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hbonet-0.25

Use Case and High-Level Description

The hbonet-0.25 model is one of the classification models from repository with width_mult=0.25

Specification

Metric Value
Type Classification
GFLOPs 0.037
MParams 1.9300
Source framework PyTorch*

Accuracy

Metric Original model
Top 1 57.30%
Top 5 79.80%

Input

Original Model

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

  • B - batch size
  • C - number of channels
  • H - image height
  • W - image width

Expected color order: RGB. Mean values: [123.675, 116.28, 103.53], scale factor for each channel: [58.395, 57.12, 57.375]

Converted Model

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

  • B - batch size
  • C - number of channels
  • H - image height
  • W - image width

Expected color order: BGR.

Output

Object classifier according to ImageNet classes, shape: 1, 1000 in B, C format, where:

  • B - batch size
  • C - vector of probabilities for all dataset classes 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:

Legal Information

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0.txt.