Render a Large Scene

gsplat is designed with efficiency in mind so it’s very suitable to render a large scene. For example here we mimic a large scene by replicating the Garden scene into a 9x9 grid, which results 30M Gaussians in total while gsplat still allows real-time rendering for it.

The main magic that allows this is a very simple trick: we disregard the Gaussians that are far away from the camera, by applying a small threshold (e.g., 3 pixel) to the projected Gaussian radius which is configurable in our rasterization() API as radius_clip.

With gsplat as CUDA Backend:

With diff-gaussian-rasterization as CUDA Backend:

Note: Similar to the nerfstudio viewer, our viewer automatically switch to low resolution if the rendering is slow.

The code for this example can be found under examples/:

# First train a 3DGS model
CUDA_VISIBLE_DEVICES=0 python simple_trainer.py default \
    --data_dir data/360_v2/garden/ --data_factor 4 \
    --result_dir ./results/garden

# View it in a viewer with gsplat
python simple_viewer.py --scene_grid 5 --ckpt results/garden/ckpts/ckpt_6999.pt --backend gsplat

# Or, view it with inria's backend (requires to insteall `diff-gaussian-rasterization`)
python simple_viewer.py --scene_grid 5 --ckpt results/garden/ckpts/ckpt_6999.pt --backend inria

# Warning: a large `--scene_grid` might blow up your GPU memory.