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densenet-121-caffe2

Use Case and High-Level Description

This is a Caffe2* version of densenet-121 model, one of the DenseNet group of models designed to perform image classification. This model was converted from Caffe* to Caffe2* format. For details see repository, paper.

Specification

Metric

Value

Type

Classification

GFLOPs

5.723

MParams

7.971

Source framework

Caffe2*

Accuracy

Metric

Value

Top 1

74.904%

Top 5

92.192%

Input

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 - 58.8235294.

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 - 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 Inference Engine Format

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>
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