This is a tiny MIT-licensed C library of image utilities for dealing with height maps, normal maps, distance fields, and the like. It has a very low-level API, where an "image" is simply a flat array of floats. It's pretty fast too, since it's parallelized with OpenMP.
Heman can do stuff like this:
- Create a random height field using simplex noise and FBM.
- Generate a normal map from a height map.
- Compute ambient occlusion from a height map.
- Generate a signed distance field (SDF).
- Export a 3D mesh in PLY format.
- Apply a color gradient to a heightmap.
- Generate a color gradient, given a list of control points.
- Compute diffuse lighting with an infinite light source.
- Generate a nicely-distributed list of points according to a density field.
Heman implements some really nice 21st-century algorithms:
- Ambient occlusion is generated using Sean Barrett's efficient method that makes 16 sweeps over the height field.
- Distance field computation uses the beautiful algorithm from Distance Transforms of Sampled Functions (Felzenszwalb and Huttenlocher).
- Density field samples are generated using Robert Bridson's Fast Poisson Disk Sampling in Arbitrary Dimensions.
Unit tests are performed using the Python bindings, which live in prideout/heman-python.
The above images were generated from code that looks like this:
// Generate an island shape using simplex noise and a distance field. heman_image* elevation = heman_generate_island_heightmap(1024, 1024, rand()); // Compute ambient occlusion from the height map. heman_image* occ = heman_lighting_compute_occlusion(elevation); // Visualize the normal vectors. heman_image* normals = heman_lighting_compute_normals(elevation); // Apply a color gradient. heman_image* gradient = heman_color_create_gradient(...); heman_image* albedo = heman_color_apply_gradient(elevation, -0.5, 0.5, grad); // Apply diffuse lighting. heman_image* final = heman_lighting_apply(elevation, albedo, ...);
For the unabridged version, see
test_lighting in test/test_heman.c.
Heman has no dependencies, so it should be easy just to incorporate the code directly into your project.
For building a shared library in OS X, you can do this:
brew install scons scons lib
Note that this will not use OpenMP or build any tests.
Linux is required for OpenMP and tests. If you are not using a Linux machine but you want OpenMP support, take a look at the provided Dockerfile.
There's a script in the repo, env.sh, that makes using Docker easy. It calls
docker-machine and builds a container. Here's how to use it:
brew install docker-machine . env.sh # Lots of stuff spews out as it builds the container... heman-bash # You're now inside the VM -- press enter twice for the prompt. scons && build/test_heman # You can now look at the generated images: ls build/*.png
Here are some to-be-done items:
- Provide "Exponentially Distributed Noise", in addition to Simplex.
- Flesh out the Python Bindings and provide docstrings.
- Implement a contour extractor:
heman_ops_extract_contour(image, threshold, thickness)
- this just does a Sobel operator, that's all
- More distance field stuff.
- Allow non-monochrome source images.
- Allow computation of unsigned, squared distance.
- Spherical distance.
- Smarter Mesh Output
- Create a hull from poisson samples
- Sobel + (Step => Sobel) => Density Field => Poisson Samples
- Do not use marching squares!
- Two meshes: overwater and underwater
- Provide gamma decode and encode functions.
- More noise routines!
- Bridson's Curl noise (and a routine that performs advection?)
- Worley noise (useful for billows as seen in Real-time Volumetric Cloudscapes of Horizon)
- Analytic noise normals
- Wavelet Noise
- heman_image_sample doesn't do any interpolation. Maybe it should at least do a 2x2 box filter.
- Provide functionality from Scalable Height-Field Self-Shadowing
- If we need more string handling, we can integrate SDS.
- Integrate aaOcean, or some other implementation of Tessendorf waves.
- If we need to read JSON, we might use this or this.
- There are cool data structures in http://concurrencykit.org/