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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 pretrained 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 1x3x224x224 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 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 following license:

This model is released for unrestricted use.