greekocr-1.0.1/ 0000755 0001750 0001750 00000000000 11635564234 012663 5 ustar dalitz dalitz greekocr-1.0.1/TODO 0000644 0001750 0001750 00000001116 11536114132 013336 0 ustar dalitz dalitz Tasks for future versions of the GreekOCR toolkit
-------------------------------------------------
- optionally enable grouping for the separatistic approach
- add new wholistic recognition which attaches accents to
characters with Gamera's grouping algorithm
- do thorough tests for the different approaches and
measure the performances on various documents
- Why does the recognition result contain spurious additional lines?
- integrate the improved attachment of diacritical signs to
characters into the basic OCR toolkit
- disambiguate between quotes and accents
greekocr-1.0.1/MANIFEST.in 0000644 0001750 0001750 00000000717 11530742470 014420 0 ustar dalitz dalitz recursive-include src *.cpp *.c *.h makefile.* *.hpp *.hxx *.cxx *.txt ANNOUNCE CHANGES INSTALL KNOWNBUG LICENSE README TODO
recursive-include include *.cpp *.c *.h makefile.* *.hpp *.hxx *.cxx *.txt ANNOUNCE CHANGES INSTALL KNOWNBUG LICENSE README TODO
recursive-include scripts greekocr
include ACKNOWLEDGEMENTS CHANGES TODO INSTALL LICENSE README KNOWN_BUGS MANIFEST.in version
recursive-include doc *.txt *.html *.css *.py *.jpg *.jpeg *.png *.gif *.fig
greekocr-1.0.1/LICENSE 0000644 0001750 0001750 00000035423 11635556523 013701 0 ustar dalitz dalitz GNU GENERAL PUBLIC LICENSE
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greekocr-1.0.1/setup.py 0000755 0001750 0001750 00000003041 11530744025 014366 0 ustar dalitz dalitz #!/usr/bin/env python
from distutils.core import setup, Extension
from gamera import gamera_setup
# This constant should be the name of the toolkit
TOOLKIT_NAME = "greekocr"
VERSION = open("version", 'r').readlines()[0].strip()
AUTHOR = "Christian Brandt and Christoph Dalitz"
HOMEPAGE = "http://gamera.sourceforge.net/"
DESCRIPTION = "An addon Greek OCR toolkit for the Gamera framework for document analysis and recognition."
LICENSE = "GNU GPL version 2"
# ----------------------------------------------------------------------------
# You should not usually have to edit anything below, but it is
# implemented here and not in the Gamera core so that you can edit it
# if you need to do something more complicated (for example, building
# and linking to a third- party library).
# ----------------------------------------------------------------------------
PLUGIN_PATH = 'gamera/toolkits/%s/plugins/' % TOOLKIT_NAME
PACKAGE = 'gamera.toolkits.%s' % TOOLKIT_NAME
PLUGIN_PACKAGE = PACKAGE + ".plugins"
plugins = gamera_setup.get_plugin_filenames(PLUGIN_PATH)
plugin_extensions = gamera_setup.generate_plugins(plugins, PLUGIN_PACKAGE)
# This is a standard distutils setup initializer. If you need to do
# anything more complex here, refer to the Python distutils documentation.
setup(name=TOOLKIT_NAME, version=VERSION, license=LICENSE, url=HOMEPAGE,
author=AUTHOR, description=DESCRIPTION,
ext_modules = plugin_extensions,
packages = [PACKAGE, PLUGIN_PACKAGE],
scripts = ['scripts/greekocr4gamera.py'])
greekocr-1.0.1/gamera/ 0000755 0001750 0001750 00000000000 11635564234 014117 5 ustar dalitz dalitz greekocr-1.0.1/gamera/toolkits/ 0000755 0001750 0001750 00000000000 11635564234 015767 5 ustar dalitz dalitz greekocr-1.0.1/gamera/toolkits/greekocr/ 0000755 0001750 0001750 00000000000 11635564234 017570 5 ustar dalitz dalitz greekocr-1.0.1/gamera/toolkits/greekocr/singlediacritics.py 0000644 0001750 0001750 00000013744 11635564123 023470 0 ustar dalitz dalitz # -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
# Copyright (C) 2010-2011 Christian Brandt
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
from gamera.core import *
from gamera.plugins.pagesegmentation import textline_reading_order
from gamera.toolkits.ocr.ocr_toolkit import *
from gamera.toolkits.ocr.classes import Textline,Page,ClassifyCCs
import gamera.kdtree as kdtree
import unicodedata
import sys
class SinglePage(Page):
def lines_to_chars(self):
subccs = self.img.sub_cc_analysis(self.ccs_lines)
for i,segment in enumerate(self.ccs_lines):
self.textlines.append(SingleTextline(segment, subccs[1][i]))
class Character(object):
def __init__(self, glyph):
self.maincharacter = glyph
self.unicodename = glyph.get_main_id()
self.unicodename = self.unicodename.replace(".", " ").upper()
#print self.unicodename
#self.unicodename =
self.combinedwith = []
#print self.maincharacter
def addCombiningDiacritics(self, diacrit):
self.combinedwith.append(diacrit)
pass
def toUnicodeString(self):
try:
str = u""
mainids = self.maincharacter.get_main_id().split(".and.")
for char in mainids:
if char == "skip" or char == "unclassified":
continue
str = str + u"%c" % return_char(char)
#str = u"" + return_char(self.unicodename)
for char in self.combinedwith:
#char = char.get_main_id().replace(".", " ").upper()
mainids = char.get_main_id().split(".and.")
