notebooks/3D-segmentation-point-clouds/README.md

Part Segmentation of 3D Point Clouds with OpenVINO™

Point clouds are an important type of geometric data structure. OpenVINO can directly consume point cloud data and perform inference with it.

Notebook Contents

This notebook demonstrates how to process point cloud data and run 3D Part Segmentation with OpenVINO. The inputs of this task are a collection of individual data points in a three-dimensional plane with each point having a set coordinates on the X, Y, and Z axes.

This notebook uses a pre-trained PointNet model to detect each part of a chair and return its category.

Installation Instructions

This is a self-contained example that relies solely on its own code.
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start. For details, please refer to Installation Guide.