DeepLab is a state-of-art deep learning model for semantic image segmentation. For details see paper.
| Metric | Value |
|---|---|
| Type | Semantic segmentation |
| GFLOPs | 11.469 |
| MParams | 23.819 |
| Source framework | TensorFlow* |
| Metric | Value |
|---|---|
| mean_iou | 68.41% |
Image, name: ImageTensor, shape: 1, 513, 513, 3, format: B, H, W, C, where:
B- batch sizeH- image heightW- image widthC- number of channels
Expected color order: RGB.
Image, name: mul_1/placeholder_port_1, shape: 1, 513, 513, 3, format: B, H, W, C, where:
B- batch sizeH- image heightW- image widthC- number of channels
Expected color order: BGR.
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 sizeH- image heightW- image width
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 sizeH- image heightW- image width
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.