#print mainids
for char in mainids:
if char == "skip":
continue
#print "added %s to output" % char
str = str + u"%c" % return_char(char)
return unicodedata.normalize('NFD', str)
except:
#print self.unicodename
return u"E"
class SingleTextline(Textline):
def sort_glyphs(self):
self.glyphs.sort(lambda x,y: cmp(x.ul_x, y.ul_x))
#begin calculating threshold for word-spacing
glyphs = []
for g in self.glyphs:
if self.is_combining_glyph(g):
continue
glyphs.append(g)
spacelist = []
total_space = 0
for i in range(len(glyphs) - 1):
spacelist.append(glyphs[i + 1].ul_x - glyphs[i].lr_x)
if(len(spacelist) > 0):
threshold = median(spacelist)
threshold = threshold * 2.0
else:
threshold = 0
#end calculatin threshold for word-spacing
self.words = chars_make_words(self.glyphs, threshold)
def is_combining_glyph(self, glyph):
ret = glyph.get_main_id().find("combining") != -1
return ret
def to_string(self):
k = 3
max_k = 10
output = ""
for word in self.words:
med_center = median([g.center.y for g in word])
glyphs_combining = []
characters = []
nodes_normal = []
skipids = ["manual.xi.upper", "manual.xi.lower", "manual.theta.outer", "_split.splitx", "skip"]
for glyph in word:
mainid = glyph.get_main_id()
if skipids.count(mainid) > 0:
continue
elif mainid == "manual.xi.middle":
glyph.classify_automatic("greek.capital.letter.xi")
elif mainid == "manual.theta.inner":
glyph.classify_automatic("greek.capital.letter.theta")
elif mainid == "comma" or mainid == "combining.comma.above":
#print "%s - center_y: %d - med_center: %d" % (mainid, glyph.center.y, med_center)
if glyph.center.y > self.bbox.center.y:
glyph.classify_automatic("comma")
else:
glyph.classify_automatic("combining.comma.above")
elif mainid.find("manual") != -1 or mainid.find("split") != -1:
continue
if self.is_combining_glyph(glyph):
glyphs_combining.append(glyph)
else:
c = Character(glyph)
characters.append(c)
#print c
nodes_normal.append(kdtree.KdNode((glyph.center.x, glyph.center.y), c))
if (nodes_normal == None or len(nodes_normal) == 0):
continue
tree = kdtree.KdTree(nodes_normal)
for g in glyphs_combining:
fast = True
if fast:
knn = tree.k_nearest_neighbors((g.center.x, g.center.y), k)
knn[0].data.addCombiningDiacritics(g)
else:
found = False
while (not found) and k < max_k:
knn = tree.k_nearest_neighbors((g.center.x, g.center.y), k)
for nn in knn:
if (nn.data.maincharacter.get_main_id().split(".").count("greek") > 0) and not found:
nn.data.addCombiningDiacritics(g)
found = True
break
k = k + 2
for c in characters:
output = output + c.toUnicodeString()
output = output + " "
return output
greekocr-1.0.1/gamera/toolkits/greekocr/compare.py 0000644 0001750 0001750 00000006017 11635564123 021571 0 ustar dalitz dalitz # -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
# Copyright (C) 2010-2011 Christian Brandt
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
import unicodedata
import codecs
def levenshtein(s1, s2):
"""Computes the Levenshtein distance (aka edit distance) between
the two Unicode strings *s1* and *s2*. Signature:
``levenshtein(s1, s2)``
This implementation differs from the plugin *edit_distance* in the Gamera
core in two points:
- the Gamera core function is implemented in C++ and currently only
works with ASCII strings
- this implementation is written in pure Python and therefore somewhat
slower, but it works with Unicode strings.
For details about the algorithm see
http://en.wikibooks.org/wiki/Algorithm_implementation/Strings/Levenshtein_distance
"""
if len(s1) < len(s2):
return levenshtein(s2, s1)
if not s1:
return len(s2)
previous_row = xrange(len(s2) + 1)
for i, c1 in enumerate(s1):
current_row = [i + 1]
for j, c2 in enumerate(s2):
insertions = previous_row[j + 1] + 1 # j+1 instead of j since previous_row and current_row are one character longer
deletions = current_row[j] + 1 # than s2
substitutions = previous_row[j] + (c1 != c2)
current_row.append(min(insertions, deletions, substitutions))
previous_row = current_row
return previous_row[-1]
def levenshtein_multi_unicode(str1, str2):
#remove linebreaks
str1 = str1.replace("\n", "")
str2 = str2.replace("\n", "")
#remove spaces
str1 = str1.replace(" ", "")
str2 = str2.replace(" ", "")
str1_n = unicodedata.normalize("NFD", str1)
str2_n = unicodedata.normalize("NFD", str2)
return levenshtein(str1_n, str2_n), len(str1_n), len(str2_n)
def errorrate(groundtruth, ocr):
"""For the two given Unicode strings, the edit distance divided by the
length of the first string is returned.
Signature:
``errorrate(groundtruth, ocr)``
"""
errorcount, gtlength, ocrlength = levenshtein_multi_unicode(groundtruth, ocr)
rate = float(errorcount) / gtlength
print "Errorcount: %d" % errorcount
print "Characters in GT: %d" % gtlength
print "Characters in OCR: %d" % ocrlength
print "Error Rate: %.2f %%" % (rate * 100)
#print "=%5d %5d %5d %3.2f" % (errorcount, gtlength, ocrlength, rate*100)
return rate
greekocr-1.0.1/gamera/toolkits/greekocr/unicode_teubner.py 0000644 0001750 0001750 00000017420 11635564123 023315 0 ustar dalitz dalitz #encoding: utf-8
# -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
# Copyright (C) 2010-2011 Christian Brandt
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
import sys
charactermap = {
"GREEK CAPITAL LETTER ALPHA": "A","GREEK CAPITAL LETTER BETA": "B",
"GREEK CAPITAL LETTER GAMMA": "G","GREEK CAPITAL LETTER DELTA": "D",
"GREEK CAPITAL LETTER EPSILON": "E","GREEK CAPITAL LETTER ZETA": "Z",
"GREEK CAPITAL LETTER ETA": "H","GREEK CAPITAL LETTER THETA": "J",
"GREEK CAPITAL LETTER IOTA": "I","GREEK CAPITAL LETTER KAPPA": "K",
"GREEK CAPITAL LETTER LAMDA": "L","GREEK CAPITAL LETTER MU": "M",
"GREEK CAPITAL LETTER NU": "N","GREEK CAPITAL LETTER XI": "X",
"GREEK CAPITAL LETTER OMICRON": "O","GREEK CAPITAL LETTER PI": "P",
"GREEK CAPITAL LETTER RHO": "R","GREEK CAPITAL LETTER SIGMA": "C",
"GREEK CAPITAL LETTER TAU": "T","GREEK CAPITAL LETTER UPSILON": "U",
