Skip to content
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

Scenes trained with MCMC method fail after conversion to .ksplat #422

Closed
williefalloon opened this issue Feb 13, 2025 · 2 comments
Closed

Comments

@williefalloon
Copy link

Hi, this issue has been occurring for some time and I haven't seen it mentioned here so want to bring it to your attention.

If these conditions are met, the scene will fail to load, or take a very long time to load.

  • Trained using MCMC profile in PostShot (default training profile in PS)
  • The scene has a high (but well under published limits) splat count
  • Conversion to ksplat

I have some files below with pass and fail cases from my testing.

Points to note:

  • It seems that the critical point is the ksplat conversion.
  • SH level settings do not affect pass or fails.
  • Scenes trained with the ADC profile in PostShot and cropped do not have the issue.
  • The scenes often do load eventually, but CPU usage is at max for quite a long time before it succeeds.
@mkkellogg
Copy link
Owner

I think it might have something to do with the dimensions of your scene, which appear to be somewhat large, which can be addressed by changing the "block size" parameter when converting (bigger block sizes work better for scenes with larger dimensions). I used a block size of 20 with a bucket size of 512 and that seemed to work well. My .ksplat compression scheme is fairly janky, so it doesn't automatically handle non-optimal conditions very well 🙂

@mkkellogg
Copy link
Owner

I'll close this for now, but let me know if you know any more help

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants