Semantic Segmentation - 3.5 English

Vitis AI Library User Guide (UG1354)

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3.5 English

Semantic segmentation assigns a semantic category to each pixel in the input image, that is, it classifies pixels as part of an object, say, a car, a road, a tree, a horse, etc. Libsegmentation is a segmentation library that can be used in ADAS applications. It offers simple interfaces for a developer to deploy segmentation tasks on an AMD target.

The following is an example of semantic segmentation, where "blue-gray" denotes the sky, "green" denotes trees, "red" denotes people, "dark blue" denotes cars, "plum" denotes the road, and "gray" denotes structures.

Figure 1. Semantic Segmentation Example

The following table lists the semantic segmentation models supported by the Vitis AI Library.

Table 1. Semantic Segmentation Models
No Model Name Framework
1 fpn Caffe
2 FPN-resnet18_Endov
3 semantic_seg_citys_tf2 TensorFlow
4 mobilenet_v2_cityscapes_tf


6 ENet_cityscapes_pt
7 unet_chaos-CT_pt
8 SemanticFPN_Mobilenetv2_pt
9 HRNet_pt