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Source: zinnia
Priority: optional
Maintainer: IME Packaging Team <pkg-ime-devel@lists.alioth.debian.org>
Uploaders: LI Daobing <lidaobing@debian.org>
Build-Depends:
debhelper (>= 7),
autotools-dev,
python-all-dev (>= 2.5.4-1~),
python-support (>= 0.90)
Standards-Version: 3.8.4
Section: libs
Homepage: http://zinnia.sourceforge.net/
Vcs-Browser: https://code.launchpad.net/~pkg-ime/zinnia/debian-zinnia
Vcs-Bzr: lp:~pkg-ime/zinnia/debian-zinnia
Package: zinnia-utils
Section: utils
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}
Description: utils for the zinnia library
Zinnia provides a simple, customizable, and portable dynamic OCR
system for hand-written input, based on Support Vector Machines.
.
Zinnia simply receives user pen strokes as coordinate data and outputs
the best matching characters sorted by SVM confidence. To maintain
portability, it has no rendering functionality. In addition to
recognition, Zinnia provides a training module capable of creating
highly efficient handwriting recognition models.
.
This package provide utils for zinnia library.
Package: libzinnia-dev
Section: libdevel
Architecture: any
Depends: libzinnia0 (= ${binary:Version}), ${misc:Depends}
Description: development files for the zinnia library
Zinnia provides a simple, customizable, and portable dynamic OCR
system for hand-written input, based on Support Vector Machines.
.
Zinnia simply receives user pen strokes as coordinate data and outputs
the best matching characters sorted by SVM confidence. To maintain
portability, it has no rendering functionality. In addition to
recognition, Zinnia provides a training module capable of creating
highly efficient handwriting recognition models.
.
This package is needed to compile programs against libzinnia0,
as only it includes the header files and static libraries (optionally)
needed for compiling.
Package: libzinnia-doc
Section: doc
Architecture: all
Depends: ${misc:Depends}
Description: documention files for the zinnia library
Zinnia provides a simple, customizable, and portable dynamic OCR
system for hand-written input, based on Support Vector Machines.
.
Zinnia simply receives user pen strokes as coordinate data and outputs
the best matching characters sorted by SVM confidence. To maintain
portability, it has no rendering functionality. In addition to
recognition, Zinnia provides a training module capable of creating
highly efficient handwriting recognition models.
.
This package provide the documention files for the zinnia library.
Package: libzinnia0
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}
Description: online handwriting recognition system with machine learning
Zinnia provides a simple, customizable, and portable dynamic OCR
system for hand-written input, based on Support Vector Machines.
.
Zinnia simply receives user pen strokes as coordinate data and outputs
the best matching characters sorted by SVM confidence. To maintain
portability, it has no rendering functionality. In addition to
recognition, Zinnia provides a training module capable of creating
highly efficient handwriting recognition models.
.
This package contains the shared libraries.
Package: libzinnia0-dbg
Priority: extra
Section: debug
Architecture: any
Depends: libzinnia0 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends}
Description: debugging symbols for the zinnia library
Zinnia provides a simple, customizable, and portable dynamic OCR
system for hand-written input, based on Support Vector Machines.
.
Zinnia simply receives user pen strokes as coordinate data and outputs
the best matching characters sorted by SVM confidence. To maintain
portability, it has no rendering functionality. In addition to
recognition, Zinnia provides a training module capable of creating
highly efficient handwriting recognition models.
.
This package contains the detached debugging symbols.
Package: python-zinnia
Section: python
Architecture: any
Provides: ${python:Provides}
Depends: ${python:Depends}, ${shlibs:Depends}, ${misc:Depends}
Description: Python binding for the zinnia library
Zinnia provides a simple, customizable, and portable dynamic OCR
system for hand-written input, based on Support Vector Machines.
.
Zinnia simply receives user pen strokes as coordinate data and outputs
the best matching characters sorted by SVM confidence. To maintain
portability, it has no rendering functionality. In addition to
recognition, Zinnia provides a training module capable of creating
highly efficient handwriting recognition models.
.
This package contains the Python binding.
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