Segmentation of sandplain lupin weeds from morphologically similar narrow-leafed lupins in the field
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https://figshare.com/articles/dataset/Segmentation_of_sandplain_lupin_weeds_from_morphologically_similar_narrow-leafed_lupins_in_the_field/21746669/1
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资源简介:
Dataset for weed detection used in the paper "Segmentation of sandplain lupin weeds from morphologically similar narrow-leafed lupins in the field". <br> The scripts developed are available on GitHub at mdanilevicz/WeedDetectionML. <br> This repository contains five datasets collected in the field by drone or smartphone in Western Australia, Australia. The images for <strong>field-1, field-2, grow-1</strong> and <strong>grow-2</strong> datasets were collected using the DJI Phantom 4 unoccupied aerial vehicle (UAV) RGB camera. The images were collected between 12 and 2 PM under overcast or clear sky conditions. The details for the image collection can be seen in Table 3. The images were collected with 75% side overlap and 80% front overlap, with five ground control points distributed across the field to increase GPS accuracy. Additionally, 217 images with 4879 sandplain lupins labelled among narrow-leafed lupins were downloaded from the Weed-AI database and named <strong>ext-1 </strong>dataset. <br> In this repository you will find the RGB images, plant-soil segmentation mask obtained using CIVE vegetation index and weed-crop-soil segmentation mask. <br> Detailed methods fro dataset generation is available on the paper, and github repositories. <br> <br>
本数据集用于论文"《田间从形态相似窄叶羽扇豆中分割沙原羽扇豆杂草》"中的杂草检测任务。<br>所开发的脚本已开源至GitHub平台,仓库地址为mdanilevicz/WeedDetectionML。<br>本仓库包含在澳大利亚西澳州通过无人机或智能手机实地采集的五组数据集。其中field-1、field-2、grow-1与grow-2数据集的图像均通过DJI Phantom 4型民用无人机(UAV)RGB相机采集。图像采集时段为正午12时至下午2时,采集时天气为阴天或晴朗。图像采集的详细参数可见表3。本次采集采用75%的旁向重叠度与80%的航向重叠度,并在田间布设5个地面控制点以提升GPS定位精度。此外,从Weed-AI数据库中下载得到217张图像,其中包含4879株标注于窄叶羽扇豆中的沙原羽扇豆样本,该数据集命名为ext-1。<br>本仓库中包含RGB原图、基于CIVE植被指数得到的植株-土壤分割掩码,以及杂草-作物-土壤分割掩码。<br>详细的数据集生成方法可参阅该论文及GitHub仓库文档。
提供机构:
figshare
创建时间:
2023-03-26
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集专注于沙原羽扇豆杂草与窄叶羽扇豆在田间的分割检测,包含五个子集,图像通过无人机或智能手机采集,部分来自Weed-AI数据库,提供RGB图像和分割掩码。数据集用于支持杂草检测研究,与相关论文和GitHub脚本关联。
以上内容由遇见数据集搜集并总结生成



