[数据集][目标检测]垃圾目标检测数据集VOC格式14963张44类别

数据集格式:Pascal VOC格式(不包含分割的txt文件,仅仅包含jpg图片和对应的xml)

图片数量(jpg文件个数):14963

标注数量(xml文件个数):14963

标注类别数:44

标注类别名称:["toiletries","plastic utensils","seasoning bottles","leftovers","chopsticks","ceramic utensils","pots","metal utensils","cutting boards","old clothes","expired drugs","fish bones","metal food cans","peels and pulp","cartons and cartons","plug wires","plastic clothes hangers","vegetable leaves","glassware","tea dregs","shoes","disposable fast food boxes","eggshells","plush toys","metal kitchenware","power bank","dry batteries","pull cans","plastic toys","garbage cans","Wine bottle","defaced paper","ointment","big bone","express paper bag","defaced plastic","edible oil barrel","cigarette butts","beverage bottle","bag","flower pot","pillow","book paper","toothpick"]

对应中文名称:

"洗护用品", "塑料器皿", "调料瓶", "剩饭剩菜", "筷子", "陶瓷器皿", "锅", "金属器皿", "砧板", "旧衣服", "过期药物", "鱼骨", "金属食品罐", "果皮果肉", "纸盒纸箱", "插头电线", "塑料衣架", "菜帮菜叶", "玻璃器皿", "茶叶渣", "鞋", "一次性快餐盒", "蛋壳", "毛绒玩具", "金属厨具", "充电宝", "干电池", "易拉罐", "塑料玩具", "垃圾桶","酒瓶", "污损用纸", "软膏", "大骨头", "快递纸袋", "污损塑料", "食用油桶", "烟蒂", "饮料瓶", "包", "花盆", "枕头", "书籍纸张", "牙签"

每个类别标注的框数:

toiletries count = 1030

plastic utensils count = 666

seasoning bottles count = 543

leftovers count = 1414

chopsticks count = 817

ceramic utensils count = 2662

pots count = 530

metal utensils count = 341

cutting boards count = 466

old clothes count = 394

expired drugs count = 710

fish bones count = 525

metal food cans count = 400

peels and pulp count = 1052

cartons and cartons count = 623

plug wires count = 1277

plastic clothes hangers count = 325

vegetable leaves count = 984

glassware count = 878

tea dregs count = 409

shoes count = 463

disposable fast food boxes count = 329

eggshells count = 458

plush toys count = 655

metal kitchenware count = 284

power bank count = 410

dry batteries count = 445

pull cans count = 414

plastic toys count = 439

garbage cans count = 108

Wine bottle count = 346

defaced paper count = 227

ointment count = 418

big bone count = 413

express paper bag count = 248

defaced plastic count = 1237

edible oil barrel count = 446

cigarette butts count = 433

beverage bottle count = 371

bag count = 442

flower pot count = 211

pillow count = 382

book paper count = 206

toothpick count = 156

使用标注工具:labelImg

标注规则:对类别进行画矩形框

重要说明:类别全是英文不用担心标签中文问题,且数据集经过标注校验保证无错误标注

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

下载地址:

https://download.csdn.net/download/FL1623863129/85682652

相关推荐
橘子师兄18 分钟前
C++AI大模型接入SDK—ChatSDK封装
开发语言·c++·人工智能·后端
桂花很香,旭很美19 分钟前
基于 MCP 的 LLM Agent 实战:架构设计与工具编排
人工智能·nlp
Christo320 分钟前
TFS-2026《Fuzzy Multi-Subspace Clustering 》
人工智能·算法·机器学习·数据挖掘
五点钟科技28 分钟前
Deepseek-OCR:《DeepSeek-OCR: Contexts Optical Compression》 论文要点解读
人工智能·llm·ocr·论文·大语言模型·deepseek·deepseek-ocr
人工智能AI技术31 分钟前
【C#程序员入门AI】本地大模型落地:用Ollama+C#在本地运行Llama 3/Phi-3,无需云端
人工智能·c#
2501_9416012136 分钟前
Yolov10n多骨干网络多尺度注意力机制__垃圾分类目标检测系统开发与应用
yolo·目标检测·分类
Agentcometoo40 分钟前
智能体来了从 0 到 1:规则、流程与模型的工程化协作顺序
人工智能·从0到1·智能体来了·时代趋势
工程师老罗43 分钟前
什么是目标检测?
人工智能·目标检测·计算机视觉
jarreyer44 分钟前
【AI 编程工具】
人工智能·编程工具
阿杰学AI1 小时前
AI核心知识75——大语言模型之MAS (简洁且通俗易懂版)
人工智能·ai·语言模型·自然语言处理·agent·多智能体协作·mas