This is a small python binding to the pointcloud library. Currently, the following parts of the API are wrapped (all methods operate on XYZ) point types

• I/O and integration; saving and loading PCD files
• segmentation
• SAC
• smoothing
• filtering

The code tries to follow the Point Cloud API, and also provides helper function for interacting with numpy. For example (from tests/test.py)

import pcl
p = pcl.PointCloud()
p.from_array(np.array([[1,2,3],[3,4,5]], dtype=np.float32)))
seg = self.p.make_segmenter()
seg.set_model_type(pcl.SACMODEL_PLANE)
seg.set_method_type(pcl.SAC_RANSAC)
indices, model = seg.segment()

This release has been tested with

• pcl 1.5.1
• Cython 0.16

Point Cloud is a heavily templated API, and consequently mapping this into python using Cython is challenging.

It is written in Cython, and implements enough hard bits of the API (from Cythons perspective, i.e the template/smart_ptr bits) to provide a foundation for someone wishing to carry on.

.. autosummary::
   pcl.PointCloud
   pcl.Segmentation
   pcl.SegmentationNormal
   pcl.StatisticalOutlierRemovalFilter
   pcl.MovingLeastSquares

.. automodule:: pcl
   :members:
   :undoc-members: