I'm surprised at your colleague's experience. We've run some
polygonize on large images and have never had this problem. The
g2.2xlarge instance is overkill in the sense that the code is not
multi-threaded, so the extra CPUs don't help. Also, as you have
already determine
I have been informed by a colleague attempting to convert a 1.4GB TIF file
using gdal_polygonize.py on a g2.2xlarge Amazon instance (8 vCPU, 15gb RAM)
that the processing took over 2 weeks running constantly. I have also
been told that the same conversion using commercial tooling was completed
in
