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pyntcloud is a Python 3 library for working with 3D point clouds leveraging the power of the Python scientific stack.
- Examples (We encourage you to try out the examples by launching Binder.)
- Documentation
conda install pyntcloud -c conda-forgeOr:
pip install pyntcloudYou 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")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 defaultimport 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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