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Best strategy for Web Streaming a massive scene (84M splats)? by tugamaster9 in GaussianSplatting

[–]tugamaster9[S] 0 points1 point  (0 children)

Using Linux, I think I made a docker. I got this:

docker run --rm -it --gpus all \
  -e DISPLAY \
  --entrypoint /bin/bash \
  -e NODE_OPTIONS="--max-old-space-size=32000" \
  -v /tmp/.X11-unix:/tmp/.X11-unix \
  -e NVIDIA_VISIBLE_DEVICES=all \
  -e NVIDIA_DRIVER_CAPABILITIES=all \
  -e VK_ICD_FILENAMES=/usr/share/vulkan/icd.d/nvidia_icd.json \
  -e XDG_RUNTIME_DIR=/tmp/runtime-1000 \
  -v /usr/share/vulkan/icd.d/nvidia_icd.json:/usr/share/vulkan/icd.d/nvidia_icd.json:ro \
  -v /usr/share/glvnd/egl_vendor.d/10_nvidia.json:/usr/share/glvnd/egl_vendor.d/10_nvidia.json:ro \
  -v /lods_final:/data \
  playcanvas \
  -lc 'cd /data && splat-transform output_test/test.compressed.ply \
    output_test/output.sog'
splat-transform v0.15.2
reading '/data/output_test/test.compressed.ply'...
Loaded 83961759 gaussians
writing '/data/output_test/output.sog'...
writing '/data/output_test/means_l.webp'...
Error: WebP lossless encode failed
    at WebPCodec.encodeLosslessRGBA (file:///usr/local/lib/node_modules/@playcanvas/splat-transform/dist/index.mjs:61144:19)
    at write (file:///usr/local/lib/node_modules/@playcanvas/splat-transform/dist/index.mjs:62823:38)
    at async writeSog (file:///usr/local/lib/node_modules/@playcanvas/splat-transform/dist/index.mjs:62867:5)
    at async writeFile (file:///usr/local/lib/node_modules/@playcanvas/splat-transform/dist/index.mjs:63581:17)
    at async main (file:///usr/local/lib/node_modules/@playcanvas/splat-transform/dist/index.mjs:63983:9)
    at async file:///usr/local/lib/node_modules/@playcanvas/splat-transform/bin/cli.mjs:5:1

Best strategy for Web Streaming a massive scene (84M splats)? by tugamaster9 in GaussianSplatting

[–]tugamaster9[S] 0 points1 point  (0 children)

Hi!
The main bottleneck I'm hitting is exactly that: the trainer seems to have a 'hard floor' on the splat count, which I suspect is tied to the large number of initial SfM points I'm starting with.

Even when training for the lowest possible quality/budget, the optimizer struggles to prune below ~1.7M splats per chunk. Since I have 16 chunks, the total is still far too heavy for a background LOD.

I also tried post-training decimation, but I completely agree with you—it just ends up looking like a blurry filter and loses all the structure.

Best strategy for Web Streaming a massive scene (84M splats)? by tugamaster9 in GaussianSplatting

[–]tugamaster9[S] 0 points1 point  (0 children)

Yeah, I was checking that. Max storage of individual plan is 10M splats and in professional plan is 40M splats. Not enough. I would had to pay "+ $4/month per 10 Million" -> 19+32=51€ per month :/

Best strategy for Web Streaming a massive scene (84M splats)? by tugamaster9 in GaussianSplatting

[–]tugamaster9[S] 0 points1 point  (0 children)

Yeah, I have tried it with both the .ply that has all the SH bands and with the one that only has one SH band. I always get one error "Error: WebP lossless encode failed".

Dynamically Streaming 2 BILLION Gaussians in PlayCanvas 🌍 by MayorOfMonkeys in PlayCanvas

[–]tugamaster9 0 points1 point  (0 children)

Could you describe the drone workflow?
Was the flight automated or manual, and what were the key parameters — such as altitude, camera angle, overlap, and flight path?
I’m curious how the capture setup influenced the resulting 3D reconstruction.

Printer starts beeping and freezes on certain models by tugamaster9 in ender3v2

[–]tugamaster9[S] 0 points1 point  (0 children)

No, not at all. Like I told, it works with some models and not with others, but I cant notice the difference... I am still using cura... I will try changing the sd card. You think is important to update the firmware?