Lets say you have a complex industrial plant, or datacenter you want to upgrade.

You scan it with lidar and get a pointcloud and 360 panorama images. This gives you a large dataset, but what you really want is a floorplan, a lite CAD plan showing the racks, cable trays etc.

You take the scan, slice the pointcloud and make an ortho image .. it really looks like an xray of a building from the top down.

Then someone has to manually trace that in CAD to make a useful 3D model they can use for designing the upgrade.

So Im automating the boring manual part - turning the xray plan pixels into vector polylines, using machine learning.

One of our clients scanned their datacenter, and we generated a floorplan that shows all the rack box positions, cable trays, pipes etc.

Other examples : drawing the weld lines of patches in steel storage tanks, drawing in all the steel girder beams in a scan of an old railway bridge, or the windows, doors, ceiling pipes of a commercial realestate refurb.

gord at quato.xyz

As part of this work, were looking at running our custom machine learning kernel on multi-core x86 CPUs.