./inputmethod/zinnia, Online hand writing recognition system with machine learning

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Branch: CURRENT, Version: 0.06, Package name: zinnia-0.06, Maintainer: pkgsrc-users

Zinnia is a simple, customizable and portable online hand recognition system
based on Support Vector Machines. Zinnia simply receives user pen strokes as a
sequence of coordinate data and outputs n-best characters sorted by SVM
confidence. To keep portability, Zinnia doesn't have any rendering
functionality. In addition to recognition, Zinnia provides training module that
allows us to create any hand-written recognition systems with low-cost.


Master sites:

SHA1: bc67d65857186bb49710a712a2fc8f8cb81211c0
RMD160: 7ade98fa37144f2750b027278c1b55d810612974
Filesize: 446.694 KB

Version history: (Expand)


CVS history: (Expand)


   2015-11-03 23:13:42 by Alistair G. Crooks | Files touched by this commit (111)
Log message:
Add SHA512 digests for distfiles for inputmethod category

Problems found locating distfiles:
	Package anthy: missing distfile 2ch.t
	Package anthy: missing distfile okinawa-20090801.t

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.
   2015-03-15 18:15:02 by Hiramatsu Yoshifumi | Files touched by this commit (7)
Log message:
Set MAINTAINER to pkgsrc-users.
   2012-10-06 16:25:22 by Aleksej Saushev | Files touched by this commit (114)
Log message:
Drop superfluous PKG_DESTDIR_SUPPORT, "user-destdir" is default these days.
   2011-09-14 18:58:42 by Hans Rosenfeld | Files touched by this commit (2)
Log message:
Remove stupid make check from configure to fix build on SunOS.
   2010-08-14 16:30:40 by OBATA Akio | Files touched by this commit (4) | Package updated
Log message:
Update zinia to 0.06.

no changes information, seems some fixes.
   2010-05-20 11:05:30 by OBATA Akio | Files touched by this commit (6) | Imported package
Log message:
Import zinnia-0.05 as inputmethod/zinnia.

Zinnia is a simple, customizable and portable online hand recognition system
based on Support Vector Machines.  Zinnia simply receives user pen strokes as a
sequence of coordinate data and outputs n-best characters sorted by SVM
confidence.  To keep portability, Zinnia doesn't have any rendering
functionality.  In addition to recognition, Zinnia provides training module that
allows us to create any hand-written recognition systems with low-cost.