A viewer for gaussian-splatting reconstructions
Project description
Overview
A viewer and some tools to work with guassian splatting reconstructions. Currently will open .ply files and gaussian splatting workspaces from the original guassian-splatting implementation. Intended primarily for testing taichi-splatting
Example data
Some example scenes can be found from the official gaussian-splatting page. Under Pre-trained models.
splat-viewer
A gaussian splatting viewer. An example of some visualizations produced by this viewer can be seen:
Arguments
usage: splat-viewer [-h] [--model MODEL] [--device DEVICE] [--debug] model_path
positional arguments:
model_path workspace folder containing cameras.json, input.ply and point_cloud folder with .ply models
options:
-h, --help show this help message and exit
--model MODEL load model from point_clouds folder, default is latest iteration
--device DEVICE torch device to use
--debug enable taichi kernels in debug mode
Keyboard Controls
Switch View mode
- 1: normal rendering
- 2: render gaussian centers as points
- 3: render depth map
Show/hide
- 0 : cropped foreground
- 9 : initial points
- 8 : camera markers
Misc
- prntsc: save high-res snapshot into workspace directory
- shift return: toggle fullscreen
Camera
-
'[' : Prev camera
-
']' : Next camera
-
'=' : zoom in
-
'-' : zoom out
-
w/s a/d q/e : forward/backward left/right up/down
-
keypad plus/minus: navigate faster/slower
Animation
- space: add current viewpoint to animaiton sequence
- control-space: save current animation sequence to workspace folder
- return: animate current sequence
- shift plus/minus: animation speed faster/slower
splat-benchmark
A benchmark to test forward and backward passes of differentiable renderers.
Example splat-benchmark models/garden --sh_degree 1 --resize_image 1920
Arguments
usage: splat-benchmark [-h] [--device DEVICE] [--model MODEL] [--profile] [--debug] [-n N] [--tile_size TILE_SIZE] [--backward] [--sh_degree SH_DEGREE] [--no_sort] [--depth]
[--resize_image RESIZE_IMAGE] [--taichi]
model_path
positional arguments:
model_path workspace folder containing cameras.json, input.ply and point_cloud folder with .ply models
options:
-h, --help show this help message and exit
--device DEVICE torch device to use
--model MODEL model iteration to load from point_clouds folder
--profile enable profiling
--debug enable taichi kernels in debug mode
-n N number of iterations to render
--tile_size TILE_SIZE
tile size for rasterizer
--backward benchmark backward pass
--sh_degree SH_DEGREE
modify spherical harmonics degree
--no_sort disable sorting by scale (sorting makes tilemapping faster)
--depth render depth maps
--resize_image RESIZE_IMAGE
resize longest edge of camera image sizes
--taichi use taichi renderer
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