数据集格式：Pascal VOC格式+YOLO格式(不包含分割路径的txt文件，仅仅包含jpg图片以及对应的VOC格式xml文件和yolo格式txt文件)
图片数量(jpg文件个数)：2199
标注数量(xml文件个数)：2199
标注数量(txt文件个数)：2199
标注类别数：44
所在github仓库：firc-dataset
标注类别名称(注意yolo格式类别顺序不和这个对应，而以labels文件夹classes.txt为准):["allysum","aphid","astillbe","beetle","bellflower","bellflower_L","black eyed susan","black eyed susan_L","bougainvillea","bougainvillea_L","bulbfly","calandulla","calendulla","carnation","caterpillar","commondaisy","coreopsis","cyclamen","cyclamenmites","daffodill","dahlia","daisy","dandelion","geranium","iris","leafhopper","leafminer","magnolia","marigold","mealybugs","pansy","primula","rananculus","rose","rose_L","slug","spidermite","sunflower","sunflower_L","thrips","tulip","waterlily","weevil","whitefly"]
每个类别标注的框数：
allysum (香雪球) 框数 = 163
aphid (蚜虫) 框数 = 77
astillbe (落新妇) 框数 = 258
beetle (甲虫) 框数 = 61
bellflower (风铃草) 框数 = 144
bellflower_L (风铃草_L) 框数 = 4
black eyed susan (黑心菊) 框数 = 338
black eyed susan_L (黑心菊_L) 框数 = 33
bougainvillea (三角梅/叶子花) 框数 = 99
bougainvillea_L (三角梅_L) 框数 = 8
bulbfly (球茎蝇) 框数 = 47
calandulla (金盏花) 框数 = 3
calendulla (金盏花) 框数 = 170
carnation (康乃馨) 框数 = 73
caterpillar (毛毛虫) 框数 = 44
commondaisy (普通雏菊) 框数 = 203
coreopsis (金鸡菊) 框数 = 182
cyclamen (仙客来) 框数 = 158
cyclamenmites (仙客来螨) 框数 = 13
daffodill (水仙花) 框数 = 118
dahlia (大丽花) 框数 = 89
daisy (雏菊) 框数 = 157
dandelion (蒲公英) 框数 = 82
geranium (天竺葵) 框数 = 228
iris (鸢尾花) 框数 = 77
leafhopper (叶蝉) 框数 = 44
leafminer (潜叶虫) 框数 = 16
magnolia (木兰/玉兰) 框数 = 169
marigold (万寿菊) 框数 = 458
mealybugs (粉蚧) 框数 = 74
pansy (三色堇) 框数 = 165
primula (报春花) 框数 = 345
rananculus (毛茛) 框数 = 63
rose (玫瑰/月季) 框数 = 267
rose_L (玫瑰_L) 框数 = 23
slug (蛞蝓) 框数 = 50
spidermite (红蜘蛛/叶螨) 框数 = 29
sunflower (向日葵) 框数 = 192
sunflower_L (向日葵_L) 框数 = 4
thrips (蓟马) 框数 = 84
tulip (郁金香) 框数 = 192
waterlily (睡莲) 框数 = 142
weevil (象鼻虫) 框数 = 24
whitefly (粉虱) 框数 = 138
总框数：5308
图片分辨率：多分辨率图片,如56x56,600x800等
使用标注工具：labelImg
标注规则：对类别进行画矩形框
重要说明：数据集没有划分训练验证测试集需自行划分
特别声明：本数据集不对训练的模型或者权重文件精度作任何保证
图片预览：
标注例子：
的核心原理与应用指南){kind=spacer}