"GREEK CAPITAL LETTER PHI": "F","GREEK CAPITAL LETTER CHI": "Q",
"GREEK CAPITAL LETTER PSI": "Y","GREEK CAPITAL LETTER OMEGA": "W",
"GREEK SMALL LETTER ALPHA": "a","GREEK SMALL LETTER BETA": "b",
"GREEK SMALL LETTER GAMMA": "g","GREEK SMALL LETTER DELTA": "d",
"GREEK SMALL LETTER EPSILON": "e","GREEK SMALL LETTER ZETA": "z",
"GREEK SMALL LETTER ETA": "h","GREEK SMALL LETTER THETA": "j","GREEK THETA SYMBOL": "j",
"GREEK SMALL LETTER IOTA": "i","GREEK SMALL LETTER KAPPA": "k",
"GREEK SMALL LETTER LAMDA": "l","GREEK SMALL LETTER MU": "m",
"GREEK SMALL LETTER NU": "n","GREEK SMALL LETTER XI": "x",
"GREEK SMALL LETTER OMICRON": "o","GREEK SMALL LETTER PI": "p",
"GREEK SMALL LETTER RHO": "r","GREEK SMALL LETTER FINAL SIGMA": "c",
"GREEK SMALL LETTER SIGMA": "s","GREEK SMALL LETTER TAU": "t",
"GREEK SMALL LETTER UPSILON": "u","GREEK SMALL LETTER PHI": "f",
"GREEK SMALL LETTER CHI": "q","GREEK SMALL LETTER PSI": "y",
"GREEK SMALL LETTER OMEGA": "w", "SPACE": " ",
"FULL STOP": ".", "COMMA": ",", "HYPHEN-MINUS": "-"
}
accentmap = [
['\\`%c', ['combining.grave.accent']],
['\\\'%c', ['combining.acute.accent']],
['\\~%c', ['combining.greek.perispomeni']],
['\\"%c', ['combining.diaresis']],
['\\u{%c}', ['combining.breve']],
['\\U{%c%c}', ['combining.double.breve']],
['\\=%c', ['combining.overline']],
['\\r{%c}', ['combining.comma.above']],
['\\s{%c}', ['combining.reversed.comma.above']],
['\\Ad{%c}', ['combining.acute.accent', 'combining.diaresis']],
['\\Gd{%c}', ['combining.diaresis', 'combining.grave.accent']],
['\\Cd{%c}', ['combining.diaresis', 'combining.greek.perispomeni']],
['\\Ar{%c}', ['combining.acute.accent', 'combining.reversed.comma.above']],
['\\Gr{%c}', ['combining.grave.accent', 'combining.reversed.comma.above']],
['\\Cr{%c}', ['combining.greek.perispomeni', 'combining.reversed.comma.above']],
['\\As{%c}', ['combining.acute.accent', 'combining.comma.above']],
['\\Gs{%c}', ['combining.comma.above', 'combining.grave.accent']],
['\\Cs{%c}', ['combining.comma.above', 'combining.greek.perispomeni']],
['\\c{%c}', ['combining.inverted.breve.below']],
['\\ut{%cw}', ['combining.double.breve.below']],
['\\Ab{%c}', ['combining.acute.accent', 'combining.breve']],
['\\Gb{%c}', ['combining.breve', 'combining.grave.accent']],
['\\Arb{%c}', ['combining.acute.accent', 'combining.breve', 'combining.reversed.comma.above']],
['\\Grb{%c}', ['combining.breve', 'combining.grave.accent', 'combining.reversed.comma.above']],
['\\Asb{%c}', ['combining.acute.accent', 'combining.breve', 'combining.comma.above']],
['\\Gsb{%c}', ['combining.breve', 'combining.comma.above', 'combining.grave.accent']],
['\\Am{%c}', ['combining.acute.accent', 'combining.overline']],
['\\Gm{%c}', ['combining.grave.accent', 'combining.overline']],
['\\Cm{%c}', ['combining.greek.perispomeni', 'combining.overline']],
['\\Arm{%c}', ['combining.acute.accent', 'combining.overline', 'combining.reversed.comma.above']],
['\\Grm{%c}', ['combining.grave.accent', 'combining.overline', 'combining.reversed.comma.above']],
['\\Crm{%c}', ['combining.greek.perispomeni', 'combining.overline', 'combining.reversed.comma.above']],
['\\Asm{%c}', ['combining.acute.accent', 'combining.comma.above', 'combining.overline']],
['\\Gsm{%c}', ['combining.comma.above', 'combining.grave.accent', 'combining.overline']],
['\\Csm{%c}', ['combining.comma.above', 'combining.greek.perispomeni', 'combining.overline']],
['\\Sm{%c}', ['combining.comma.above', 'combining.overline']],
['\\Rm{%c}', ['combining.overline', 'combining.reversed.comma.above']],
['\\iS{%c}', ['combining.greek.ypogegrammeni']],
['\\d{%c}', ['combining.dot.below']],
['\\bd{%c}', ['combining.breve', 'combining.diaresis']],
['\\ring{%c}', ['combining.ring.below']]
]
accentmap.sort(key=lambda s: s[1])
def unicode_to_teubner(unicode_text):
"""Returns the given unicode string to a LaTeX document body using
the Teubner style for representing Greek characters and accents. Signature:
``unicode_to_teubner (unicode_text)``
The returned LaTeX code does not contain the LaTeX header. To create
a complete LaTeX document, you can use the following code:
.. code:: Python
# LaTeX header
print "\documentclass[10pt]{article}"
print "\usepackage[polutonikogreek]{babel}"
print "\usepackage[or]{teubner}"
print "\\\\begin{document}"
print "\selectlanguage{greek}"
# document body
print unicode_to_teubner(unicode_string)
# LaTex footer
print "\end{document}"
"""
import unicodedata
output = u""
combinewith = []
maincharacter = None
i = 0
while i < len(unicode_text):
character = unicode_text[i]
try:
name_unicode = unicodedata.name(character)
except:
if character == "\n":
output += " "
name = name_unicode.lower()
name = name.replace(" ", ".")
if name.find("combining") == -1: #non-combining character
if maincharacter != None and len(combinewith) > 0:
#do lookup
combinewith.sort()
for format,combination in accentmap:
if combination == combinewith:
try:
output += format % charactermap[maincharacter]
except KeyError:
sys.stderr.write("Teubner: Unknown character '%s'\n" % maincharacter)
break
maincharacter = None
combinewith = []
elif maincharacter != None:
try:
output += charactermap[maincharacter]
maincharacter = None
except KeyError:
sys.stderr.write("Teubner: Unknown character '%s'\n" % maincharacter)
maincharacter = name_unicode
else: #combining character
if maincharacter != None:
combinewith.append(name)
else:
output += "e"
i += 1
return output
if __name__ == "__main__":
import unicodedata
teststr = u"ἔθαψε, ὡς οἰκὸς ἦν"
print unicode_to_teubner(unicodedata.normalize("NFD", teststr))
for a in accentmap:
sort = sorted(a[1])
#unicodedata.normalize(u"aäb", "NFD"))
greekocr-1.0.1/gamera/toolkits/greekocr/plugins/ 0000755 0001750 0001750 00000000000 11635564234 021251 5 ustar dalitz dalitz greekocr-1.0.1/gamera/toolkits/greekocr/plugins/__init__.py 0000644 0001750 0001750 00000000207 11511157302 023344 0 ustar dalitz dalitz # You need to have some sort of __init__.py file here
