Abstract
As deep learning shines in the field of machine vision, this article uses the YOLACT instance segmentation algorithm to solve the detection and segmentation of pedestrians, vehicles and other objects in traffic scenes. In this paper, the backbone in the YOLACT algorithm is changed from the original resnet50 to the lightweight resnet18 to ensure that the algorithm can be deployed on Jetson-AGX-Xavier, and the processing speed can reach 9.4 frames per second, and the map can reach 81%. In NVIDIA 2070 super, the inference speed on the graphics card can reach 40 frames per second.
Export citation and abstract BibTeX RIS
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.