Comments (3)
What torch version are you using? There are problems with Torch 2.0.1. If so, you could upgrade to 2.1.2.
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You absolute genius! I was indeed on Torch 2.0.1. After running pip install -U torch==2.1.2
it worked! Training did seem to be a bit faster, but tough to notice due to colmap still :/ That said, what was most impressive was that the splat took up half the disk space than the one produced from the previous nerfstudio version. Literally went from 5.4 MB to 2.7 MB which is so huge when trying to render these splats on the client. Congrats on the awesome work, I am looking forward to regenerating all of my splats now, lol
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Closing this one for the related issue #3235
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Related Issues (20)
- Adding a New Method: Different (bad) Results than nerfacto while trying to inherit from nerfacto HOT 6
- Nerfstudio release v1.1.3 for breaking bugs HOT 2
- Can you introduce the new methods used by Splatfacto
- @torch_compile() for function get_viewmat() cause the bad training results. HOT 1
- ns-export gaussian-splat bug HOT 2
- How does nerfstudio obtain explicit output
- Error when using get_viewmat with @torch_compile() on Nvidia Orin NX HOT 3
- Integrate SAM model with Nerfstudio HOT 2
- Prefilter the invisible 3DGS before splatting on images
- "Downloading and Processing Data" section in Collab Notebook doesn't work HOT 1
- Splatfacto fails due to the model being train mode instead of eval mode HOT 1
- Georeferenced datasets processed on Metashape are loaded incorrectly/can't be loaded using splatfacto.
- Ability to disable Viser during training a nerf HOT 3
- ns-render BUG HOT 1
- Calling viewer from VS code HOT 2
- Question Regarding Image Downscaling Method HOT 1
- Rotation not applied when exporting with gaussina-splatting --obb-rotation
- Make `awscli` an optional dependency HOT 7
- zip nerf is not working 360.gin file is missing HOT 9
- Issues training pynerf (standard and synthetic)
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