I have a machine learning model that uses csv with measured data about buildings: width, length, height etc. I use it to predict some features and it works properly.
I would like to drop csv with length, height and width, and I would like to use some kind of algorithm to parse 3d model into the ML algorithm.
The second reason is to try this approach with nonrectangular buildings, which are hard to describe in simple csv generated by humans.
I do not necessarily need the algorithm to read the width, length etc. but to be able to predict some values based on training set of 3d models acompanied by csv with results.
What should I look into? Where can I find information about this approach?