一种用于目标识别的数据集生成和生成ROS2 FPGA节点的工具

2021 International Conference on Field-Programmable Technology (ICFPT) Pub Date : 2021-12-06 DOI:10.1109/ICFPT52863.2021.9609880

Hayato Amano, Hayato Mori, Akinobu Mizutani, Tomohiro Ono, Yuma Yoshimoto, Takeshi Ohkawa, H. Tamukoh

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引用次数: 4

摘要

本文介绍了我们的自动驾驶系统，该系统配备了来自相机图像的识别处理单元，用于危险物体/人偶检测和车道检测。本文重点研究了一种神经网络数据集生成方法，以及面向ROS2-FPGA节点的生成工具“FPGA Oriented Easy Synthesizer tool (FOrEST)”。结果表明，使用生成的数据集训练的神经网络的mAP值为94%，FOrEST对ROS2-FPGA的通信开销为2-3 ms。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A dataset generation for object recognition and a tool for generating ROS2 FPGA node

This paper introduces our autonomous driving system equipped with recognition processing units from a camera image for hazard object / human-doll detection and drive lane detection. In particular, this paper focuses on a dataset generation method for neural networks and a generation tool “FPGA Oriented Easy Synthesizer Tool (FOrEST)” for ROS2-FPGA nodes. The results show that mAP of a neural network trained by the generated dataset is 94%, and a overhead of ROS2-FPGA communication by the FOrEST is 2–3 ms.

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2021 International Conference on Field-Programmable Technology (ICFPT)

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