# in order to import modules in this directory.
# It is deliberately empty.
greekocr-1.0.1/gamera/toolkits/greekocr/greekocr.py 0000644 0001750 0001750 00000017676 11635564123 021761 0 ustar dalitz dalitz # -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
# Copyright (C) 2010-2011 Christian Brandt
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
from gamera.core import *
init_gamera()
from gamera import knn
from gamera.plugins import pagesegmentation
from gamera.plugins.pagesegmentation import textline_reading_order
from gamera.classify import ShapedGroupingFunction
from gamera.plugins.image_utilities import union_images
from gamera.toolkits.ocr.ocr_toolkit import *
from gamera.toolkits.ocr.classes import Textline,Page,ClassifyCCs
from gamera.gamera_xml import glyphs_to_xml
from gamera.knn_editing import edit_cnn
from gamera.toolkits.greekocr.singlediacritics import *
from gamera.toolkits.greekocr.wholisticdiacritics import *
import unicodedata
import codecs
def clean_classifier(cknn):
glyphs = cknn.get_glyphs()
print "old %d" % len(glyphs)
sorted_glyphs = sorted(glyphs, key=lambda g: g.to_rle())
new_glyphs = []
last_rle = sorted_glyphs[0].to_rle()
new_glyphs.append(sorted_glyphs[0])
for i in range(1, len(sorted_glyphs) -1):
if last_rle != sorted_glyphs[i].to_rle():
new_glyphs.append(sorted_glyphs[i])
else:
print sorted_glyphs[i].get_main_id()
print "new after removing duplicates: %d" % len(new_glyphs)
cknn.set_glyphs(new_glyphs)
cknn = edit_cnn(cknn)
print "new after cnn: %d" % len(cknn.get_glyphs())
return cknn
class GreekOCR(object):
"""Provides the functionality for GreekOCR. The following parameters
control the recognition process:
**cknn**
The kNNInteractive classifier.
**mode**
The mode for dealing with accents.
Can be ``wholistic`` or ``separatistic``.
"""
def __init__(self, mode="wholistic"):
"""Signature:
``init (mode="wholistic")``
where *mode* can be "wholistic" or "separatistic".
"""
self.optimizeknn = False
self.debug = False
self.cknn = knn.kNNInteractive([], ["aspect_ratio", "volume64regions", "moments", "nholes_extended"], 0)
self.autogroup = None
self.output = ""
self.mode = mode
def load_trainingdata(self, trainfile):
"""Loads the training data. Signature:
``load_trainingdata (trainfile)``
where *trainfile* is an Gamera XML file containing training data.
Make sure that the training file matches the *mode* (wholistic
or separatistic).
"""
self.cknn.from_xml_filename(trainfile)
if self.optimizeknn:
self.cknn = clean_classifier(self.cknn)
def segment_page(self):
if(self.mode == "separatistic"):
self.page = SinglePage(self.img)
else:
self.page = WholisticPage(self.img)
if self.debug:
print "start page segmentation..."
t = time.time()
self.page.segment()
if self.debug:
t = time.time() - t
print "\t segmentation done [",t,"sec]"
def get_page_glyphs(self, image):
"""Returns a list of segmented CCs using the selected segmentation
approach on the given image. This list can be used for creating training data.
Signature:
``get_page_glyphs (image)``
where *image* is a Gamera image.
"""
if image.data.pixel_type != ONEBIT:
image = image.to_onebit()
self.img = image
self.segment_page()
glyphs = []
for line in self.page.textlines:
for g in line.glyphs:
glyphs.append(g)
return glyphs
def save_debug_images(self):
"""Saves the following images to the current working directory:
**debug_lines.png**
Has a frame drawn around each detected line.
**debug_chars.png**
Has a frame drawn around each detected character.
**debug_words.png**
Has a frame drawn around each detected word.
"""
rgbfilename = "debug_lines.png"
rgb = self.page.show_lines()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
rgbfilename = "debug_chars.png"
rgb = self.page.show_glyphs()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
rgbfilename = "debug_words.png"
rgb = self.page.show_words()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
def classify_text(self):
self.output = ""
for line in self.page.textlines:
line.glyphs = \
self.cknn.classify_and_update_list_automatic(line.glyphs)
line.sort_glyphs()
self.output = self.output + line.to_string() + "\n"
self.output = self._normalize(self.output)
def get_text(self):
return self.output
def process_image(self, image):
"""Recognizes the given image and returns the recognized text
as Unicode string. Signature:
``process_image (image)``
where *image* is a Gamera image. The recognized text is additionally stored
in the ``GreekOCR`` property *output*, which can subsequently be written to
a file with save_text_unicode_ or save_text_teubner_.
Make sure that you have called load_trainingdata_ before!
"""
if image.data.pixel_type != ONEBIT:
image = image.to_onebit()
self.img = image
if self.debug:
print "Doing page Segmentation"
self.segment_page()
if self.debug:
print "Classifying Text"
self.classify_text()
if self.debug:
print "Returning Output"
return self.get_text()
def save_text_xetex(self, filename):
data = \
'''\documentclass[11pt]{article}
\usepackage{xltxtra}
\setmainfont[Mapping=tex-text]{GFS Porson}
\\begin{document}
%s
\end{document}''' % self.output.replace("\n", "\n\n")
f = codecs.open(filename, "w", encoding='utf-8')
f.write(data)
f.close()
def save_text_unicode(self, filename):
"""Stores the recognized text to the given *filename* as Unicode string.
Signature
``save_text_unicode(filename)``
Make sure that you have called process_image_ before!
"""
f = codecs.open(filename, "w", encoding='utf-8')
f.write(self.output)
f.close()
def save_text_teubner(self, filename):
"""Stores the recognized text to the given *filename* as a LaTeX
document utilizing the Teubner style for representing Greek characters and
accents.
Signature
``save_text_teubner(filename)``
Make sure that you have called process_image_ before!
