densenet-121

Use Case and High-Level Description

The densenet-121 model is one of the DenseNet group of models designed to perform image classification. The authors originally trained the models on Torch*, but then converted them into Caffe* format. All DenseNet models have been pre-trained on the ImageNet image database. For details about this family of models, check out the repository.

Specification

Metric

Value

Type

Classification

GFLOPs

5.724

MParams

7.971

Source framework

Caffe*

Accuracy

Metric

Value

Top 1

74.42%

Top 5

92.136%

See the original repository.

Input

The model input is a blob that consists of a single image of 1, 3, 224, 224 in BGR order. Before passing the image blob into the network, subtract BGR mean values as follows: [103.94, 116.78, 123.68]. In addition, values must be divided by 0.017.

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 - [103.94, 116.78, 123.68], scale value - 58.8235294117647

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

The model output for densenet-121 is a typical object classifier output for 1000 different classifications matching those in the ImageNet database.

Original Model

Object classifier according to ImageNet classes, name - fc6, shape - 1, 1000, 1, 1, contains predicted probability for each class in logits format.

Converted Model

Object classifier according to ImageNet classes, name - fc6, shape - 1, 1000, 1, 1, contains predicted probability for each class in logits format.

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: