efficientnet-b0

February 21, 2022 · View on GitHub

Use Case and High-Level Description

The efficientnet-b0 model is one of the EfficientNet models designed to perform image classification. This model was pre-trained in TensorFlow*. All the EfficientNet models have been pre-trained on the ImageNet image database. For details about this family of models, check out the TensorFlow Cloud TPU repository.

Specification

MetricValue
TypeClassification
GFLOPs0.819
MParams5.268
Source frameworkTensorFlow*

Accuracy

MetricOriginal modelConverted model
Top 175.70%75.70%
Top 592.76%92.76%

Input

Original Model

Image, name - image, shape - 1, 224, 224, 3, format is B, H, W, C, where:

  • B - batch size
  • H - height
  • W - width
  • C - channel

Channel order is RGB.

Converted Model

Image, name - sub/placeholder_port_0, shape - 1, 224, 224, 3, format is B, H, W, C, where:

  • B - batch size
  • H - height
  • W - width
  • C - channel

Channel order is 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 - predicted probabilities for each class in logits format

Converted Model

Object classifier according to ImageNet classes, name - efficientnet-b0/model/head/dense/MatMul, shape - 1, 1000, output data format is B, C, where:

  • B - batch size
  • C - predicted probabilities for each class 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:

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-TF-TPU.txt.