[数据集][目标检测]狗种类检测数据集VOC+YOLO格式20578张120类别

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):20578

标注数量(xml文件个数):20578

标注数量(txt文件个数):20578

标注类别数:120

标注类别名称:["Chihuahua","Blenheim_spaniel","curly-coated_retriever","golden_retriever","Labrador_retriever","Chesapeake_Bay_retriever","German_short-haired_pointer","vizsla","English_setter","Irish_setter","Gordon_setter","Brittany_spaniel","papillon","clumber","English_springer","Welsh_springer_spaniel","cocker_spaniel","Sussex_spaniel","Irish_water_spaniel","kuvasz","schipperke","groenendael","malinois","briard","kelpie","komondor","toy_terrier","Old_English_sheepdog","Shetland_sheepdog","collie","Border_collie","Bouvier_des_Flandres","Rottweiler","German_shepherd","Doberman","miniature_pinscher","Greater_Swiss_Mountain_dog","Bernese_mountain_dog","Rhodesian_ridgeback","Appenzeller","Japanese_spaniel","EntleBucher","boxer","bull_mastiff","Tibetan_mastiff","French_bulldog","Great_Dane","Saint_Bernard","Eskimo_dog","malamute","Afghan_hound","Siberian_husky","affenpinscher","basenji","pug","Leonberg","Newfoundland","Great_Pyrenees","Samoyed","Pomeranian","chow","keeshond","Brabancon_griffon","Pembroke","basset","Cardigan","toy_poodle","miniature_poodle","standard_poodle","Mexican_hairless","dingo","dhole","African_hunting_dog","beagle","bloodhound","bluetick","black-and-tan_coonhound","Walker_hound","English_foxhound","redbone","borzoi","Maltese_dog","Irish_wolfhound","Italian_greyhound","whippet","Ibizan_hound","Norwegian_elkhound","otterhound","Saluki","Scottish_deerhound","Weimaraner","Staffordshire_bullterrier","American_Staffordshire_terrier","Bedlington_terrier","Border_terrier","Kerry_blue_terrier","Pekinese","Irish_terrier","Norfolk_terrier","Norwich_terrier","Yorkshire_terrier","wire-haired_fox_terrier","Lakeland_terrier","Sealyham_terrier","Airedale","Shih-Tzu","cairn","Australian_terrier","Dandie_Dinmont","Boston_bull","miniature_schnauzer","giant_schnauzer","standard_schnauzer","Scotch_terrier","Tibetan_terrier","silky_terrier","soft-coated_wheaten_terrier","West_Highland_white_terrier","Lhasa","flat-coated_retriever"]

每个类别标注的框数:

