mobilenet-v3-small-1.0-224-tf¶
Use Case and High-Level Description¶
mobilenet-v3-small-1.0-224-tf
is one of MobileNets V3 - next generation of MobileNets, based on a combination of complementary search techniques as well as a novel architecture design. mobilenet-v3-small-1.0-224-tf
is targeted for low resource use cases. For details see paper.
Specification¶
Metric |
Value |
---|---|
Type |
Classification |
GFlops |
0.121 |
MParams |
2.537 |
Source framework |
TensorFlow* |
Accuracy¶
Metric |
Original model |
Converted model |
---|---|---|
Top 1 |
67.36% |
67.36% |
Top 5 |
87.45% |
87.45% |
Input¶
Original Model¶
Image, name: input
, shape: 1, 224, 224, 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, 3, 224, 224
, format: B, C, H, W
, where:
B
- batch sizeC
- number of channelsH
- image heightW
- image width
Expected color order: BGR
.
Output¶
Original Model¶
Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax
, shape: 1, 1001
, format: B, C
, where:
B
- batch sizeC
- vector of probabilities.
Converted Model¶
Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax
, shape: 1, 1001
, format: B, C
, where:
B
- batch sizeC
- vector of probabilities.
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 Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0-TF-Models.txt
.