How to Build a 3D Interactive App in Python: Point Cloud Feature Extraction Tutorial (Part 2)

Veröffentlicht am: 21 März 2024
auf dem Kanal: Florent Poux

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This tutorial is for Python enthusiasts and 3D Innovators! We dive into the exciting 3D LiDAR point cloud feature extraction world using Python. If you want to create interactive Python Apps to handle 3D LiDAR data, this video is for you! We'll cover everything you need to automate the process of feature selection and thresholding for segmentation purposes.

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

🍇 RESOURCES:
Download the LiDAR dataset used: https://drive.google.com/drive/folder...
The Part 1 of the Tutorial:    • 3D Point Cloud Feature Extraction Tut...

🍿 NEXT STEPS:
Code a 3D Point Cloud Segmentation Solution with Python:    • 3D Point Cloud Segmentation and Shape...
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]: Introduction to feature extraction tutorial
[00:01:23]: Automating feature extraction on full point cloud
[00:05:32]: Visualization of computed features using PyVista
[00:08:07]: Thresholding features for segmentation
[00:10:51]: Interactive selection and remanence technique
[00:13:33]: Merging features with coordinates
[00:14:57]: Saving results in a file
[00:16:11]: Exploring the classified results
[00:17:26]: Creating a labeled dataset using thresholding techniques
[00:18:40]: Conclusion and future 3D Coding Tutorial

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