127.5, 127.5], scale values - [127.5, 127.5, 127.5].

Converted Model

Image, name: input, shape: 1, 3, 384, 384, 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:

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-PyTorch-Image-Models.txt.