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：