Announcing an skimage-inspired project

[Adam Hughes]

Hey everyone,

I have been working on a small project over the last month based on an idea
posted to the list last month:

https://groups.google.com/forum/#!topic/scikit-image/6LgfQLO4Jcc

In my research, we do a lot of processing of electron microscope images of
nanoparticles. While image processing is very simple in scikit-image (and
not-so-simple but still manageable when we were writing ImageJ Python
spaghetti code way back when), the post-processing always turned ad-hoc
once we started to quantify, manage and manipulate the segmented particles.
Simple masking worked to an extent, but got hard to juggle for all of the
various things we needed to do.

When I set out to tackle the "pattening/drawing" issue linked above, it
occurred to me that a fairly pythonic API for "managing particles" could be
adapted to particles returned by skimage.draw(), as well as
skimage.morphology.labels()/descriptors(). In other words, "particles" from
labeled images as well as "drawn particles" could be abstracted into a
single API. This was, in a sense, the key insight to motivate the pursuit,
and I think it paid off. The project is only possible because
skimage.draw/labels() are so intelligently built.

Except for maybe the gridding capabilities, all of the core structures are
built primarily to streamline common processing operations and are designed
to work for scikit-image, not in opposition to it. If any of the
descriptions of notebook tutorials suggest otherwise, please let me know so
that I may reword them.

Well, without further ado, here is the project, *pyparty.  *Thanks!

https://github.com/hugadams/pyparty

https://pypi.python.org/pypi
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