-
Notifications
You must be signed in to change notification settings - Fork 1.5k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Using custom number of points #482
Comments
+1, I met the same problem. 我怀疑可能是坐标系的问题 |
@Gragonfly @samiragarwala Have you solved the problem? I met the same problem... |
I also meet the same issues, but on Colmap dataset. However, if i increase the number of points like from 100 to 1000, this issus wont happened. So, I guess it was the problem during optimization? I also looking at it. |
could you tell me how to increase "the number of points" ? thanks! @ys31jp |
I face the same problem, by checking the code, I think the main reason leading to this problem is the "pruning". Sometimes, all Gaussians are pruned so that the number of gaussian is 0, and then, it may lead to this gradient computation error. Hope this suggestion could help you. |
I try to create a Colmap dataset with a single orthogonal camera. It is traced to the setting of the threshold for pruning large Gaussian kernels. If there is only one camera, the prune extent is 0 pruning everything. |
I have the same problem and the error throws alsways at the same Iteration (3100). It is happening with different colmap datasets. So far I tried datasets with roughly 7000 and 31000 initial points. |
We have the same problem,so do I when iter 3100,have you solved?thank you! |
You may have a bad initialization, no points fall in the camera views. @qianyuling-wl |
Hi! I was trying to initialise a custom number of points in the blender dataset reader but found runtime issues on doing the same. In particular, I am seeing issues such as
RuntimeError: Function _RasterizeGaussiansBackward returned an invalid gradient at index 2 - got [0, 0, 3] but expected shape compatible with [0, 16, 3]
when using more than 1 point andRuntimeError: Sizes of tensors must match except in dimension 1. Expected size 1 but got size 15 for tensor number 1 in the list.
when using a single point during initialisation. I would appreciate any insight about these issues. Thank you!The text was updated successfully, but these errors were encountered: