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mathieuorhan / pointnet2_semantic

A pointnet++ fork, with focus on semantic segmentation of differents datasets
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Help me out! #4

Open OmarAhmadin opened 5 years ago

OmarAhmadin commented 5 years ago

Hello,

Please help me out. From what I understand; in order to feed my own dataset for semantic segmentation. I have to do the following:

1- I first feed my dataset to the PreprocessingSem3D (using main.cpp) in order to preprocess it. 2- Run train.py. 3- Use predict.py with feeding the best ckpt I have got.

Now, I have multiple questions:

1- Can I use class 0? (I noticed that zero is unlabeled and it is discarded into main.cpp for preprocessing.) I have only two classes. Either powerline or non-powerline points. It should be easier problem. But I did not get any good results. 2- Shall I pass my test data to the preprocessingSem3D before feeding it to prediction.py?? 3- After prediction.py I shall feed the output to interplation3D right?

Thanks.

luoxiaoliaolan commented 5 years ago

Hi! It's my honor to try to answer your questions.

  1. I think you can set the non-powerline points to class 0, and the powerline points to class 1.
  2. I have preprocessed my dataset(include train data and test data), so I think you should pass your test data to the preprocessingSem3D.
  3. Yes, you should feed the output to interplation3D, otherwise you will get the point cloud data after subsampling.