SemanticML v0.1.1

Semantic segmentation of 3D point clouds is the process of classifying each point in a point cloud into different semantic classes, such as buildings, roads, vegetation, water and others. One approach to accomplish this is by using Machine Learning techniques such as Random Forest ans Gradient Boosting classifiers.

This package provides an easy way to perform surpervised classification of 3D unorganized point clouds using ML algorithms without having to write many lines of code. The models can be easily trained and saved, then used to get predictions.