Entwine is a data organization library for massive point clouds, designed to conquer datasets of hundreds of billions of points as well as desktop-scale point clouds. Entwine can index anything that is PDAL-readable, and can read/write to a variety of sources like S3 or Dropbox. Builds are completely lossless, so no points will be discarded even for terabyte-scale datasets.

Check out the client demos, showcasing Entwine output with Plas.io, Potree, and Cesium clients.

Usage

Getting started with Entwine is easy with Docker. Pull the most recent image with docker pull connormanning/entwine. Let's build an Entwine index of some publicly hosted data:

docker run -it -v $HOME:$HOME connormanning/entwine build \
    -i https://entwine.io/sample-data/red-rocks.laz \
    -o ~/entwine/red-rocks

Now we have our output at ~/entwine/red-rocks. We could have also passed a directory like -i ~/county-data/ to index multiple files. Now we can view this data with Greyhound - we'll map our top-level Entwine output directory into one of the default search paths for the Greyhound container.

docker run -it -v ~/entwine:/entwine -p 8080:8080 connormanning/greyhound

Now that we have Greyhound running locally and ready to serve our data, we can view it with these Plasio or Potree links which point at our local resource.

Going further

For detailed information about how to configure your builds, check out the configuration documentation. Here, you can find information about reprojecting your data, using configuration files and templates, enabling S3 capabilities, producing Cesium 3D Tiles output, and all sorts of other settings.