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Display, quality presets and the voxel view

Change how the data looks without changing the data - colour by any column, points or surface, a quality preset that suits the GPU, and a voxel view up to 2048 cells a side.

Where Properties › Display · Process › Voxelize… Tier Free CLI render --voxel

Every display option is free. Exporting voxels as glTF is Pro.

The Properties pane of Neurones 3D with the Display card open: point size, colour by RGB, Height or a scalar field, surfels, eye-dome lighting, the Eco, Balanced and Premium quality presets and the voxel view
The Properties pane: Display on top, then AI Analysis, Compare and Navigation.

When to use it

All the time. Colour by height to read a floor, by intensity to read a road, by confidence after a classification, by hag after a ground fit. Switch to crisp points to measure, to the surface to present. Drop to Eco on a weak GPU and to Premium for a screenshot.

Step by step

  1. Open Properties › Display (the right pane). Set Point size with the slider.
  2. Under Colour by, choose RGB, Height (a ramp on elevation), Normals, or any scalar field the cloud carries or N3D computed: intensity, classification, hag, confidence, deviation and so on.
  3. In the toolbar, Eye-dome lighting gives depth edges to raw points; Surface reconstruction turns the points into a continuous lit surface with hole infill (off gives crisp EDL points). Surfels in Display draws each point as a small oriented disc.
  4. Pick a Quality preset: Eco (no supersampling, no effects, a 3 million point budget, for integrated graphics), Balanced (effects on at native resolution) or Premium (2x supersampling, sharpening and every effect). Advanced effects holds ambient occlusion, hole infill, SSAA and sharpening one by one.
  5. For the voxel view, press the Voxel view chip in Display, or Process › Voxelize…. A Resolution slider appears: 40 to 2048 cells along the longest side, 140 by default. The cubes take the colour the cloud was showing.
  6. If the model or scan lies on its side, set Up axis at the top of Display (Z up, Y up, Y up flipped, X up, upside down).
  7. To export the voxel grid for a game engine or a DCC tool, use File › Export voxels as glTF….
A 43.5 million point interior laser scan rendered as crisp eye-dome-lit points
Eye-dome lit points: the classic survey look.
The interior scan drawn as a continuous lit surface rather than as points
The same points with surface reconstruction on.
Close view of photoreal Gaussian surfels where individual points blend into smooth surfaces
Surfels: points blend into surface, with no meshing step.
The interior scan voxelised into a block world at 260 voxels across
The voxel view, coloured by whatever the cloud was showing.

What it was measured at

Measured

The voxel view goes up to 2048 cells a side. Integrated GPUs start in Eco automatically on first launch.

From the command line

n3d-render-cli render --input scan.las --out height.png --color height
n3d-render-cli render --input scan.las --out points.png --points          # crisp EDL points, no surface
n3d-render-cli render --input scan.las --out blocks.png --voxel 256
n3d-render-cli export-voxel-gltf --input scan.las --out voxels.glb --res 160

Limits, stated

  • Display changes how the cloud is drawn, never the file. A colour ramp is not written into an export unless you tick the column itself.
  • Surfels are forced off in Eco.

Related questions

What hardware do I need?

A 64-bit Windows 10 or 11 PC with a GPU that supports DirectX 12 or Vulkan. Integrated graphics work: they start in the Eco quality preset, which drops supersampling and effects for smoothness. See system requirements.

Do I need a lot of memory?

Less than the file size. Point clouds are indexed out of core and streamed, so a cloud larger than your RAM still opens. Composing a large USD stage for the first time is the heaviest case measured: 6.5 GB peak for a 900,000-prim stage, after which every reopen reads a cache in 1.64 s.

More in the FAQ.

About

Why Neurones 3D exists.

Standing inside a 43.5 million point indoor laser scan rendered by Neurones 3D

I have spent years working with point clouds, and for most of them the software got in the way. I wanted one tool I would actually reach for every day: fast enough to enjoy, honest about what it does, and calm to use.

Neurones 3D started in Python, the way most of my research does. It worked, but it was heavy, and heavy tools quietly discourage you from opening them. So I rebuilt everything in Rust, from the file readers to the renderer, with one rule: stay frugal. A single small file, no cloud, no telemetry, billions of points on a laptop that is ten years old. In an age where every tool reaches for a data center, I wanted the opposite.

The goal is simple to say and hard to earn. One package that carries you from capture to understanding to deliverable, without exporting to five other programs along the way. Load a scan, a splat, a building, a phone video. See it, classify it, measure it, and send out something real. Together, in one place.

This is the tool I always wanted. I hope it becomes yours too.

Dr. Florent Poux 3D Geodata Academy

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