链接中提供模型精度测试的几点疑问？

[yukaizhou]

首先非常感谢博主的代码开源，感谢🙏。我的疑问是 您提供模型的33.5是在val2017上的精度吗？其次就是您说33.5的精度是在600px上得到的，但我看您代码中分为最大最小值，都不等于600，请问这是什么原因呢？期待您的回复，感谢！

[yukaizhou]

hi yhenon have you update the pretrained model ?thank in advance

[yukaizhou]

CUDA available: True
loading annotations into memory...
Done (t=0.57s)
creating index...
index created!
Loading and preparing results...
DONE (t=8.47s)
creating index...
index created!
Running per image evaluation...
Evaluate annotation type bbox
DONE (t=90.08s).
Accumulating evaluation results...
DONE (t=15.75s).
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.516
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.369
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.180
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.381
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.486
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.306
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.487
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.530
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.339
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.581
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.699

I just download the repost pth and the surce code,then get a more better map