[Viame] Announcing the early availability of the VIAME toolkit

[Linus Sherrill]

VIAME is a processing framework designed to integrate image and
video processing algorithms in a flexible processing framework. The core
infrastructure connecting different system components is currently
supplied by the KWIVER library by the Vital algorithm framework and the
sprokit pipeline framework.

VIAME is an SDK intended to be an integration platform for assembling
analytical tools
composed of modules from a wide variety of sources. Using the sprokit data
flow
approach, data sources, image processing, detectors, and analyzers can be
easily
integrated from different organizations.

Algorithms and processes can be developed independently as stand-alone
modules
(libraries) that are discovered and loaded at run time. This dynamic
approach
reduces coupling between customer code bases and facilitates easy sharing
of these
modules without requiring each user to rebuild them from the original
source.

*Getting the software*

VIAME itself can be built either as a super-build, which builds all of
its dependencies alongside itself, or standalone. By default it is a
superbuild
so all major dependencies are built into the VIAME project. To build ViAME:

git clone https://github.com/Kitware/VIAME.git

The build instructions can be found in the documentation directory:
VIAME/doc/install_guide.rst

There are currently several cmake options to VIAME, such as
"VIAME_ENABLE_MATLAB", "VIAME_ENABLE_OPENCV", "VIAME_ENABLE_VXL", and
"VIAME_ENABLE_CAFFE" to turn on support for different components. It is
generally a good
idea to enable most all of these options to assure that all KIWVER based
components are available.
If a package based option is not enabled, then the functionality that
depends on that package will
not be available from KWIVER or for your project.

The options can be set on the cmake command line or interactively selected
using the ccmake program.

*Using the VIAME toolkit*

The VIAME toolkit provides an environment to support data processing
algorithms such
as image filters and detectors. There is a introductory tutorial on how to
create
an object detector in the file "VIAME/doc/detector-introduction.rst". This
tutorial
steps through creating a basic detector algorithm and then wraps that
detector in
a sprokit process.

With the VIAME toolkit, you should be able to wrap existing image
processing and
detection algorithms so they can be easily assembled and reconfigured to
solve existing
and new image based problems.

In addition to the tutorial, there is a wrapped SCALLOP-TK detector to
serve as an example
of how an external package are added to VIAME and how they can be wrapped.
This
also serves as an example for how inputs and outputs are converted.

The current VIAME toolkit contains some basic support for running Matlab
code as a detector and
image filter. Matlab support will evolve to meet the needs of the community.

In anticipation of the pre-hackathon teleconference to be held on Wednesday
 at 1PM EDT, we'd like participating organizations to prepare a single
slide outlining their technology, their goals for the hackathon and other
useful information as outlined in the following PowerPoint template:

http://www.viametoolkit.org/wp-content/uploads/2016/08/VIAME
_Hackathon_Quad_Template.pptx

To facilitate the meeting, please provide us your slide by noon on
Wednesday so that we can aggregate them and make them available for the
meeting.

-- 
*Linus Sherrill - *Staff R&D Engineer
Kitware, Inc.
28 Corporate Drive
Clifton Park, NY 12065-8662
E: linus.sherrill at kitware.com
P: 518.881.4400
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