🚀 Potree Labeling Extension

This project is a fork of Potree that adds powerful labeling capabilities to the point cloud viewer.

The goal is to make large-scale point cloud annotation accessible directly in the browser—without requiring expensive proprietary software or high-end local machines. It enables teams and the machine learning community to efficiently label data, collaborate, and extract insights from point clouds.

This tool serves as a free, web-based alternative to expensive proprietary solutions such as Terrasolid, Terrascan, and Pointly.

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✨ Key Features

🏷️ Annotation Tools

• Segments Tool
  Select a point to automatically segment and label similar points in its vicinity.

• Polygon Lasso Tool
  Draw a polygon from any viewpoint to label all points within the selected area.

• Volume Labeling Tool
  Define 3D volumes and label all points contained within them.

• Subselection Tool
  Isolate a volume and zoom into it to focus on a subset of points for precise labeling.

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⚙️ Additional Capabilities

• Class Locking
  Lock specific classes to prevent accidental labeling—only unlocked classes can be modified.

• QA Visualization Mode
  Convert point clouds into an image-like representation for easier quality control.

• Hillshade Mode
  Generate hillshade visualizations to assist in ground classification and QC.

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🤝 Collaboration

Built for teams, this tool supports collaborative workflows:

• Labelers and QA teams can work together seamlessly
• Enables efficient review and validation processes

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⚡ Performance

Powered by WebGPU, the labeling engine delivers high-performance rendering and interaction—making it fast and responsive even for large point clouds.

About

• Potree is a free open-source WebGL based point cloud renderer for large point clouds. It is based on the TU Wien Scanopy project and research projects Harvest4D, GCD Doctoral College and Superhumans.
• Newest information and work in progress is usually available on twitter
• Contact: Markus Schütz (mschuetz@potree.org)
• References:
  • Potree: Rendering Large Point Clouds in Web Browsers (2016)
  • Fast Out-of-Core Octree Generation for Massive Point Clouds (2020)

Getting Started

Install on your PC

Install node.js

Install dependencies, as specified in package.json, and create a build in ./build/potree.

npm install

Run on your PC

Use the npm start command to

• create ./build/potree
• watch for changes to the source code and automatically create a new build on change
• start a web server at localhost:1234.

Go to http://localhost:1234/examples/ to test the examples.

Deploy to a server

• Simply upload the Potree folderm with all your point clouds, the build directory, and your html files to a web server.
• It is not required to install node.js on your webserver. All you need is to host your files online.

Convert Point Clouds to Potree Format

Download PotreeConverter and run it like this:

./PotreeConverter.exe C:/pointclouds/data.las -o C:/pointclouds/data_converted

Copy the converted directory into <potreeDirectory>/pointclouds/data_converted. Then, duplicate and rename one of the examples and modify the path in the html file to your own point cloud.

Downloads

• Potree
• PotreeConverter - Convert your point cloud to the Potree format.
• PotreeDesktop - Desktop version of Potree. Allows drag&drop of point clouds into the viewer.

Examples

Basic Viewer	CA13 (18 billion Points)	Retz (Potree + Cesium)	Classifications	Various Features	Toolbar

More Examples

Load Project	Matcap	Virtual Reality	Heidentor	Lion	Lion LAS
Lion LAZ	EPT	EPT Binary	EPT zstandard	Clipping Volume	Oriented Images
Elevation Profile	Measurements	Meshes	Multiple Point Clouds	Camera Animation	Features (CA13)
Annotations	Hierarchical Annotations	Animation Path	Shapefiles	Cesium CA13	Geopackage
Cesium Sorvilier	Custom Sidebar Section	Embedded Iframe	Gradient Colors

VR

Heidentor	Eclepens	Morro Bay	Lion	Dechen Cave

Showcase

Matterhorn	Retz	Lake Tahoe	Sorvilier	Grave	Chowilla

More

Chiller	Cooler	Dechen Cave	Ruins	Eclepens	Heidentor
Building	LDHI	Lion Head	Overpass	Pielach	pompei
Santorini	Skatepark	Subsea Eq.	Subsea Man.	Westend Palais	Whitby

Funding

Potree is funded by a combination of research projects, companies and institutions.

Research projects who's funding contributes to Potree:

Project Name	Funding Agency
LargeClouds2BIM	FFG
Harvest4D	EU 7th Framework Program 323567
GCD Doctoral College	TU Wien
Superhumans	FWF

We would like to thank our sponsors for their financial contributions that keep this project up and running!

Diamond € 15,000+
Gold € 10,000+
Silver € 5,000+
Bronze € 1,000+	Data-viewer

Credits

• The multi-res-octree algorithms used by this viewer were developed at the Vienna University of Technology by Michael Wimmer and Claus Scheiblauer as part of the Scanopy Project.
• Three.js, the WebGL 3D rendering library on which potree is built.
• plas.io point cloud viewer. LAS and LAZ support have been taken from the laslaz.js implementation of plas.io. Thanks to Uday Verma and Howard Butler for this!
• Harvest4D Potree currently runs as Master Thesis under the Harvest4D Project
• Christian Boucheny (EDL developer) and Daniel Girardeau-Montaut (CloudCompare). The EDL shader was adapted from the CloudCompare source code!
• Martin Isenburg, Georepublic, Veesus, Sigeom Sa, SITN, LBI ArchPro, Pix4D as well as all the contributers to potree and PotreeConverter and many more for their support.

Bibtex

@article{SCHUETZ-2020-MPC,
	title =      "Fast Out-of-Core Octree Generation for Massive Point Clouds",
	author =     "Markus Schütz and Stefan Ohrhallinger and Michael Wimmer",
	year =       "2020",
	month =      nov,
	journal =    "Computer Graphics Forum",
	volume =     "39",
	number =     "7",
	doi =        "10.1111/cgf.14134",
	pages =      "13",
	publisher =  "John Wiley & Sons, Inc.",
	pages =      "1--13",
	keywords =   "point clouds, point-based rendering, level of detail",
}