efficientnet-b0-pytorch¶

Use Case and High-Level Description¶

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

The model input is a blob that consists of a single image with the 3, 224, 224 shape in the RGB order. Before passing the image blob to the network, do the following:

Subtract the RGB mean values as follows: [123.675, 116.28, 103.53]
Divide the RGB mean values by [58.395, 57.12, 57.375]

The model output for efficientnet-b0-pytorch is the typical object classifier output for 1000 different classifications matching those in the ImageNet database.

Specification¶

Metric	Value
Type	Classification
GFLOPs	0.819
MParams	5.268
Source framework	PyTorch*

Accuracy¶

Metric	Original model	Converted model
Top 1	77.70%	77.70%
Top 5	93.52%	93.52%

Input¶

Original Model¶

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

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

Channel order is RGB. Mean values - [123.675, 116.28, 103.53], scale values - [58.395, 57.12, 57.375].

Converted Model¶

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

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

Channel order is BGR.

Output¶

Original Model¶

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

B - batch size
C - predicted probabilities for each class in the logits format

Converted Model¶

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

B - batch size
C - predicted probabilities for each class in the 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-EfficientNet.txt.

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