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 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 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

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.