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vgg16

Use Case and High-Level Description

The vgg16 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 "1x3x224x224" 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 vgg16 is the typical object classifier output for the 1000 different classifications matching those in the ImageNet database.

Example

Specification

Metric Value
Type Classification
GFLOPs 30.974
MParams 138.358
Source framework Caffe*

Accuracy

Metric Value
Top 1 70.968%
Top 5 89.878%

Performance

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

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 CC-BY-4.0.txt.