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WIP: Simplify and replace postprocessing #199

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Rewrites the postprocessing step to use a Dask-based algorithm that is a significant departure from the original postprocessing algorithm. This is done for a few reasons. First the old postprocessing algorithm was pretty sensitive and had many failure modes. Second the previous algorithm had a lot of knobs, which slowed down finding a good solution. Third a lot of heuristics were baked into the old postprocessing algorithm, which made it hard to rationalize or understand what it was doing let alone be confident in the result it found. Borrows some pieces from PR ( #110 ) to do this.

@jakirkham jakirkham added this to the v2.11.0 milestone Mar 16, 2018
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Moving off until the next release as we need a rebuild with the Tornado 5 fixes, the Distributed Array Store, and newer dependency versions. Also this code needs some exploration on data to understand what works well, which will be easier to do with a new release. Adding the dask-ndmeasure requirement in this release with PR ( #213 ) to facilitate this exploration.

@jakirkham jakirkham modified the milestones: v2.11.0, v2.12.0 Mar 26, 2018
Make sure to import `dask_ndmeasure` along with the other dask-image org
libraries. Will be needed to construct the label image. IOW will be used
for ROI extraction.
Simply use a threshold with no other constraints.
Also make the chunks concrete (as they are undefined) to allow storage.
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