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veetinator/Road_Line_Marking_Dataset

Road Line and Marking Segmentation Dataset (RLMD) This repository contains dataset and additional information for paper RLMD: A Dataset for Road Marking Segmentation. Introduction RLMD is a road line and marking semantic segmentation dataset containing 2137 driving scene images and annotations. The annotations is manually annotated with 25 categories and saved in polygon mask format. Information about the categories is shown bellow, or you can download the [csv].… See the full description on the dataset page: https://huggingface.co/datasets/veetinator/Road_Line_Marking_Dataset.

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Road Line and Marking Segmentation Dataset (RLMD)

This repository contains dataset and additional information for paper RLMD: A Dataset for Road Marking Segmentation.

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Table of Contents

  1. 1.Introduction
  2. 2.Citation

Introduction

RLMD is a road line and marking semantic segmentation dataset containing 2137 driving scene images and annotations. The annotations is manually annotated with 25 categories and saved in polygon mask format. Information about the categories is shown bellow, or you can download the [csv].

idnameabbrrgb
0backgroundBG000
1box junctionBJ2552420
2crosswalkCW3411776
3stop lineSL6172204
4solid single whiteSSW2372836
5solid single yellowSSY16373164
6solid single redSSR18512287
7solid double whiteSDW136021
8solid double yellowSDY112146190
9dashed single whiteDSW18123029
10dashed single yellowDSY153217234
11left arrowLA15815976
12straight arrowSA121138134
13right arrowRA416496
14left straight arrowLSA7102146
15right straight arrowRSA247153255
16channelizing lineCL255204153
17motor prohibitedMP155255153
18slowSLOW255153173
19motor priority laneMPL230224147
20motor waiting zoneMWZ352787
21left turn boxLTB193158155
22motor iconMI1092978
23bike iconBI3164204
24parking lotPL175157185

Citation

This a dataset curated and labelled in proceeding of the following paper, please cite the following paper.

@inproceedings{
hsiao2023rlmd,
title={RLMD: A Dataset for Road Marking Segmentation},
author={Hsiao, Heng-Chih and Cai, Yi-Chang and Lin, Huei-Yung and Chiu, Wei-Chen and Chan, Chiao-Tung},
booktitle={2023 International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan)},
pages={427--428},
year={2023},
organization={IEEE}
}

license: mit task_categories:

  • image-segmentation
  • image-feature-extraction language:
  • en tags:
  • code ---