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 sizeC
- number of channelsH
- image heightW
- 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 sizeC
- number of channelsH
- image heightW
- 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 sizeC
- 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 sizeC
- 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
.