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Custom data set #82
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Please check here for the config explanation. |
I only have two classes, with unbalance proportion of points, and independently of how I set the config parameters after 1 or 2 epochs of training the semantic part predicts zero points for the second class. Do you know why this could be? |
I'm also facing a similar issue with unbalanced points, I have 4 classes and only 1 of them is being classified. I even tried using the WeightedRandomSampler rather than the DistrubutedSampler but I'm still having the same issue |
I am also having same kind of issue. I also have unbalanced proportion of points in my datasets. I have 3 classes Leaf, stem and node. For instance, in one of my 3D model(16th model) the no .of points are as following:
I also tried changing many parameters in config file, updated weights according to class distribution ratio
to model/softgroup.py (on line 144) to balance the class imbalance but still the semantic part predicts to zero for the second and third class. |
@IgnacioSan22 @theshapguy did you guys manage to solve these issues?If yes, please help me as well. Thanks in advance. |
@thangvubk can you please maybe suggest us something regarding this issue? It would be immense help. Thank you in advance. |
On dataset with imbalanced point per class i have two suggestions.
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@thangvubk Thank you for your quick reply. How did you calculated those semantic weights for stpls3d? How can I do that for my custom dataset? |
Great work! |
Hi! Have you done this? And I also have the same question as you do. |
I'm trying to train the model with a completely different dataset. I'm struggling to set the values in the config file, is there some documentation about setting them correctly or their meaning/influence?
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