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pspnet-pytorch

Use Case and High-Level Description

pspnet-pytorch is a semantic segmentation model, pre-trained on Pascal VOC dataset for 21 object classes, listed in <omz_dir>/data/dataset_classes/voc_20cl_bkgr.txt file. The model was built on ResNetV1-50 backbone and PSP segmentation head. This model is used for pixel-level prediction tasks. For details see repository, paper.

Specification

Metric Value
Type Semantic segmentation
GFlops 357.1719
MParams 46.5827
Source framework PyTorch*

Accuracy

Metric Value
mean_iou 70.1%

Accuracy metrics were obtained with fixed input resolution 512x512.

Input

Original model

Image, name: input.1, shape: 1, 3, 512, 512, format: B, C, H, W, where:

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

Expected color order: RGB. Mean values: [123.675, 116.28, 103.53], scale values: [58.395, 57.12, 57.375]

Converted Model

Image, name: input.1, shape: 1, 3, 512, 512, format: B, C, H, W, where:

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

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: segmentation_map, shape: 1, 1, 512, 512 in B, 1, 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: segmentation_map, shape: 1, 1, 512, 512 in B, 1, 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:

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-MMSegmentation-Models.txt.