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WebGL point cloud viewer for large datasets

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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

Examples

Basic ViewerCA13 (18 billion Points)Retz (Potree + Cesium)ClassificationsVarious FeaturesToolbar
More Examples
Load ProjectMatcapVirtual RealityHeidentorLionLion LAS
Lion LAZEPTEPT BinaryEPT zstandardClipping VolumeOriented Images
Elevation ProfileMeasurementsMeshesMultiple Point CloudsCamera AnimationFeatures (CA13)
AnnotationsHierarchical AnnotationsAnimation PathShapefilesCesium CA13Geopackage
Cesium SorvilierCustom Sidebar SectionEmbedded IframeGradient Colors

VR

HeidentorEclepensMorro BayLionDechen Cave

Showcase

MatterhornRetzLake TahoeSorvilierGraveChowilla
More
ChillerCoolerDechen CaveRuinsEclepensHeidentor
BuildingLDHILion HeadOverpassPielachpompei
SantoriniSkateparkSubsea Eq.Subsea Man.Westend PalaisWhitby

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",
}

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WebGL point cloud viewer for large datasets

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