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: [1x3x227x227], format: [BxCxHxW] 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: [1x3x227x227], format: [BxCxHxW] 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 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>

Legal Information

The original model is distributed under the following license:

This model is released for unrestricted use.