C++ and the ROS have been the traditional tools for interacting with lidar data, but they can be cumbersome for quick prototyping and testing. We have recently launched an Ouster SDK for Python to allow Ouster lidar users the ease of quick development Python is known for, while maintaining the processing speed of C++ which underpins the SDK.
In this webinar, we are going to go into the code and walk through how to install the SDK, how to write some quick statistical analysis scripts, and even how to do some more complicated analysis that leverage Python open source libraries.
What you’ll learn:
How to install the Ouster SDK
How to set up a virtual environment for development
How to run basic statistical analysis on a set of Ouster lidar data
How open source libraries Python libraries designed for 2D data can supercharge your Ouster lidar development
Ouster builds high-resolution 3D lidar sensors that are powering autonomy in the industrial, smart infrastructure, robotics, and automotive industries. We are a team with deep knowledge of semiconductors, optics, signal processing, computer vision, and high-volume manufacturing. Our breakthrough digital lidar technology produces sensors that are high-resolution, reliable, and affordable. We are working to make 3D sensing lidar technology ubiquitous throughout our everyday lives.
3:40 Intro to the SDK
7:07 Create Virtual Environment
9:45 Install Ouster Python SDK with pip
10:48 Live Stream Ouster Data Example
13:08 Live Stream Code Walkthrough
17:39 Live Statistics Example
18:08 Live Statistics Code Walkthrough
24:20 Run Live Statistics Code
26:42 Machine Learning Example with Votenet
28:20 Votenet Code Modifications for Ouster
32:25 Run Votenet on Live Ouster Sensor
38:28 Why we built the Ouster Python SDK