mobilenet-v1-0.25-128
is one of MobileNets - small, low-latency, low-power models parameterized to meet the resource constraints of a variety of use cases. They can be built upon for classification, detection, embeddings and segmentation similar to how other popular large scale models are used. For details, see paper.
Metric | Value |
---|---|
Type | Classification |
GFlops | 0.028 |
MParams | 0.468 |
Source framework | TensorFlow* |
Metric | Value |
---|---|
Top 1 | 40.54% |
Top 5 | 65% |
Image, name: input
, shape: 1, 128, 128, 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
Image, name: input
, shape: 1, 128, 128, 3
, format: B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Expected color order: BGR
.
Probabilities for all dataset classes in [0, 1] range (0 class is background). Name: MobilenetV1/Predictions/Reshape_1
.
Probabilities for all dataset classes in [0, 1] range (0 class is background). Name: MobilenetV1/Predictions/Softmax
, shape: 1, 1001
, format: B, C
, where:
B
- batch sizeC
- vector of probabilities.
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>
The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:
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
.