特别注意数据集中里面图片都是从大模型生成的视频截图的，注意查看图片预览
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)：9366
标注数量(xml文件个数)：9366
标注数量(txt文件个数)：9366
标注类别数：69
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):["Apple","Apple_sliced","Book","Book_opened","Bottle","Bottle_filled","Bowl","Bowl_filled","Bread","Bread_cooked_sliced","Bread_sliced","ButterKnife","Cabinet","Cabinet_opened","CoffeeMachine","CounterTop","CreditCard","Cup","Cup_filled","DishSponge","Drawer","Drawer_opened","Egg","Egg_cooked_sliced","Egg_sliced","Faucet","Floor","Fork","Fridge","Fridge_opened","GarbageCan","HousePlant","Kettle","Knife","Lettuce","Lettuce_sliced","LightSwitch","Microwave","Microwave_opened","Mug","Mug_filled","Pan","PaperTowelRoll","PepperShaker","Plate","Pot","Pot_filled","Potato","Potato_cooked","Potato_cooked_sliced","Potato_sliced","SaltShaker","Shelf","ShelvingUnit","Sink","SoapBottle","Spatula","Spoon","Statue","Stool","StoveBurner","StoveKnob","Toaster","Tomato","Tomato_sliced","Vase","Window","WineBottle","WineBottle_filled"]
每个类别标注的框数：
Apple（苹果）框数 = 634
Apple_sliced（苹果切片）框数 = 837
Book（书本）框数 = 1575
Book_opened（打开的书本）框数 = 332
Bottle（瓶子）框数 = 1355
Bottle_filled（装满的瓶子）框数 = 344
Bowl（碗）框数 = 1873
Bowl_filled（装满的碗）框数 = 458
Bread（面包）框数 = 2813
Bread_cooked_sliced（熟面包切片）框数 = 230
Bread_sliced（面包切片）框数 = 5264
ButterKnife（黄油刀）框数 = 1802
Cabinet（橱柜）框数 = 16998
Cabinet_opened（打开的橱柜）框数 = 1576
CoffeeMachine（咖啡机）框数 = 2122
CounterTop（台面）框数 = 10326
CreditCard（信用卡）框数 = 678
Cup（杯子）框数 = 2169
Cup_filled（装满的杯子）框数 = 447
DishSponge（洗碗海绵）框数 = 1023
Drawer（抽屉）框数 = 14301
Drawer_opened（打开的抽屉）框数 = 696
Egg（鸡蛋）框数 = 222
Egg_cooked_sliced（熟鸡蛋切片）框数 = 344
Egg_sliced（鸡蛋切片）框数 = 1239
Faucet（水龙头）框数 = 1982
Floor（地板）框数 = 6408
Fork（叉子）框数 = 2223
Fridge（冰箱）框数 = 1896
Fridge_opened（打开的冰箱）框数 = 317
GarbageCan（垃圾桶）框数 = 989
HousePlant（室内植物）框数 = 2044
Kettle（水壶）框数 = 2625
Knife（刀）框数 = 3119
Lettuce（生菜）框数 = 1959
Lettuce_sliced（生菜切片）框数 = 5407
LightSwitch（电灯开关）框数 = 370
Microwave（微波炉）框数 = 1856
Microwave_opened（打开的微波炉）框数 = 371
Mug（马克杯）框数 = 1470
Mug_filled（装满的马克杯）框数 = 252
Pan（平底锅）框数 = 3033
PaperTowelRoll（厨房纸巾卷）框数 = 1679
PepperShaker（胡椒瓶）框数 = 1187
Plate（盘子）框数 = 1589
Pot（锅）框数 = 2362
Pot_filled（装满的锅）框数 = 911
Potato（土豆）框数 = 1327
Potato_cooked（熟土豆）框数 = 385
Potato_cooked_sliced（熟土豆切片）框数 = 379
Potato_sliced（土豆切片）框数 = 1089
SaltShaker（盐瓶）框数 = 1319
Shelf（搁板）框数 = 7509
ShelvingUnit（货架单元）框数 = 3332
Sink（水槽）框数 = 3715
SoapBottle（皂液瓶）框数 = 2083
Spatula（锅铲）框数 = 1033
Spoon（勺子）框数 = 2356
Statue（雕像）框数 = 1814
Stool（凳子）框数 = 2839
StoveBurner（炉灶燃烧器）框数 = 7571
StoveKnob（炉灶旋钮）框数 = 3041
Toaster（烤面包机）框数 = 1855
Tomato（西红柿）框数 = 1340
Tomato_sliced（西红柿切片）框数 = 3644
Vase（花瓶）框数 = 2360
Window（窗户）框数 = 3616
WineBottle（葡萄酒瓶）框数 = 1058
WineBottle_filled（装满的葡萄酒瓶）框数 = 1324
总框数：168696
图片分辨率：720x720
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：
