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.
Metric | Value |
---|---|
Type | Classification |
GFLOPs | 39.3 |
MParams | 143.667 |
Source framework | Caffe* |
Metric | Value |
---|---|
Top 1 | 71.062% |
Top 5 | 89.832% |
Image, name - data
, shape - 1,3,224,224
, format is B,C,H,W
where:
B
- batch sizeC
- channelH
- heightW
- width
Channel order is BGR
.
Mean values - [103.939, 116.779, 123.68]
Image, name - data
, shape - 1,3,224,224
, format is B,C,H,W
where:
B
- batch sizeC
- channelH
- heightW
- width
Channel order is BGR
.
Object classifier according to ImageNet classes, name - prob
, shape - 1,1000
, output data format is B,C
where:
B
- batch sizeC
- Predicted probabilities for each class in [0, 1] range
Object classifier according to ImageNet classes, name - prob
, shape - 1,1000
, output data format is B,C
where:
B
- batch sizeC
- Predicted probabilities for each class in [0, 1] range
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>
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.