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caffenet

Use Case and High-Level Description

CaffeNet* model is used for classification. For details see paper.

Specification

Metric

Value

Type

Classification

GFlops

1.463

MParams

60.965

Source framework

Caffe*

Accuracy

Metric

Value

Top 1

56.714%

Top 5

79.916%

Input

Original Model

Image, name: data, shape: 1, 3, 227, 227, format: B, C, H, W, where:

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order: BGR. Mean values: [104.0, 117.0, 123.0].

Converted Model

Image, name: data, shape: 1, 3, 227, 227, format: B, C, H, W, where:

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order: BGR.

Output

Original Model

Object classifier according to ImageNet classes, name: prob, shape: 1, 1000. Contains predicted probability for each class.

Converted model

Object classifier according to ImageNet classes, name: prob, shape: 1, 1000. Contains predicted probability for each class.

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:

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