Source: zinnia Priority: optional Maintainer: Debian Input Method Team Uploaders: Boyuan Yang , Build-Depends: debhelper (>= 11), Standards-Version: 4.2.1 Section: libs Homepage: https://taku910.github.io/zinnia/ Vcs-Git: https://salsa.debian.org/input-method-team/zinnia.git Vcs-Browser: https://salsa.debian.org/input-method-team/zinnia Package: libzinnia-dev Section: libdevel Architecture: any Depends: libzinnia0 (= ${binary:Version}), ${misc:Depends}, Suggests: libzinnia-doc, 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 Multi-Arch: foreign Depends: ${misc:Depends}, Description: documentation 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 documentation files for the zinnia library. Package: libzinnia0 Architecture: any Depends: ${misc:Depends}, ${shlibs: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: python-zinnia # Section: python # Architecture: any # Provides: # ${python:Provides}, # Depends: # ${misc:Depends}, # ${python:Depends}, # ${shlibs: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. Package: zinnia-utils Section: utils Architecture: any Depends: ${misc:Depends}, ${shlibs: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.