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项目包含:30种水果、植物叶片病害检测【VOC标注格式,包含训练集和验证集、类别json文件以及可视化脚本】,数据保存按照文件夹保存,经测试,可直接用作目标检测数据集,无需额外处理。 图像分辨率为600-2000的大分辨率RGB图片,数据集为水果、植物叶片病害检测。标注的边界框完整,每张图像均有数个目标。包含的水果植物有苹果、玉米、番茄、马铃薯、大豆、樱桃等等 【数据集介绍】30类别:玉米叶枯病、苹果锈叶、番茄霉叶等等 【数据总大小】427 MB 【数据集详情】data目录下分为两个目录,train为训练数据、val为验证数据,每个目录下各有两个子文件夹。images存放数据图片,labels目录存放标注文件。训练集共2254张图片和2254个xml解释文件。验证集共314张图片和314个xml解释文件 【json文件】30 类别的json字典文件 为了方便查看数据,提供了可视化py文件,随机传入一张图片即可绘制边界框,并且保存在当前目录。脚本无需更改,可以直接运行得到标注后的图像
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目标检测数据集:30种水果、植物叶片病害检测【VOC标注格式,包含训练集和验证集、类别json文件以及可视化脚本】 (2000个子文件)
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peaches-w-leaves_jpg.rf.8d20fc1bbf2f1b1bdd27bbc3e9a1bafb.xml 3KB
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