Python library for working with 3D point clouds.
pyntcloud is a Python 3 library for working with 3D point clouds leveraging the power of the Python scientific stack.
conda install pyntcloud -c conda-forge
pip install pyntcloud
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:
from pyntcloud import PyntCloud cloud = 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:
import open3d as o3d from pyntcloud import PyntCloud # FROM Open3D original_triangle_mesh = o3d.io.read_triangle_mesh("diamond.ply") cloud = PyntCloud.from_instance("open3d", original_triangle_mesh) # TO Open3D cloud = PyntCloud.from_file("diamond.ply") converted_triangle_mesh = cloud.to_instance("open3d", mesh=True) # mesh=True by default
import pyvista as pv from pyntcloud import PyntCloud # FROM PyVista original_point_cloud = pv.read("diamond.ply") cloud = PyntCloud.from_instance("pyvista", original_point_cloud) # TO PyVista cloud = PyntCloud.from_file("diamond.ply") converted_triangle_mesh = cloud.to_instance("pyvista", mesh=True)
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