街景目標檢測數據集4813張VOC+YOLO格式

數據集格式：VOC格式+YOLO格式
壓縮包內含：3個文件夾，分別存儲圖片、xml、txt文件
JPEGImages文件夾中jpg圖片總計：4813
Annotations文件夾中xml文件總計：4813
labels文件夾中txt文件總計：4813
標籤種類數：26
標籤名稱:["bicycle","building","bus","car","cctv","crosswalk","curb","guardrail","lanemarking","manhole","motorcycle","obstacle","parking","person","pole","road","road-sign","safety-sign","sidewalk","speed-bump","street-light","terrain","traffic light","traffic-sign","truck","utility-pole"]
標籤中文對照：“自行車”、“建築”、“公共汽車”、“汽車”、“閉路電視”、“人行橫道”、“路緣”、“護欄”、“車道標記”、“下水井”、“摩托車”、“障礙物”、“停車場”、“人”、“杆”、“道路”、“路標”、“安全標誌”、“人行道”、“減速帶”、“路燈”、“地形”、“交通燈”、“車輛標誌”、”卡車“電線杆”]
每個標籤的框數（注意yolo格式類別順序不和這個對應，而以labels文件夾classes.txt為準）：
bicycle 框數 = 106
building 框數 = 4898
bus 框數 = 107
car 框數 = 8815
cctv 框數 = 141
crosswalk 框數 = 396
curb 框數 = 241
guardrail 框數 = 612
lanemarking 框數 = 783
manhole 框數 = 886
motorcycle 框數 = 517
obstacle 框數 = 344
parking 框數 = 485
person 框數 = 1952
pole 框數 = 31
road 框數 = 4405
road-sign 框數 = 510
safety-sign 框數 = 453
sidewalk 框數 = 4964
speed-bump 框數 = 586
street-light 框數 = 686
terrain 框數 = 53
traffic light 框數 = 317
traffic-sign 框數 = 40
truck 框數 = 784
utility-pole 框數 = 1287
總框數：34399
圖片清晰度（分辨率：像素）：清晰
圖片是否增強：是
標籤形狀：矩形框，用於目標檢測識別
重要説明：暫無021
特別聲明：本數據集不對訓練的模型或者權重文件精度作任何保證，數據集只提供準確且合理標注
標註及圖片情況如下：