"""
from unicode_teubner import unicode_to_teubner
data = '''
\documentclass[10pt]{article}
\usepackage[polutonikogreek]{babel}
\usepackage[or]{teubner}
\\begin{document}
\selectlanguage{greek}
%s
\end{document}
''' % unicode_to_teubner(self.output).replace("\n", "\n\n")
f = codecs.open(filename, "w", encoding='utf-8')
f.write(data)
f.close()
def _normalize(self,str):
str = unicodedata.normalize("NFD", str)
output = u""
combined = []
for i in str:
is_combining = True
try:
is_combining = unicodedata.combining(i) > 0 or unicodedata.name(i).find("ACCENT") >= 0
except:
is_combining = False
if not is_combining:
for j in sorted(combined):
output += j
combined = []
output += i
else:
combined.append(i)
if len(combined) > 0:
for j in sorted(combined):
output += j
return unicodedata.normalize("NFD", output)
greekocr-1.0.1/gamera/toolkits/greekocr/wholisticdiacritics.py 0000644 0001750 0001750 00000014643 11635564123 024213 0 ustar dalitz dalitz # -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
# Copyright (C) 2010-2011 Christian Brandt
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
from gamera.core import *
from gamera.plugins.pagesegmentation import textline_reading_order
from gamera.toolkits.ocr.ocr_toolkit import *
from gamera.toolkits.ocr.classes import Textline,Page,ClassifyCCs
import gamera.kdtree as kdtree
import unicodedata
import sys
class WholisticPage(Page):
def __init__(self, img):
self.img = img
#cknn = knn.kNNInteractive([], ["aspect_ratio", "volume64regions", "moments", "nholes_extended"], 0)
#cknn.from_xml_filename("x01/classifier-all-2/classifier_glyphs.xml")
#if(opt.ccsfilter):
# the_ccs = ccs
#else:
the_ccs = img.cc_analysis()
self.median_cc = int(median([cc.nrows for cc in the_ccs]))
#autogroup = ClassifyCCs(cknn)
#autogroup.parts_to_group = 3
#autogroup.grouping_distance = max([2,median_cc / 8])
Page.__init__(self, img)#, classify_ccs=autogroup)
#print "autogrouping glyphs activated."
#print "maximal autogroup distance:", autogroup.grouping_distance
def lines_to_chars(self):
self.textlines = self.get_line_glyphs(self.img, self.ccs_lines)
def check_glyph_greek_accent(self, item,glyph):
remove = []
add = []
result = []
if((glyph.ul_x == item.ul_x and glyph.ul_y == item.ul_y and glyph.lr_x == item.lr_x and glyph.lr_y == item.lr_y) or \
glyph.intersects_x(item) or \
(glyph.distance_bb(item) < 3 and \
(glyph.distance_cx(item) < (self.median_cc / 2) or 2*glyph.nrows < item.nrows or 2*item.nrows < glyph.nrows ) \
)\
): ##nebeinander?
# print "y"
remove.append(glyph)
remove.append(item)
new = union_images([item,glyph])
add.append(new)
result.append(add) #result[0] == ADD
result.append(remove) #result[1] == REMOVE
return result
def get_line_glyphs(self,image,textlines):
i=0
show = []
lines = []
ret,sub_ccs = image.sub_cc_analysis(textlines)
#print "doc has %d lines" % len(sub_ccs)
linenumber = 0
for ccs in sub_ccs:
linenumber = linenumber + 1
#print "line %d" % linenumber
line_bbox = Rect(textlines[i])
i = i + 1
glyphs = ccs[:]
newlist = []
remove = []
add = []
result = []
glyphs.sort(lambda x,y: cmp(x.ul_x, y.ul_x))
#print "first run"
for position, item in enumerate(glyphs):
olditem = item
left = max(0,position - 5)
right = min(position + 5, len(glyphs))
checklist = glyphs[left:right]
for glyph in checklist:
if(item == glyph):
continue
result = self.check_glyph_greek_accent(item,glyph)
if(len(result[0]) > 0): #something has been joind...
item = result[0][0]
#add.append(result[0][0]) #joind glyph
remove.append(result[1][0]) #first part of joind one
remove.append(result[1][1]) #second part of joind one
if olditem != item:
add.append(item)
for elem in remove:
if(elem in glyphs):
glyphs.remove(elem)
for elem in add:
glyphs.append(elem)
remove = []
add = []
glyphs = textline_reading_order(glyphs)
glyphs = list(set(glyphs))
#print len(glyphs)
new_line = WholisticTextline(line_bbox)
final = []
if(len(glyphs) > 0):
for glyph in glyphs:
final.append(glyph)
new_line.add_glyphs(final,False)
#new_line.sort_glyphs() #reading order -- from left to right
lines.append(new_line)
for glyph in glyphs:
show.append(glyph)
return lines
class WholisticTextline(Textline):
#called after classification
def sort_glyphs(self):
self.glyphs = textline_reading_order(self.glyphs)
#begin calculating threshold for word-spacing
spacelist = []
for i in range(len(self.glyphs) - 1):
spacelist.append(self.glyphs[i + 1].ul_x - self.glyphs[i].lr_x)
if(len(spacelist) > 0):
threshold = median(spacelist)
threshold = threshold * 2.0
else:
threshold = 0
#end calculatin threshold for word-spacing
self.words = chars_make_words(self.glyphs, threshold)
def to_string(self):
k = 3
max_k = 10
output = u""
for word in self.words:
characters = []
skipids = ["manual.xi.upper", "manual.xi.lower", "manual.theta.outer"]
for glyph in word:
mainid = glyph.get_main_id()
if mainid == "comma" or mainid == "combining.comma.above":
#print "%s - center_y: %d - med_center: %d" % (mainid, glyph.center.y, med_center)
if glyph.center.y > self.bbox.center.y:
glyph.classify_automatic("comma")
else:
glyph.classify_automatic("combining.comma.above")
mainid = glyph.get_main_id()
mainid = mainid.split(".and.")
for a in mainid:
char = return_char(a)
#print "added %s to output" % char
output = output + char#unicodedata.normalize('NFD', char)
output = output + " "
return output
greekocr-1.0.1/gamera/toolkits/greekocr/__init__.py 0000644 0001750 0001750 00000002505 11635564123 021700 0 ustar dalitz dalitz # -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
# Copyright (C) 2010-2011 Christian Brandt
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
"""
Toolkit setup
This file is run on importing anything within this directory.
Its purpose is only to help with the Gamera GUI shell,
and may be omitted if you are not concerned with that.
"""
from gamera import toolkit
from gamera.toolkits.greekocr import compare
from gamera.toolkits.greekocr.greekocr import *
# Let's import all our plugins here so that when this toolkit
# is imported using the "Toolkit" menu in the Gamera GUI
# everything works.
greekocr-1.0.1/PKG-INFO 0000644 0001750 0001750 00000000510 11635564234 013754 0 ustar dalitz dalitz Metadata-Version: 1.0
Name: greekocr
Version: 1.0.1
Summary: An addon Greek OCR toolkit for the Gamera framework for document analysis and recognition.
