Closed zhanghaoyu816 closed 3 weeks ago
When I attempted to replicate your method on DDP dataset, I encountered several potential bugs and some questions, which I have listed here for reference.
depth_weight_mask_margin
defined in L147 refers Config.depth_rank_margin
? If so, they should be the same name.self.images
is being used before it is declared, which leads to an error.Ellipsis
? It seems not cause a program error, but it is highlighted in red as a warning in VSCodeConfig.batch_size = 4096
), I found that the memory usage has exceeded 40 GB!Is this a reasonable situation?I've uploaded the code get_kpts_prior.py
that generates the keypoint prior, and you can follow the instructions to generate the relevant data.
1 & 2: The related bug has been fixed(1ea44535befb8a0a3ffe783a8f48f20f4be0c98c), thanks for the heads up.
3: This is the code in the original RegNeRF, and removing it will have no effect.
4: Jax's mechanism is to pre-allocate more GPU memory, if you don't need it to pre-allocate, you can refer to the official documentation to set it up.
Thanks for your nice work! I would like to validate your method on other indoor datasets, but I'm not sure how to get the keypoint-pairs prior of dataset. You mentioned in your paper that you used LoFTR to extract feature point matches and did some other post-processing, but I'm still not sure of the process. So could you please release the code of generating prior so that I can test your method on some other dataset. Thanks a lot!