googlenet-v3#
Use Case and High-Level Description#
The googlenet-v3
model is the first of the Inception family of models designed to perform image classification. For details about this family of models, check out the paper.
Specification#
Metric |
Value |
---|---|
Type |
Classification |
GFLOPs |
11.469 |
MParams |
23.819 |
Source framework |
TensorFlow* |
Accuracy#
Metric |
Value |
---|---|
Top 1 |
77.904% |
Top 5 |
93.808% |
Input#
Original Model#
Image, name: input
, shape: 1, 299, 299, 3
, format: B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Expected color order: RGB
.
Mean values: [127.5, 127.5, 127.5], scale factor for each channel: 127.5
Converted Model#
Image, name: input
, shape: 1, 299, 299, 3
, format: B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Expected color order: BGR
.
Output#
Object classifier according to ImageNet classes, name: InceptionV3/Predictions/Softmax
, shape: 1, 1001
in B, C
format, where:
B
- batch sizeC
- vector of probabilities for all dataset classes in [0, 1] range (0 class is background).
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-TF-Models.txt
.