Home-page: http://gamera.sourceforge.net/
Author: Christian Brandt and Christoph Dalitz
Author-email: UNKNOWN
License: GNU GPL version 2
Description: UNKNOWN
Platform: UNKNOWN
greekocr-1.0.1/doc/ 0000755 0001750 0001750 00000000000 11635564234 013430 5 ustar dalitz dalitz greekocr-1.0.1/doc/html/ 0000755 0001750 0001750 00000000000 11635564234 014374 5 ustar dalitz dalitz greekocr-1.0.1/doc/html/functions.html 0000644 0001750 0001750 00000012562 11535422120 017262 0 ustar dalitz dalitz
GreekOCR Toolkit: Global Functions
The toolkit defines a number of free function which are not image
methods. These are defined in different modules and can be imported
in a python script with
The purpose of the GreekOCR Toolkit is to help building optical character
recognition (OCR) systems for text documents with polytonal Greek text, i.e.
classical Greek with a wide variety of accents. It can be used as is, but
can also be used as a building block for implementing a custom OCR system
for polytonal Greek.
The toolkit is based on and requires the Gamera framework for document
analysis and recognition. Moreover it requires the OCR toolkit for Gamera.
As an addon package for Gamera, it provides
a ready-to-run python script greekocr4gamera.py which acts as
a basic GreekOCR-system
python library functions for building a custom GreekOCR system
Please note that the toolkit currently does not include any training data.
This means that you must create a training data base of Greek characters
before you can use the script greekocr4gamera.py.
Compared to texts with Roman letters or modern (or monotonal) Greek,
classical (or polytonal) Greek uses a large number of accents that
can be used in a wide range of combinations. Compared to the ordinary
OCR process, this requires a special treatment both for attaching accents
to characters and for recognizing the resulting combinations. From a
general point of view, two different approaches are possible:
Wholistic approach:
Identify each character as a whole, including its accents.
This approach requires that all possible character/accents combinations
have been predefined and are present as samples in the training data.
Separatistic approach:
Identify core characters and accents separately and combine them
subsequently. In this case, the training data contains the core
characters and the individual accents.
This toolkit offers both possibilities. You must therefore make sure
that your training data matches the chosen recognition approach.
As the segmentation of the individual characters is based on a connected
component analysis, the toolkit cannot deal with touching characters, unless
they have been trained as combinations. It is therefore in general only
applicable to printed documents, rather than handwritten documents.
From a user's perspective, there are some points to beware in this toolkit:
It does not include methods for preprocessing like skew correction
or noise removal. For this purpose, the standard routines shipped with
Gamera must be used beforehand, e.g. rotation_angle_projections for
skew correction, or despeckle for noise removal.
It does not provide prototypes of the Greek characters and accents.
This means that characters must be trained on sample pages before using
the toolkit.
The standard page segmentation algorithm for textline separation
is currently very basic.
We have only tested the toolkit on Linux and MacOS X, but as
the toolkit is written entirely in Python, the following
instructions should work for any operating system.
Command 1) compiles the toolkit from the sources and command 2) installs
it. As the latter requires
root privilegue, you need to use sudo on Linux and MacOS X. On Windows,
sudo is not necessary.
Note that the script greekocr4gamera.py is installed into /usr/bin or
/usr/local/bin on Linux and newer versions of MacOS X, but into
/System/Library/Frameworks/Python.framework/Versions/2.x/bin
on older MacOS X versions. As the latter directory is not in the standard
search path, you could either add it to your search path, or install the
scripts additionally into /usr/bin on MacOS X with:
# install scripts into standard path (older MacOS X, optional)
sudo python setup.py install_scripts -d /usr/bin
If you want to regenerate the documentation, go to the doc directory
and run the gendoc.py script. The output will be placed in the doc/html/
directory. The contents of this directory can be placed on a webserver
for convenient viewing.
Note
Before building the documentation you must install the
toolkit. Otherwise gendoc.py will not find the plugin documentation.
The above installation with pythonsetup.pyinstall will install
the toolkit system wide and thus requires root privileges. If you do
not have root access (Linux) or are no sudoer (MacOS X), you can
install the GreekOcr toolkit into your home directory. Note however
that this also requires that Gamera is installed into your home directory.
It is currently not possible to install Gamera globally and only toolkits
locally.
Here are the steps to install both Gamera and the OCR toolkit into
~/python:
All python library files of this toolkit are installed into the
gamera/toolkits/greekocr subdirectory of the Python library folder.
Thus it is sufficient to remove this directory for an uninstallation.
Where the python library folder is depends on your system and python version.
Here are the folders that you need to remove on MacOS X and Debian Linux
("2.x" stands for the python version; replace it with your actual version):
The standalone scripts are installed into /usr/bin or /usr/local/bin
(Linux) or /System/Library/Frameworks/Python.framework/Versions/2.x/bin
(older MacOS X), unless you have explicitly chosen a different location with
the options --prefix or --home during installation.
The documentation was written by Christoph Dalitz.
Permission is granted to copy, distribute and/or modify this documentation
under the terms of the Creative Commons Attribution Share-Alike License (CC-BY-SA) v3.0. In addition, permission is granted to use and/or
modify the code snippets from the documentation without restrictions.
The toolkit provides the functionality to segment an image page into
text lines, words and characters, to sort them in reading-order,
and to generate an output string.
Before you can use the OCR toolkit, you must first train characters
from sample pages, which will then be used by the toolkit for classifying
characters:
Hence the proper use of this toolkit requires the following two steps:
training of sample characters on representative document images.
This step is interactive and is done with the Gamera GUI, as described
in the Gamera training tutorial
recognition of documents with the aid of this training data.
This step usually runs automatically without user interaction.
For this purpose, the tools from the present toolkit can be used.
There are two options to use this toolkit: you can either use the script
greekocr4gamera.py as provided by the toolkit, or you can build your
own recognition scripts with the aid of the python library functions
provided by the toolkit. Both alternatives are described below.
As explained in the GreekOCR toolkit overview, you must create different
training data, depending on the approach for dealing with accents:
for the wholistic approach, you must train all possible (or frequent)
combinations characters and accents
for the separatistic approach, you must train characters and accents
separately
The wholistic approach has the disadvantage that the training data
will generally be incomplete because rare combinations are unlikely
to appear in the samples used for training. Moreover, it requires
much more training effort. Depending on the documents under consideration,
it might however be that the one or the other approach yields better results;
testing both approaches might therefore pay off.
A list of CCs for training using the wholistic or separatistic algorithms
on image can be created with:
When accents frequently touch the characters, you should train
these combinations even for the separatistic approach, because
the glyph segmentation is based on a connected component analysis,
which cannot split touching symbols.
For "separatistic" recognition, the characters and accents must be trained
separately. The class names for the characters must correspond to the
names in the Unicode table Greek, and the names for the accents must
correspond to the Unicode table Combining Diacritical Marks.
The latter typically start with the word COMBINING. For punctuation
marks like "full stop", the names from the Unicode table Basic Latin
can be used.
