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output masks consistently showing the same structure #60

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aryaabdi opened this issue Mar 20, 2023 · 5 comments
Open

output masks consistently showing the same structure #60

aryaabdi opened this issue Mar 20, 2023 · 5 comments

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@aryaabdi
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@aryaabdi aryaabdi changed the title Thank you for this interesting work. I have trained this model from scratch using medical images. When evaluating the model, all the output masks (# of masks used = 8) consistently show the same structure with different intensity. Have you seen this issue using natural images? Any idea what could cause this? Thank you. output masks consistently showing the same structure Mar 23, 2023
@aryaabdi
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Thank you for this interesting work. I have trained this model from scratch using medical images. When evaluating the model, all the output masks (# of masks used = 8) consistently show the same structure with different intensity. Have you seen this issue using natural images? Any idea what could cause this? Thank you.

@mbehjati
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Hi @aryaabdi,
Did you manage to solve the problem you mentioned? I'm getting a similar behavior.

@MohammadHossein-Bahari
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I get the same issue. @xvjiarui Can you help please?

@xvjiarui
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Hi all,

Sorry for the late reply. If you are training with specific domain images, I would suggest you start with pre-training on large scale natural images first. And the contrastive loss needs large batch size and large dataset to work.

@aryaabdi
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I tried training from scratch and also from the pre-trained (on natural images) model. The latter performed better. However, I realized the contrastive loss is not going to be effective if the number of entities within a batch is limited. I believe @xvjiarui can use a very large batch size because the training dataset contains many different entities. For example, gcc3m contains ~16k different entities. This was not the case in my training dataset and I think that is why I was not getting the desired behavior. Hope this helps.

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4 participants