laserchicken

• Find neighboring points in your point cloud and describe them as feature values
• Filter points spatially or by attribute
• Normalize height for every point

Laserchicken is a user-extendable, cross-platform Python tool for extracting statistical properties (features in machine learning jargon) of flexibly defined subsets of point cloud data.
Laserchicken loads a point-cloud from a LAS or LAZ or PLY file. After this, it can filter points by various criteria, and it can normalize the height. Laserchicken can load another point cloud, which contains targets. For every target point, Laserchicken computes its neighbors. Based on the list of neighbors, Laserchicken extracts features that effectively describe the neighborhood of each target point.