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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)：6675

标注数量(xml文件个数)：6675

标注数量(txt文件个数)：6675

标注类别数：36

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):["AW cola","Beijing Beef","Chow Mein","Fried Rice","Hashbrown","Honey Walnut Shrimp","Kung Pao Chicken","String Bean Chicken Breast","Super Greens","The Original Orange Chicken","White Steamed Rice","black pepper rice bowl","burger","carrot_eggs","cheese burger","chicken waffle","chicken_nuggets","chinese_cabbage","chinese_sausage","crispy corn","curry","french fries","fried chicken","fried_chicken","fried_dumplings","fried_eggs","mango chicken pocket","mozza burger","mung_bean_sprouts","nugget","perkedel","rice","sprite","tostitos cheese dip sauce","triangle_hash_brown","water_spinach"]

每个类别标注的框数：

AW cola 框数 = 250

Beijing Beef 框数 = 530

Chow Mein 框数 = 108

Fried Rice 框数 = 331

Hashbrown 框数 = 141

Honey Walnut Shrimp 框数 = 233

Kung Pao Chicken 框数 = 624

String Bean Chicken Breast 框数 = 362

Super Greens 框数 = 101

The Original Orange Chicken 框数 = 268

White Steamed Rice 框数 = 692

black pepper rice bowl 框数 = 220

burger 框数 = 105

carrot_eggs 框数 = 793

cheese burger 框数 = 105

chicken waffle 框数 = 99

chicken_nuggets 框数 = 708

chinese_cabbage 框数 = 1115

chinese_sausage 框数 = 1139

crispy corn 框数 = 173

curry 框数 = 758

french fries 框数 = 231

fried chicken 框数 = 394

fried_chicken 框数 = 1685

fried_dumplings 框数 = 621

fried_eggs 框数 = 1448

mango chicken pocket 框数 = 109

mozza burger 框数 = 178

mung_bean_sprouts 框数 = 1653

nugget 框数 = 130

perkedel 框数 = 374

rice 框数 = 2499

sprite 框数 = 24

tostitos cheese dip sauce 框数 = 20

triangle_hash_brown 框数 = 1197

water_spinach 框数 = 1412

总框数：20830

使用标注工具：labelImg

标注规则：对类别进行画矩形框

重要说明：暂无

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，数据集只提供准确且合理标注

图片预览：

标注例子：