FLANN is Fast Library for Approximate Nearest Neighbors, which is a purportedly wicked fast nearest neighbor library for comparing multi-dimensional points. I only say purportedly, as I haven’t verified, but I assume this to be quite true. I’d like to move some (all) of my KNN calculations outside the database. I’d like to do the following with FLANN– take a LiDAR point cloud and change … Continue reading KNN with FLANN and laspy, a starting place
There’s all sorts of reasons why what I’ve been doing so far is wrong (see the previous 5 posts). More on that later. But in case you needed 3D visualization of the chipping I’ve been working through, look no further: Continue reading LiDAR and pointcloud extension pt 6
Now for the crazy stuff: The objective is to allow us to do vertical and horizontal summaries of our data. To do this, we’ll take chipped LiDAR input and further chip it vertically by classifying it. First a classifier for height that we’ll use to do vertical splits on our point cloud chips: And now, let’s pull apart our point cloud, calculate heights from approximate … Continue reading LiDAR and pointcloud extension pt 5
Now, we navigate into unknown (and perhaps silly) territory. Now we do point level calculations of heights, and drop the new calculated points back into the point cloud as though it were a Z value. I don’t recommend this code as a practice– this is as much as me thinking aloud as anything Caveat emptor: Continue reading LiDAR and pointcloud extension pt 4
Digging a little deeper. Ran the chipper on a smaller number of points and then am doing a little hacking to get height per chip (if you start to get lost, go to Paul Ramsey’s tutorial). Here’s my pipeline file. Note the small chipper size– 20 points per chip. Easy enough to load (though slow for the sake of the chip size): Now we can … Continue reading LiDAR and pointcloud extension pt 3
As much for my edification as anyones: Want to get at just a few points within the pointcloud extension? A with query will get you there: Continue reading LiDAR and pointcloud extension pt 2
Paul Ramsey has a great tutorial on using the pointcloud extension with PostgreSQL / PostGIS: http://workshops.boundlessgeo.com/tutorial-lidar/ You can get point cloud and all that goodness running a variety of ways. Probably the easiest is to download OpenGeo Suite from Boundless: http://boundlessgeo.com/solutions/opengeo-suite/download/ If you are an Ubuntu user, try a docker instance to run PostGIS with PDAL, pointcloud, etc in a container: https://github.com/vpicavet/docker-pggis Also, I’m working … Continue reading LiDAR and pointcloud extension
Docker. See: https://github.com/vpicavet/docker-pggis for a quick and easy Docker running PostGIS. Understand, this isn’t production ready (the connection permissions make my teeth hurt a little) but, so nice to have a one stop shop for postgis, pgrouting, and pointcloud. Now I may have to write blog posts on pointcloud. Point cloud didn’t get in the PostGIS Cookbook because it was too hard to build. I … Continue reading The easiest way to get PostGIS and friends running:
In my previous post on Getting Bundler and friends running, I suggested how to modify an existing script to get Bundler and other structure from motion parts/pieces up and running. Here’s my follow up. Install Vagrant and VirtualBox. Download (or clone) this repo: https://github.com/OpenDroneMap/odm-vagrant Navigate into the cloned or unzipped directory (on the command line), run vagrant up Go have a cup of coffee. Come … Continue reading Getting Bundler and friends running — part deux
Anyone who has jumped down the rabbit hole of computer vision has run into dependency h*ll getting software to run. I jumped down that hole again today with great success that I don’t want to forget (these directions are for Ubuntu, fyi). First, clone BundlerTools: https://github.com/qwesda/BundlerTools This will download and compile (almost) everything for you, which is a wonderful thing. The one exception is graclus. … Continue reading Getting Bundler and friends running
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