retinanet模型训练后进行验证,验证指标得到的结果全是0

[161399695]

训练retinanet模型时,每个epoch结束后在验证集上验证总会出现下边的这种问题 Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0 这些指标全为0是咋回事呀(好难过)

[zhangjingxian1998]

去debug看看哪里有问题呗

[Ninnerking]

我也遇到了这个问题

[Ninnerking]

我之后启用混合精度训练就ok了

[HaronCHou]

https://github.com/WZMIAOMIAO/deep-learning-for-image-processing/issues/740#issuecomment-1649253697 参考这个呢，注意pascal_voc_classes.json文件夹里面的内容；RetinaNet和前面的网络结构不一样，类别是从0开始，不+1的。