DownloadThis page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and cheaply) acquired from different sources. pyntcloud enables simple and interactive exploration of point cloud data, regardless of which sensor was used to generate it or what the use case is. Although it was built for being used on Jupyter Notebooks, the library is suitable for other kinds of uses. pyntcloud is composed of several modules (as independent as possible) that englobe common point cloud processing operations.
Features
- Most of the functionality of this modules can be accessed by the core class of the library
- Build a grid of voxels from the point cloud
- Build a new point cloud keeping only the nearest point to each occupied voxel center
- pyntcloud offers seamless integration with other 3D processing libraries
- You can create / convert PyntCloud instances from / to many 3D processing libraries
- We encourage you to try out the examples by launching Binder
Project Samples
