TRoM

displayName: TRoM
license:
- TRoM Custom
paperUrl: https://ieeexplore.ieee.org/document/8317749
publishDate: "2017"
publishUrl: http://www.tromai.icoc.me/
publisher:
- Tsinghua University
tags:
- Roads

---
# 数据集介绍
## 简介
清华道路标记，称为TRoM，是用于识别道路标记的数据集。这是第一个专注于自动驾驶或ADAS的道路标记的数据集。数据集中的样本是在中国北京市收集的，收集期持续了一个多月。它涵盖了各种交通和天气条件。在当前版本的TRoM中，注释了19个类别的道路标记以供识别使用。该基准测试旨在为自动驾驶和ADAS开发令人惊叹的数据驱动深度学习算法。

## Download dataset
:modelscope-code[]{type="git"}

displayName: TRoM
license:
- TRoM Custom
paperUrl: https://ieeexplore.ieee.org/document/8317749
publishDate: "2017"
publishUrl: http://www.tromai.icoc.me/
publisher:
- Tsinghua University
tags:
- Roads

---
# Dataset Introduction
## Overview
Tsinghua Road Markings (TRoM) is a dataset for road marking recognition. It is the first dataset focused on road markings for autonomous driving or ADAS. The samples in the dataset were collected in Beijing, China over a period of more than one month, covering various traffic and weather conditions. In the current version of TRoM, road markings from 19 categories are annotated for recognition purposes. This benchmark is designed to facilitate the development of excellent data-driven deep learning algorithms for autonomous driving and ADAS.

## Download Dataset
:modelscope-code[]{type="git"}

搜集汇总

背景与挑战

背景概述

TRoM是由清华大学发布的道路标记识别数据集，专注于自动驾驶或ADAS应用。该数据集包含在中国北京市收集的样本，涵盖多种交通和天气条件，并标注了19个类别的道路标记，旨在支持数据驱动的深度学习算法开发。