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.
Metric | Value |
---|---|
Type | Classification |
GFLOPs | 0.819 |
MParams | 5.268 |
Source framework | TensorFlow* |
Metric | Original model | Converted model |
---|---|---|
Top 1 | 76.43% | 76.43% |
Top 5 | 93.04% | 93.04% |
Image, name - image
, shape - [1x224x224x3]
, format is [BxHxWxC]
, where:
B
- batch sizeH
- heightW
- widthC
- channel
Channel order is RGB
.
Image, name - sub/placeholder_port_0
, shape - [1x3x224x224]
, format is [BxCxHxW]
, where:
B
- batch sizeC
- channelH
- heightW
- width
Channel order is BGR
.
Object classifier according to ImageNet classes, name - logits
, shape - 1,1000
, output data format is B,C
where:
B
- batch sizeC
- predicted probabilities for each class in the logits format
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 sizeC
- predicted probabilities for each class in the logits format
You can download models and if necessary convert them into Inference Engine format using the Model Downloader and other automation tools as shown in the examples below.
An example of using the Model Downloader:
python3 <omz_dir>/tools/downloader/downloader.py --name <model_name>
An example of using the Model Converter:
python3 <omz_dir>/tools/downloader/converter.py --name <model_name>
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.