# higher levels get smaller images from the pyramid -- this one is 
# 2875x2057, 16x smaller, so we can search quickly
image = pyvips.Image.new_from_file("CMU-1.svs", level=2)

# make a one-band mask image, with TRUE for pixels over 240
# this should detect a white background
# blur first, so we only detect large areas above 240
mask = image.gaussblur(20) > 240

# label connected regions in the mask image
# each connected block will be given a unique index
# the background will be label 1, each black blob will 
# be 2, 3, .. etc.
index = mask.labelregions()

# make an xy image, so each pixel contains its own coordinate
xy = pyvips.Image.xyz(width=mask.width, height=mask.height)

# now histogram the xy image, but use the index image to pick the 
# histogram bins
# don't sum the xy, instead find the min of each bin
lefttop = xy.hist_find_indexed(index, combine="min")

# now lefttop is an array where pixel (1, 0) is two ints for left/top of blob 1, 
# pixel (2, 0) is the position of blob 1, etc.
# scale up by x16 to get coordinates in the WSI image