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Thank you for sharing your work! I'm trying to replicate results on a 12 GB GPU by reducing the num_frames and num_queries parameters. However, I came across the following error:
outputs_seg_masks = outputs_seg_masks.reshape(1,360,outputs_seg_masks.size(-2),outputs_seg_masks.size(-1))
RuntimeError: shape '[1, 360, 75, 76]' is invalid for input of size 1710000
I pinpointed the issue to Line 126, where I think 360 should be replaced with self.vistr.num_queries. Could you correct this in your release?
Also, can you explain what 24 denotes in Line 115?
Thanks!
The text was updated successfully, but these errors were encountered:
Thank you for sharing your work! I'm trying to replicate results on a 12 GB GPU by reducing the num_frames and num_queries parameters. However, I came across the following error:
outputs_seg_masks = outputs_seg_masks.reshape(1,360,outputs_seg_masks.size(-2),outputs_seg_masks.size(-1))
RuntimeError: shape '[1, 360, 75, 76]' is invalid for input of size 1710000
I pinpointed the issue to Line 126, where I think 360 should be replaced with self.vistr.num_queries. Could you correct this in your release?
Also, can you explain what 24 denotes in Line 115?
Thanks!
could you get any results, after correct the hardcode?
I keep got wrong prediction class and bbox results.
Appreciate it if you can help me.
Thx
@anirudh-chakravarthy Thanks very much for your advice! But as there has been a long time and I have no extra time to review the code now, I will correct it in the future.
Hi,
Thank you for sharing your work! I'm trying to replicate results on a 12 GB GPU by reducing the
num_frames
andnum_queries
parameters. However, I came across the following error:I pinpointed the issue to Line 126, where I think 360 should be replaced with
self.vistr.num_queries
. Could you correct this in your release?Also, can you explain what 24 denotes in Line 115?
Thanks!
The text was updated successfully, but these errors were encountered: