python点云处理模块_pyntcloud是一个用于处理3D点云的Python库
Making point clouds fun again
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.)
Installation
conda install pyntcloud -c conda-forge
Or:
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:
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)