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Description
Description
First, thank you for creating such a wonderful project!
I’ve been trying to use [SugaR] to convert Gsplat models into mesh files. During the mesh generation training pipeline, I encountered an overflow error in the coarse rasterization phase. The command I ran was:
python train.py -s <COLMAP dataset path> -r "dn_consistency" --high_poly True --refinement_time "long" -c <GS Checkpoint Path>Observed Behavior
The console prints:
Bin size was too small in the coarse rasterization phase. This caused an overflow, meaning output may be incomplete.
To solve, try increasing max_faces_per_bin / max_points_per_bin, decreasing bin_size, or setting bin_size to 0 to use the naive rasterization.
Request
- Has anyone encountered and resolved this overflow error?
- Are there alternative rasterization strategies or flags that work better for high‐density Gsplat models?
- Is it possible to import Gsplat files generated by other pipelines (e.g., gaussian-splatting-lightning) into the SugaR training/conversion pipeline?
Thank you for any pointers! 😊
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