densenet-121-tf

Use Case and High-Level Description

This is a TensorFlow* version of densenet-121 model, one of the DenseNet group of models designed to perform image classification. For details, see TensorFlow* API docs, repository and paper.

Specification

Metric

Value

Type

Classification

GFlops

5.7287

MParams

7.9714

Source framework

TensorFlow*

Accuracy

Metric

Value

Top 1

74.46%

Top 5

92.13%

Input

Original Model

Image, name: input_1, shape: 1, 224, 224, 3, format: B, H, W, C, where:

  • B - batch size

  • H - image height

  • W - image width

  • C - number of channels

Expected color order: RGB. Mean values - [123.68, 116.78, 103.94], scale values - [58.395,57.12,57.375].

Converted Model

Image, name: input_1, shape: 1, 224, 224, 3, format: B, H, W, C, where:

  • B - batch size

  • H - image height

  • W - image width

  • C - number of channels

Expected color order: BGR.

Output

Original Model

Object classifier according to ImageNet classes, name: StatefulPartitionedCall/densenet121/predictions/Softmax, 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

The converted model has the same parameters as the original model.

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: