A fast, chunk-friendly implementation of Naive Surface Nets on regular grids.
Surface Nets is an algorithm for extracting an isosurface mesh from a signed distance field sampled on a regular grid. It is nearly the same as Dual Contouring, but instead of using hermite (derivative) data to estimate surface points, Surface Nets will do a simpler form of interpolation (average) between points where the isosurface crosses voxel cube edges.
Benchmarks show that [surface_nets] generates about 20 million triangles per second on a single core of a 2.5 GHz Intel
Core i7. This implementation achieves high performance by using small lookup tables and SIMD acceleration provided by glam
when doing 3D floating point vector math.
High-quality surface normals are estimated by:
When working with sparse data sets, [surface_nets] can generate meshes for array chunks that fit together seamlessly. This
works because faces are not generated on the positive boundaries of a chunk. One must only apply a translation of the mesh
into proper world coordinates for given chunk.
```rust use fastsurfacenets::ndshape::{ConstShape, ConstShape3u32}; use fastsurfacenets::{surface_nets, SurfaceNetsBuffer};
// A 16^3 chunk with 1-voxel boundary padding. pub type ChunkShape = ConstShape3u32<18, 18, 18>;
// This chunk will cover just a single octant of a sphere SDF (radius 15). let mut sdf = [1.0; ChunkShape::SIZE as usize]; for i in 0u32..(ChunkShape::SIZE) { let [x, y, z] = ChunkShape::delinearize(i); sdf[i as usize] = ((x * x + y * y + z * z) as f32).sqrt() - 15.0; }
let mut buffer = SurfaceNetsBuffer::default(); surface_nets(&sdf, &ChunkShape {}, [0; 3], [17; 3], &mut buffer);
// Some triangles were generated. assert!(!buffer.indices.is_empty()); ```
License: MIT OR Apache-2.0