About test.
huixiancheng opened this issue · comments
Thank you for the realization, great job. I was wondering if you submitted the seq11-21 prediction results to test codalab?
As far as I know, there is a large difference between the valid and test of the Semantickitti dataset.
Moreover would you like to show me where does the code do the RS(Random Sampling).
As the author say in appendices:
https://github.com/tsunghan-mama/RandLA-Net-pytorch/blob/198f3cfff52f7ada9fc74baf73e1763c612fe043/dataset/semkitti_trainset.py#L39-L46
Look like is in here generate a key value of center_point and then use query to get number of cfg.num_points points. It's this mean RS(Random Sampling).?
- For question 1: Due to the long inference time, we do not evaluate our reimplementation models on seq 11-21. However, we appreciate your comment and admit that there might be a large performance gap between val & test set.
- For question 2: Yes.
Thanks a lot for your answer. Moreover, I want to raise your attention about this issues from offical repo? Have you check this part. Look like will a littile infuence the result.
Moreover, look like the way you caculate the loss is not similar to offical repo. This is the log from Hu .
log_train_SemanticKITTI_08.txt
And this is your repo loss log which I gain.
log_train.txt
Look like a little different.
hi@huixiancheng,if you inference on semantickitti test area,i got a process killed problem when i test on sequences 13 ,19,21.could you give me some seggestions?