road-segmentation-adas-0001

Use Case and High-Level Description

This is a segmentation network to classify each pixel into four classes: BG, road, curb, mark.

Example

road-segmentation-adas-0001.png

Specification

Metric Value
Image size 896x512
GFlops 4.770
MParams 0.184
Source frameworkPyTorch*

Accuracy

The quality metrics calculated on 500 images from "Mighty AI" dataset that was converted for four class classification task are:

Label IOU ACC
mean 0.844 0.901
BG 0.986 0.994
road 0.954 0.974
curbs 0.727 0.831
marks 0.708 0.806

Performance

Inputs

A blob with a BGR image in the format: [B, C=3, H=512, W=896], where:

Outputs

The output is a blob with the shape [B, C=4, H=512, W=896]. It can be treated as a four-channel feature map, where each channel is a probability of one of the classes: BG, road, curb, mark.

Legal Information

[*] Other names and brands may be claimed as the property of others.