vgg19

Use Case and High-Level Description

The vgg19 model is one of the vgg models designed to perform image classification in Caffe* format.

The model input is a blob that consists of a single image of 1, 3, 224, 224 in BGR order. The BGR mean values need to be subtracted as follows: [103.939, 116.779, 123.68] before passing the image blob into the network.

The model output for vgg19 is the typical object classifier output for the 1000 different classifications matching those in the ImageNet database.

Specification

Metric

Value

Type

Classification

GFLOPs

39.3

MParams

143.667

Source framework

Caffe*

Accuracy

Metric

Value

Top 1

71.062%

Top 5

89.832%

Input

Original mode

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. Mean values - [103.939, 116.779, 123.68]

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 [0, 1] range

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 [0, 1] range

Download a Model and Convert it into Inference Engine 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>

Use Case and High-Level Description

The vgg19 model is one of the vgg models designed to perform image classification in Caffe* format.

The model input is a blob that consists of a single image of 1, 3, 224, 224 in BGR order. The BGR mean values need to be subtracted as follows: [103.939, 116.779, 123.68] before passing the image blob into the network.

The model output for vgg19 is the typical object classifier output for the 1000 different classifications matching those in the ImageNet database.

Specification

Metric

Value

Type

Classification

GFLOPs

39.3

MParams

143.667

Source framework

Caffe*

Accuracy

Metric

Value

Top 1

71.062%

Top 5

89.832%

Input

Original mode

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. Mean values - [103.939, 116.779, 123.68]

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 [0, 1] range

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 [0, 1] range

Download a Model and Convert it into Inference Engine 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>

Legal Information

The original model is distributed under the Creative Commons Attribution 4.0 International Public License. A copy of the license is provided in <omz_dir>/models/public/licenses/CC-BY-4.0.txt.