efficientnet-b0_auto_aug

Use Case and High-Level Description

The efficientnet-b0_auto_aug model is one of the EfficientNet models designed to perform image classification, trained with AutoAugmentation preprocessing. This model was pretrained in TensorFlow*. All the EfficientNet models have been pretrained on the ImageNet* image database. For details about this family of models, check out the TensorFlow Cloud TPU repository.

Example

Specification

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

Accuracy

Metric Original model Converted model
Top 1 76.43% 76.43%
Top 5 93.04% 93.04%

Performance

Input

Original Model

Image, name - image, shape - [1x224x224x3], format is [BxHxWxC], where:

Channel order is RGB.

Converted Model

Image, name - sub/placeholder_port_0, shape - [1x3x224x224], format is [BxCxHxW], where:

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:

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:

Legal Information

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in APACHE-2.0-TF-TPU.txt.