Hugues THOMAS

Hi @Trexzhou, First here is an answer to your first question. > Thank you for your response and suggestions! Meanwhile, I am trying to understand the function cpp_neighbors.batch_query() that was...

Now about your test. Here is a small scheme of your problem: ``` A = . B = + r = 2 |-------| cloud1 ----0---1---2---3---4---5---6---7---8---9---10-- | 1 . . ....

This is due to the dataset. The beams in Area_5 do not look like the beams in the other areas, and therefore, are never classified as such. If you use...

Hi @G-Anjanappa, The first thing I have to say is: there is something wrong with what you are doing from a scientific viewpoint. > For example, I am subsampling ceiling,...

@G-Anjanappa , So to answer your questions. > 1. I performed the sub-sampling based on labels for the S3DIS dataset as a step for data preparation before the training or...

> Could you please elaborate on the network detecting the change in density and using that as a feature to detect the objects? It would be helpful and interesting to...

I think the error comes from the fact that you did not have enough training points for one of your classes. It is a case I never encountered before, but...

Well at this point this is a valid research problem, I'll let you explore it and find the answers yourself. class_w is used here: https://github.com/HuguesTHOMAS/KPConv-PyTorch/blob/3d683b6bd6bf058135d3f9f155cd41595dc81c16/models/architectures.py#L306-L311 and you can set your...

> Suppose the training data had 12 semantic classes but the test data only 11 classes. Could you please help me understand how the network handles such cases? How IoUs...

> But what happens suppose the test set doesn't have points belonging to a class that was trained upon? We wouldn't know this prior to define the labels to ignore....