Imagine a vast shopping mall parking lot with thousands of individual parking spots and internal lanes (representing road segments within a cluster). No matter how complex it is inside, there are usually only a few key exits to the main roads. Our goal was to identify these natural "exits" for each map cluster. For instance, the complex road network around Amsterdam Airport Schiphol (see on OpenStreetMap) has many internal roads but limited primary access points.
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Once the image is generated, we can do pretty much whatever we want with it: use it to generate a .qcow2 image for a VM, couple it with anaconda to do a bare-metal installation, store it in an image registry to deploy on cloud servers, etc.