The following table lists some examples. For touching characters or accents,
you can combine their Unicode names with AND, as in the following
table demonstrated for the touching sigma and tau and the touching
comma and acute:
For "wholistic" recognition, no isolated accents are trianed. In contrast,
each character is trained in all occuring combinations with accents.
The Unicode names of the character and the accents are concatenated
with the word and, as shown in the following examples:
The order of the accents in the class names is not important, because the
accent order will be normalized automatically during the recognition process.
The greekocr4gamera.py script takes an image and already trained data and
segments the picture into single glyphs. The training-data is used to
classify those glyphs and converts them into an output code. The output
code can be a Unicode string or a LaTeX document utilizing the
Teubner style. The output is written to standard-out or can optionally
be stored in a file.
The end user application greekocr4gamera.py will be installed to /usr/bin
or /usr/local/bin unless you habe explicitly chosen a different location.
Its synopsis is:
Options can be in short (one dash, one character) or long form (two dashes,
string). When called with -h, -? or any other invalid option,
a usage message will be printed. The valid options are:
-xtrainingdata, --xml-file=trainingdata
This option is required. trainingdata must be an xml file created
with Gamera's training dialog.
-uoutfile, --unicode=outfile
Writes the Unicode output to outfile.
When neither -u nor -t are specified, the unicode
output is written to stdout.
-toutfile, --teubner=outfile
Writes the LaTeX output to outfile.
-s, --separatistic
Use the separatistic approach for recognition.
-w, --wholistic
Use the wholistic approach for recognition (default).
--deskew
Do a skew correction.
--filter
Filter out very large (images) and very small (noise) components.
--debug
Write images debug_lines.png, debug_words.png and debug_chars.png
to working directory for debugging purposes.
If you want to write your own scripts for recognition, you
can use greekocr4gamera.py as a good starting point.
In Greek OCR functionality is implemented in the class GreekOCR,
which must import at the beginning of your script:
fromgamera.toolkits.greekocrimportGreekOCR
After that you can instantiate a GreekOCR object and can recognize
an image with the following methods:
g=GreekOCR()g.mode="wholistic"# or "separatistic"g.load_trainingdata("wholistic.xml")image=load_image("imagefile.png")output=g.process_image(image)printoutput
This will print the Unicode result to stdout. To save it to a file
either in Unicode or LaTeX with the Teubner style, use the following
methods:
Returns a list of segmented CCs using the selected segmentation
approach on the given image. This list can be used for creating training data.
Signature:
Recognizes the given image and returns the recognized text
as Unicode string. Signature:
process_image(image)
where image is a Gamera image. The recognized text is additionally stored
in the GreekOCR property output, which can subsequently be written to
a file with save_text_unicode or save_text_teubner.
Stores the recognized text to the given filename as a LaTeX
document utilizing the Teubner style for representing Greek characters and
accents.
Signature
save_text_teubner(filename)
Make sure that you have called process_image before!
greekocr-1.0.1/doc/src/ 0000755 0001750 0001750 00000000000 11635564234 014217 5 ustar dalitz dalitz greekocr-1.0.1/doc/src/gamera.toolkits.greekocr.greekocr.GreekOCR.txt 0000644 0001750 0001750 00000000546 11564155126 025065 0 ustar dalitz dalitz class ``GreekOCR``
==================
``GreekOCR``
------------
In module ``gamera.toolkits.greekocr.greekocr``
.. docstring:: gamera.toolkits.greekocr.greekocr GreekOCR
:no_title:
.. docstring:: gamera.toolkits.greekocr.greekocr GreekOCR __init__ load_trainingdata get_page_glyphs process_image save_debug_images save_text_unicode save_text_teubner
greekocr-1.0.1/doc/src/usermanual.txt 0000700 0001750 0001750 00000025620 11535675604 017135 0 ustar dalitz dalitz ==============================
GreekOCR Toolkit User's Manual
==============================
This documentation is for those who want to use the toolkit for
polytonal Greek OCR, but are not interested in extending the toolkit itself.
Overview
''''''''
The toolkit provides the functionality to segment an image page into
text lines, words and characters, to sort them in reading-order,
and to generate an output string.
Before you can use the OCR toolkit, you must first train characters
from sample pages, which will then be used by the toolkit for classifying
characters:
.. image:: images/overview.png
Hence the proper use of this toolkit requires the following two steps:
- training of sample characters on representative document images.
This step is interactive and is done with the Gamera GUI, as described
in the `Gamera training tutorial`__
- recognition of documents with the aid of this training data.
This step usually runs automatically without user interaction.
For this purpose, the tools from the present toolkit can be used.
.. __: http://gamera.sourceforge.net/doc/html/training_tutorial.html
There are two options to use this toolkit: you can either use the script
``greekocr4gamera.py`` as provided by the toolkit, or you can build your
own recognition scripts with the aid of the python library functions
provided by the toolkit. Both alternatives are described below.
Training
''''''''
As explained in the `GreekOCR toolkit overview`__, you must create different
training data, depending on the approach for dealing with accents:
- for the *wholistic* approach, you must train all possible (or frequent)
combinations characters and accents
- for the *separatistic* approach, you must train characters and accents
separately
.. __: index.html#approaches-for-recognizing-accents
The wholistic approach has the disadvantage that the training data
will generally be incomplete because rare combinations are unlikely
to appear in the samples used for training. Moreover, it requires
much more training effort. Depending on the documents under consideration,
it might however be that the one or the other approach yields better results;
testing both approaches might therefore pay off.
A list of CCs for training using the *wholistic* or *separatistic* algorithms
on *image* can be created with:
.. code:: Python
from gamera.toolkits.greekocr import GreekOCR
from gamera import knn
classifier = knn.kNNInteractive()
g = GreekOCR("wholistic") #or separatistic
ccs = g.get_page_glyphs(image)
classifier.display(ccs, image)
.. note:: When accents frequently touch the characters, you should train
these combinations even for the *separatistic* approach, because
the glyph segmentation is based on a connected component analysis,
which cannot split touching symbols.
Symbol names for "separatistic" recognition
-------------------------------------------
For "separatistic" recognition, the characters and accents must be trained
separately. The class names for the characters must correspond to the
names in the Unicode table `Greek`_, and the names for the accents must
correspond to the Unicode table `Combining Diacritical Marks`_.
The latter typically start with the word ``COMBINING``. For punctuation
marks like "full stop", the names from the Unicode table `Basic Latin`_
can be used.
