Making point clouds fun again

pyntcloud is a Python library for working with 3D point clouds leveraging the power of the Python scientific stack.

• Examples.
• Documentation

Installation

pip install pyntcloud

Quick Overview

You can access most of pyntcloud's functionality from its core class: PyntCloud.

With PyntCloud you can perform complex 3D processing operations with minimum lines of code. For example you can:

• Load a PLY point cloud from disk.
• Add 3 new scalar fields by converting RGB to HSV.
• Build a grid of voxels from the point cloud.
• Build a new point cloud keeping only the nearest point to each occupied voxel center.
• Save the new point cloud in numpy's NPZ format.

With the following concise code:

frompyntcloudimportPyntCloudcloud=PyntCloud.from_file("some_file.ply")
cloud.add_scalar_field("hsv")
voxelgrid_id=cloud.add_structure("voxelgrid", n_x=32, n_y=32, n_z=32)
new_cloud=cloud.get_sample("voxelgrid_nearest", voxelgrid_id=voxelgrid_id, as_PyntCloud=True)
new_cloud.to_file("out_file.npz")

Integration with other libraries

pyntcloud offers seamless integration with other 3D processing libraries.

You can create / convert PyntCloud instances from / to many 3D processing libraries using the from_instance / to_instance methods:

• Open3D

importopen3daso3dfrompyntcloudimportPyntCloud# FROM Open3Doriginal_triangle_mesh=o3d.io.read_triangle_mesh("diamond.ply")
cloud=PyntCloud.from_instance("open3d", original_triangle_mesh)
# TO Open3Dcloud=PyntCloud.from_file("diamond.ply")
converted_triangle_mesh=cloud.to_instance("open3d", mesh=True) # mesh=True by default

• PyVista

importpyvistaaspvfrompyntcloudimportPyntCloud# FROM PyVistaoriginal_point_cloud=pv.read("diamond.ply")
cloud=PyntCloud.from_instance("pyvista", original_point_cloud)
# TO PyVistacloud=PyntCloud.from_file("diamond.ply")
converted_triangle_mesh=cloud.to_instance("pyvista", mesh=True)