Afghan_hound 框数 = 287

African_hunting_dog 框数 = 213

Airedale 框数 = 207

American_Staffordshire_terrier 框数 = 172

Appenzeller 框数 = 164

Australian_terrier 框数 = 203

Bedlington_terrier 框数 = 194

Bernese_mountain_dog 框数 = 229

Blenheim_spaniel 框数 = 203

Border_collie 框数 = 161

Border_terrier 框数 = 174

Boston_bull 框数 = 192

Bouvier_des_Flandres 框数 = 156

Brabancon_griffon 框数 = 153

Brittany_spaniel 框数 = 155

Cardigan 框数 = 170

Chesapeake_Bay_retriever 框数 = 187

Chihuahua 框数 = 158

Dandie_Dinmont 框数 = 204

Doberman 框数 = 156

English_foxhound 框数 = 197

English_setter 框数 = 169

English_springer 框数 = 168

EntleBucher 框数 = 236

Eskimo_dog 框数 = 162

French_bulldog 框数 = 164

German_shepherd 框数 = 156

German_short-haired_pointer 框数 = 154

Gordon_setter 框数 = 166

Great_Dane 框数 = 166

Great_Pyrenees 框数 = 232

Greater_Swiss_Mountain_dog 框数 = 180

Ibizan_hound 框数 = 198

Irish_setter 框数 = 163

Irish_terrier 框数 = 184

Irish_water_spaniel 框数 = 158

Irish_wolfhound 框数 = 263

Italian_greyhound 框数 = 216

Japanese_spaniel 框数 = 202

Kerry_blue_terrier 框数 = 191

Labrador_retriever 框数 = 189

Lakeland_terrier 框数 = 207

Leonberg 框数 = 256

Lhasa 框数 = 191

Maltese_dog 框数 = 264

Mexican_hairless 框数 = 162

Newfoundland 框数 = 201

Norfolk_terrier 框数 = 180

Norwegian_elkhound 框数 = 204

Norwich_terrier 框数 = 211

Old_English_sheepdog 框数 = 176

Pekinese 框数 = 152

Pembroke 框数 = 199

Pomeranian 框数 = 223

Rhodesian_ridgeback 框数 = 184

Rottweiler 框数 = 153

Saint_Bernard 框数 = 180

Saluki 框数 = 223

Samoyed 框数 = 241

Scotch_terrier 框数 = 171

Scottish_deerhound 框数 = 246

Sealyham_terrier 框数 = 234

Shetland_sheepdog 框数 = 164

Shih-Tzu 框数 = 233

Siberian_husky 框数 = 215

Staffordshire_bullterrier 框数 = 163

Sussex_spaniel 框数 = 153

Tibetan_mastiff 框数 = 154

Tibetan_terrier 框数 = 212

Walker_hound 框数 = 162

Weimaraner 框数 = 167

Welsh_springer_spaniel 框数 = 156

West_Highland_white_terrier 框数 = 186

Yorkshire_terrier 框数 = 169

affenpinscher 框数 = 153

basenji 框数 = 234

basset 框数 = 187

beagle 框数 = 209

black-and-tan_coonhound 框数 = 159

bloodhound 框数 = 197

bluetick 框数 = 173

borzoi 框数 = 169

boxer 框数 = 154

briard 框数 = 155

bull_mastiff 框数 = 175

cairn 框数 = 205

chow 框数 = 203

clumber 框数 = 167

cocker_spaniel 框数 = 163

collie 框数 = 168

curly-coated_retriever 框数 = 163

dhole 框数 = 179

dingo 框数 = 170

flat-coated_retriever 框数 = 159

giant_schnauzer 框数 = 167

golden_retriever 框数 = 162

groenendael 框数 = 152

keeshond 框数 = 175

kelpie 框数 = 160

komondor 框数 = 163

kuvasz 框数 = 159

malamute 框数 = 208

malinois 框数 = 153

miniature_pinscher 框数 = 193

miniature_poodle 框数 = 161

miniature_schnauzer 框数 = 162

otterhound 框数 = 162

papillon 框数 = 210

pug 框数 = 228

redbone 框数 = 151

schipperke 框数 = 171

silky_terrier 框数 = 189

soft-coated_wheaten_terrier 框数 = 158

standard_poodle 框数 = 173

standard_schnauzer 框数 = 187

toy_poodle 框数 = 159

toy_terrier 框数 = 175

vizsla 框数 = 159

whippet 框数 = 235

wire-haired_fox_terrier 框数 = 166

总框数:22124

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

相关推荐
深度学习实战训练营1 小时前
基于CNN-RNN的影像报告生成
人工智能·深度学习
昨日之日20063 小时前
Moonshine - 新型开源ASR(语音识别)模型,体积小,速度快,比OpenAI Whisper快五倍 本地一键整合包下载
人工智能·whisper·语音识别
浮生如梦_3 小时前
Halcon基于laws纹理特征的SVM分类
图像处理·人工智能·算法·支持向量机·计算机视觉·分类·视觉检测
深度学习lover3 小时前
<项目代码>YOLOv8 苹果腐烂识别<目标检测>
人工智能·python·yolo·目标检测·计算机视觉·苹果腐烂识别
热爱跑步的恒川4 小时前
【论文复现】基于图卷积网络的轻量化推荐模型
网络·人工智能·开源·aigc·ai编程
阡之尘埃6 小时前
Python数据分析案例61——信贷风控评分卡模型(A卡)(scorecardpy 全面解析)
人工智能·python·机器学习·数据分析·智能风控·信贷风控
孙同学要努力8 小时前
全连接神经网络案例——手写数字识别
人工智能·深度学习·神经网络
Eric.Lee20218 小时前
yolo v5 开源项目
人工智能·yolo·目标检测·计算机视觉
其实吧39 小时前
基于Matlab的图像融合研究设计
人工智能·计算机视觉·matlab
丕羽9 小时前
【Pytorch】基本语法
人工智能·pytorch·python