mobilenet-v3-large-1.0-224-tf

Use Case and High-Level Description

mobilenet-v3-large-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-large-1.0-224-tf is targeted for high resource use cases. For details see paper.

Specification

Metric Value
Type Classification
GFlops 0.4536
MParams 5.4721
Source framework TensorFlow*

Accuracy

Metric Original model Converted model
Top 1 75.70% 75.70%
Top 5 92.76% 92.76%

Input

Original Model

Image, name: input , shape: [1x224x224x3], format: [BxHxWxC], where:

- B - batch size
- H - image height
- W - image width
- C - 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: [1x3x224x224], format: [BxCxHxW], where:

- B - batch size
- C - number of channels
- H - image height
- W - 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: [BxC], where:

  • B - batch size
  • C - vector of probabilities.

Converted Model

Probabilities for all dataset classes (0 class is background). Name: MobilenetV3/Predictions/Softmax, shape: [1,1001], format: [BxC], where:

  • B - batch size
  • C - vector of probabilities.

Legal Information

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in APACHE-2.0-TensorFlow.txt.