.. _Greek: http://unicode.org/charts/PDF/U0370.pdf
.. _`Combining Diacritical Marks`: http://unicode.org/charts/PDF/U0300.pdf
.. _`Basic Latin`: http://unicode.org/charts/PDF/U0000.pdf
The following table lists some examples. For touching characters or accents,
you can combine their Unicode names with ``AND``, as in the following
table demonstrated for the touching *sigma* and *tau* and the touching
*comma* and *acute*:
+----------------------------+-------------------------------+-------------------------------------------------------+
| Character | Unicode Name(s) | Class Name |
+============================+===============================+=======================================================+
| .. image:: images/sep1.png | ``GREEK CAPITAL LETTER TAU`` | ``greek.capital.letter.tau`` |
+----------------------------+-------------------------------+-------------------------------------------------------+
| .. image:: images/sep2.png | ``GREEK SMALL LETTER DELTA`` | ``greek.small.letter.delta`` |
+----------------------------+-------------------------------+-------------------------------------------------------+
| .. image:: images/sep4.png |``COMBINING GREEK PERISPOMENI``| ``combining.greek.perispomeni`` |
+----------------------------+-------------------------------+-------------------------------------------------------+
| .. image:: images/sep5.png | ``COMBINING COMMA ABOVE`` | ``combining.comma.above`` |
+----------------------------+-------------------------------+-------------------------------------------------------+
| .. image:: images/sep7.png | ``HYPHEN-MINUS`` | ``hyphen-minus`` |
+----------------------------+-------------------------------+-------------------------------------------------------+
| .. image:: images/sep3.png | ``GREEK SMALL LETTER SIGMA``, |``greek.small.letter.sigma.and.greek.small.letter.tau``|
| | ``GREEK SMALL LETTER TAU`` | |
+----------------------------+-------------------------------+-------------------------------------------------------+
| .. image:: images/sep6.png | ``COMBINING COMMA ABOVE``, | ``combining.comma.above.and.combining.acute.accent`` |
| | ``COMBINING ACUTE ACCENT`` | |
+----------------------------+-------------------------------+-------------------------------------------------------+
Symbol names for "wholistic" recognition
----------------------------------------
For "wholistic" recognition, no isolated accents are trianed. In contrast,
each character is trained in all occuring combinations with accents.
The Unicode names of the character and the accents are concatenated
with the word ``and``, as shown in the following examples:
+----------------------------+---------------------------------------------------------------------------------------+
| Character | Class Name |
+============================+=======================================================================================+
| .. image:: images/who1.png | ``greek.small.letter.alpha`` |
+----------------------------+---------------------------------------------------------------------------------------+
| .. image:: images/who2.png | ``greek.small.letter.alpha.and.combining.acute.accent`` |
+----------------------------+---------------------------------------------------------------------------------------+
| .. image:: images/who3.png | ``greek.small.letter.alpha.and.combining.comma.above`` |
+----------------------------+---------------------------------------------------------------------------------------+
| .. image:: images/who4.png | ``greek.small.letter.alpha.and.combining.comma.above.and.combining.acute.accent`` |
+----------------------------+---------------------------------------------------------------------------------------+
| .. image:: images/who5.png | ``greek.small.letter.alpha.and.combining.greek.perispomeni`` |
+----------------------------+---------------------------------------------------------------------------------------+
The order of the accents in the class names is not important, because the
accent order will be normalized automatically during the recognition process.
Using the script ``greekocr4gamera.py``
'''''''''''''''''''''''''''''''''''''''
The *greekocr4gamera.py* script takes an image and already trained data and
segments the picture into single glyphs. The training-data is used to
classify those glyphs and converts them into an output code. The output
code can be a Unicode string or a LaTeX document utilizing the
`Teubner style`_. The output is written to standard-out or can optionally
be stored in a file.
.. _`Teubner style`: http://www.ctan.org/tex-archive/macros/latex/contrib/teubner/
The end user application *greekocr4gamera.py* will be installed to ``/usr/bin``
or ``/usr/local/bin`` unless you habe explicitly chosen a different location.
Its synopsis is::
greekocr4gamera.py -x [options]
Options can be in short (one dash, one character) or long form (two dashes,
string). When called with ``-h``, ``-?`` or any other invalid option,
a usage message will be printed. The valid options are:
``-x`` *trainingdata*, ``--xml-file``\ =\ *trainingdata*
This option is required. *trainingdata* must be an xml file created
with `Gamera's training dialog`__.
.. __: http://gamera.sourceforge.net/doc/html/training_tutorial.html
``-u`` *outfile*, ``--unicode``\ =\ *outfile*
Writes the Unicode output to *outfile*.
When neither ``-u`` nor ``-t`` are specified, the unicode
output is written to stdout.
``-t`` *outfile*, ``--teubner``\ =\ *outfile*
Writes the LaTeX output to *outfile*.
``-s``, ``--separatistic``
Use the separatistic approach for recognition.
``-w``, ``--wholistic``
Use the wholistic approach for recognition (default).
``--deskew``
Do a skew correction.
``--filter``
Filter out very large (images) and very small (noise) components.
``--debug``
Write images *debug_lines.png*, *debug_words.png* and *debug_chars.png*
to working directory for debugging purposes.
Writing custom scripts
''''''''''''''''''''''
If you want to write your own scripts for recognition, you
can use ``greekocr4gamera.py`` as a good starting point.
In Greek OCR functionality is implemented in the class GreekOCR__,
which must import at the beginning of your script:
.. __: gamera.toolkits.ocr.classes.GreekOCR.html
.. code:: Python
from gamera.toolkits.greekocr import GreekOCR
After that you can instantiate a *GreekOCR* object and can recognize
an image with the following methods:
.. code:: Python
g = GreekOCR()
g.mode = "wholistic" # or "separatistic"
g.load_trainingdata("wholistic.xml")
image = load_image("imagefile.png")
output = g.process_image(image)
print output
This will print the Unicode result to stdout. To save it to a file
either in Unicode or LaTeX with the Teubner style, use the following
methods:
.. code:: Python
g.save_text_unicode("unicode-output.txt")
g.save_text_teubner("teubner-output.tex")
For more information on how to fine control the recognition process,
see the `developer's documentation`__.
.. __: index.html#developer-s-documentation
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greekocr-1.0.1/doc/src/classes.txt 0000644 0001750 0001750 00000000262 11564155126 016412 0 ustar dalitz dalitz =======
Classes
=======
Alphabetical
-------------
**G**
GreekOCR_ (gamera.toolkits.greekocr.greekocr.GreekOCR)
.. _GreekOCR: gamera.toolkits.greekocr.greekocr.GreekOCR.html greekocr-1.0.1/doc/src/images/ 0000755 0001750 0001750 00000000000 11635564234 015464 5 ustar dalitz dalitz greekocr-1.0.1/doc/src/images/who5.png 0000644 0001750 0001750 00000001513 11533703222 017041 0 ustar dalitz dalitz PNG
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