deeplabv3

Use Case and High-Level Description

DeepLab is a state-of-art deep learning model for semantic image segmentation. For details see paper.

Specification

Metric	Value
Type	Semantic segmentation
GFLOPs	11.469
MParams	23.819
Source framework	TensorFlow*

Accuracy

Metric	Value
mean_iou	68.41%

Input

Original model

Image, name: ImageTensor, shape: 1, 513, 513, 3, format: B, H, W, C, where:

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

Expected color order: RGB.

Converted Model

Image, name: mul_1/placeholder_port_1, shape: 1, 513, 513, 3, format: B, H, W, C, where:

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

Expected color order: BGR.

Output

Original Model

Integer values in a range [0, 20], which represent an index of a predicted class for each image pixel. Name: ArgMax, shape: 1, 513, 513 in B, H, W format, where:

• B - batch size
• H - image height
• W - image width

Converted Model

Integer values in a range [0, 20], which represent an index of a predicted class for each image pixel. Name: ArgMax/Squeeze, shape: 1, 513, 513 in B, H, W format, where:

• B - batch size
• H - image height
• W - image width

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:

• Image Segmentation C++ Demo
• Image Segmentation Python* Demo

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.