Pointnet_Pointnet2_pytorch
Pointnet_Pointnet2_pytorch copied to clipboard
The scene semantic segmentation IoU is 0
Thank you very much for your contribution!
-
I would like to ask why the IoU of one of the types has always been 0 when I use pointnet++ to do my own point cloud data semantic segmentation (binary classification), but it is normal for the same data to be semantically segmented with pointnet?
-
My dataset is only half the size of the S3DIS dataset, and the point cloud density is similar, why is the training time of pointnet and pointnet++ very long, an average of 2 hours for an epoch?
My device is GPU3060-12G VR: 12 GB CPU Intel(R) Xeon(R) CPU E5-2686 v4 RAM: 31G 12 cores

1、针对其中一种类型的IoU总是0的问题,在偶然的机会下,我通过对原始数据进行Min-Max归一化操作解决了,可能的原因是道路、输电线路等狭长的点云数据在x、y、z方向上的差异较大,导致后续ScannetDatasetWholeScene()中每个block中样本类别不均衡,甚至某些类缺失
2、苦于训练时间较长的烦恼,将相关代码仔细地过了几遍,我发现ScannetDatasetWholeScene()中block_size、stride这两个参数对训练时间的影响最大,在保持一定的比例(0.5)前提下,增大参数,可以极大地提高训练效率,40分钟一个epoch