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:
Getting Started
Install on your PC
Install node.js
Install dependencies, as specified in package.json, and create a build in ./build/potree.
npm installRun 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",
}