coco数据集的评价指标

Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.000
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.000
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.000
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000

 使用centernet代码运行test.py文件对目标检测任务的最终结果进行评估,结果如上图所示。那每一行都代表什么呢?

AP:查准率

IOU=0.50:0.95:表示IOU从0.5到0.95,步长,0.05,即IOU=0.5\0.55\0.6\0.65……0.95共十种IOU,这里将这个10中IOU计算后取了平均值

area:表示目标检测的物体是达吾提还是小物体,大小物体的划分依据

APsmall                       % AP for small objects: area < 32^2

APmedium                   % AP for medium objects: 32^2 < area < 96^2

APlarge                        % AP for large objects: area > 96^2

masDets=100:表示一张图中能检测到的最多的物体数量