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ShichenLiu avatar ShichenLiu commented on July 21, 2024

Hi,

If you mean the id_to_name map, the number is the ShapeNet category id, you can find it under this site.

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qiao1025566574 avatar qiao1025566574 commented on July 21, 2024

No, I know this id_to_name map. For example, chair category has 6778 models, I see 70% for train, 20% for test and 10% for val.

I download Shapenet datasets from https://www.shapenet.org/. But I can't associate this dataset with Shapenet datasets from official website.

Every shapenet model file have a hash name, like '1b84dededd445058e44a5473032f38f' '8ea3fa037107ec737426c116c412c132'. Do you know these .npz file's hashaname?

I sort Shapenet dataset by file name, but these npz file have no law to keep. So I want to know how original author deal this file from official dataset.

Thank you for your reply !!

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ShichenLiu avatar ShichenLiu commented on July 21, 2024

Oh I see. Then you might be able to find some helpful information here :)

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qiao1025566574 avatar qiao1025566574 commented on July 21, 2024

Yes!!That‘s I need, thank you!

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zyz-1998 avatar zyz-1998 commented on July 21, 2024

Yes!!That‘s I need, thank you!
hello, I would like to ask you a question. When I load data during training, it takes up a lot of my memory. My memory configuration is only 16g. How should I set it to avoid this situation? I look forward to your reply

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qiao1025566574 avatar qiao1025566574 commented on July 21, 2024

You can adjust BATCH_SIZE to suitable value instead of read all the dataset once.
It is convenient that using class DataLoader in pytoch.

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