int8精度基本为0？

[HuKai97]

按照您的步骤，测试了yolov5和yolov8的fp32、fp16的精度都算正常，都降了一点，但是int8的精度非常低，这可能是什么原因呢？ Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.012 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.016 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.012 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.010 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.097 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 ] = 0.016 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.019 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.019 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.017 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.114 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000

[Melody-Zhou]

@HuKai97 从两方面考虑吧，一个是校准数据集另一个是校准算法，不过从你的精度来看大概率是校准数据集选择问题，按理来说 PTQ 量化精度不可能下降这么多，是不是你的校准数据没有包含所有类别，不能很好的表示整个数据集呢？