COCO数据集目标检测输出指标AP、AR、maxDets

一颗仙桃儿

于 2021-11-09 18:50:16 发布

阅读量1.8w

点赞数 42

CC 4.0 BY-SA版权

文章标签：目标检测 ar 计算机视觉

本文链接：https://blog.youkuaiyun.com/qq_40310050/article/details/121234145

最近在用retinanet进行一个实验，用的coco格式的数据集，输出的结果大致如下：

Loading and preparing results...
DONE (t=0.11s)
creating index...
index created!
Running per image evaluation...
Evaluate annotation type *bbox*
DONE (t=3.98s).
Accumulating evaluation results...
DONE (t=0.76s).
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.803
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.979
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.907
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.706
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.803
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.798
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.799
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.849
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.849
 Aver