欢迎点云相关产学研的学者和团体加入我们。
笔者评:Python语言的粉丝们有福了,以后可以通过Python开发平台对PCL中点云相关算法进行使用了,目前并未完全封装,不过有点云获取IO操作、分割、滤波、
平滑等预处理。相信后期有高人继续维护和升级的。
Python bindings for the Point Cloud Library
We are proud to to announce the release of python-pcl Python bindings for PCL.
Now you can use the power and performance of PCL from the comfort of Python. Currently the following features of PCL, using PointXYZ point
clouds, are available;
•I/O and integration; saving and loading PCD files
•segmentation
•sample consensus model fittting (RANSAC + others, cylinders, planes, common geometry)
•smoothing (median least squares)
•filtering (voxel grid downsampling, passthrough, statistical outlier removal)
•exporting, importing and analysing pointclouds with numpy
An simple demonstration showing the statistical outlier filter:
import pcl
p = pcl.PointCloud()
p.from_file("table_scene_lms400.pcd")
fil = p.make_statistical_outlier_filter()
fil.set_mean_k (50)
fil.set_std_dev_mul_thresh (1.0)
fil.filter().to_file("inliers.pcd")
For a more complete example showing how to combine filtering, plane and cylinder segmentation (the code used to generate the logo above), see
this example.
For more information please see the examples, tests,…