Does anyone know how to do a chessboard segmentation (in the same way that
ecognition does) that will select all the edges of a Landsat pixel in python/a Jupyter notebook? Given that I can use the notebook to retrieve the imagery as a multi-band
xarray, does anyone have a good recipe using
scikit-image or similar to take the imagery array and run a chessboard segmentation on it, outputting the pixel edges as a shapefile? I want every pixel edge as opposed to areas of similarity.
I can do this in
ecognition, and create a workflow. I'm looking for a python equivalent to the chessboard segmentation workflow in
ecognition that I can apply on a large scale for multiple times. I'm not doing it in
ecognition because I need to do large amounts of timesteps and large amounts of spatial area, and it's impractical in human-time-cost to do so for thousands of images.