Real-Time Visualization and Interactive Segmentation: 3D Python Tutorial

This tutorial dives into interactive visualization and segmentation using 3D Python libraries! I show you how to:
Load and prepare your 3D data
Build a responsive 3D visualization with user interaction
Gain deeper insights by manipulating your data in real-time

By the end of this video, you'll be able to create stunning and informative interactive 3D segmentations using Python.

I go through several linear phases that follow the different chapters.

🍇 RESOURCES
Code and Dataset Access (License MIT): https://drive.google.com/drive/folder... (Google Drive)

🍿 NEXT STEPS:
Code a 3D Point Cloud Segmentation Solution with Python:    • 3D Point Cloud Segmentation and Shape Reco...  
Finish the 3D Tutorial Series: https://learngeodata.eu/3d-tutorials/
Dive in Expert articles:   / florentpoux  
Become a 3D Data Science Expert: https://learngeodata.eu

🙋 FOLLOW ME
Linkedin:   / florent-poux-point-cloud  
Github: https://github.com/florentPoux
Research: https://scholar.google.com/citations?...

WHO AM I?
If we haven’t yet before - Hey 👋 I’m Florent, a professor-turned-entrepreneur, and I’ve somehow become one of the most-followed 3D expert. Through my videos here on this channel and my writing, I share evidence-based strategies and tools to help you be better coders and 3D innovators.

📄 CHAPTERS
[00:00:00]: 3D Tutorial Introduction
[00:00:33]: Overview of the 3D Workflow
[00:00:50]: Step 1: Environment
[00:02:20]: Step 2: Installing 3D Python
[00:03:10]: Step 3: IDE Setup
[00:03:48]: Step 4: Point Cloud Dataset
[00:05:05]: Step 5: Point Cloud I/O
[00:06:39]: Step 6: Point Cloud Pre-Processing
[00:07:47]: Step 7: 3D Visualization Strategy
[00:10:36]: Step 8: Point Cloud Interaction
[00:12:30]: Step 9: 3D Segmentation
[00:13:13]: Conclusion and Perspectives