googlenet-v1

Use Case and High-Level Description

The googlenet-v1 model is the first of the Inception family of models designed to perform image classification. Like the other Inception models, the googlenet-v1 model has been pre-trained on the ImageNet image database. For details about this family of models, check out the paper.

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: [104.0, 117.0, 123.0] before passing the image blob into the network.

The model output for googlenet-v1 is the typical object classifier output for the 1000 different classifications matching those in the ImageNet database.

Specification

Metric

Value

Type

Classification

GFLOPs

3.266

MParams

6.999

Source framework

Caffe*

Accuracy

Metric

Value

Top 1

68.928%

Top 5

89.144%

See the original repository.

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 BGR. Mean values - [104.0, 117.0, 123.0]

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 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: