kzampog/cilantro

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1135 stars · 203 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

cilantro is a lean, templated C++ library for processing 3D point cloud data, offering kd-trees, normal estimation, resampling, PCA, PLY I/O, RGBD conversion, convex hulls, and clustering algorithms. It emphasizes a clean API, minimal boilerplate, and extensibility across arbitrary numerical types and dimensions.

Use cases

• process 3d point clouds in c++
• register point clouds with icp
• segment point clouds
• compute convex hulls of point sets
• cluster point cloud data with k-means or mean-shift
• convert rgbd images to point clouds
• estimate surface normals from raw point clouds
• read and write ply point cloud files

When to choose

• you need a fast, header-friendly C++ alternative to PCL with less boilerplate
• you need general-dimension algorithms (kd-trees, clustering, convex hulls) beyond just 3D
• you want modular, templated point cloud pipelines with Eigen integration

When to avoid

• you need a Python-first point cloud workflow
• you require the full breadth of PCL's feature set or its ecosystem integrations
• you need GPU-accelerated point cloud processing out of the box

Facets

library · maturity active

computer-vision image-processing math data-visualization graphics computer-vision graphics robotics cpp windows cross-platform point-cloud icp ransac convex-hull clustering segmentation registration rgbd 3d kd-tree pca spectral-clustering mean-shift k-means model-fitting reconstruction algorithms linux macos

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