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which embedes positional information in the query_pos.
however, I don't understand the reason why does 2*(dim_t//2) has to be devided by 128, instead of the actual dimension pos_tensor has (e.g., 256 by default).
Hi, for question (1), why does 2*(dim_t//2) has to be devided by 128, since the position embedding performs on both the x and y direction, then concat.
Hi, thanks for sharing your wonderful work.
I got a question in here,
ConditionalDETR/models/transformer.py
Line 33 in ead865c
which embedes positional information in the query_pos.
however, I don't understand the reason why does
2*(dim_t//2)
has to be devided by 128, instead of the actual dimensionpos_tensor
has (e.g., 256 by default).ConditionalDETR/models/transformer.py
Line 38 in ead865c
Is it works correctly even
dim_t
is divided by 128?I would appreciate to be corrected !
And another question is,
when we do the calculation of the equation (1) in the paper,
ConditionalDETR/models/conditional_detr.py
Line 89 in ead865c
can I understand that the model would learn "offsets" from the corresponding reference points?
what is precise role of the reference points?
Thank you!
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