Thanks a lot for releasing the new version of your project!
I have a small note regarding the available checkpoint for the LiDAR-only model.
The checkpoint and corresponding cfg file mention the use of num_queries=900, but when loading the checkpoint it appears that it is actually trained with 600 queries;
size mismatch for pts_bbox_head.tgt_embed.weight: copying a param with shape torch.Size([600, 256]) from checkpoint, the shape in current model is torch.Size([900, 256]).size mismatch for pts_bbox_head.refpoint_embed.weight: copying a param with shape torch.Size([600, 3]) from checkpoint, the shape in current model is torch.Size([900, 3]).
For the LiDAR+camera checkpoints I don't see anything like this, so these are indeed with 900 queries.
Will you release the checkpoint for the LiDAR-only model with 900 queries? I assume this yields different results than a model with 600 queries.
Hi there,
Thanks a lot for releasing the new version of your project!
I have a small note regarding the available checkpoint for the LiDAR-only model. The checkpoint and corresponding cfg file mention the use of num_queries=900, but when loading the checkpoint it appears that it is actually trained with 600 queries;
size mismatch for pts_bbox_head.tgt_embed.weight: copying a param with shape torch.Size([600, 256]) from checkpoint, the shape in current model is torch.Size([900, 256]).
size mismatch for pts_bbox_head.refpoint_embed.weight: copying a param with shape torch.Size([600, 3]) from checkpoint, the shape in current model is torch.Size([900, 3]).
For the LiDAR+camera checkpoints I don't see anything like this, so these are indeed with 900 queries.
Will you release the checkpoint for the LiDAR-only model with 900 queries? I assume this yields different results than a model with 600 queries.
Thank you!