mirror of https://github.com/NaN-tic/nanscan.git
- Fixed doxygen file.
- Added invoice recognition module. Still missing block detection.
This commit is contained in:
Albert Cervera i Areny
parent
2cbba682f0
commit
0eb944c512
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@ -0,0 +1,153 @@
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# Copyright (C) 2009 by Albert Cervera i Areny
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# albert@nan-tic.com
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the
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# Free Software Foundation, Inc.,
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# 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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from NanScan.LevenshteinDistance import *
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from NanScan.Range import *
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from NanScan.TextPatterns import *
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class InvoiceRecognizer:
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Tags = {
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'number': {
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'tag': [
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u'factura',
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u'numero factura',
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u'factura numero',
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u'num. de factura',
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u'factura num.'
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],
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'type': 'mostly-numeric'
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},
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'date': {
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'tag': [
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u'fecha',
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u'fecha factura',
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u'fecha emision',
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u'data:',
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u'data',
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u'data factura'
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],
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'type': 'date'
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# With dates we need to be able to find a date with
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# the format '1 Sep. 2009'. Also we need to find the
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# date without a tag. Something like:
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#
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# 'fallback': functionName,
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#
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# might be appropiate for those cases in which the
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# tag can't be found.
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},
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'amount': {
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'tag': [
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u'total',
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u'total factura',
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u'total a pagar (euros)'
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],
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'type': 'numeric'
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}
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}
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def recognize(self, recognizer):
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#text = recognizer.textInRegion('text')
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analyzer = recognizer.analyzers['text']
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self.textLines = analyzer.textLinesWithSpaces()
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result = ''
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for tag in InvoiceRecognizer.Tags:
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result += 'Tag: %s, Value: %s\n' % ( tag, self.findTagValue( tag ) )
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return result
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def formatedLine(self, line):
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text = u''
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for c in line:
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text += c.character
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return text
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def findText(self, textToFind):
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ranges = Range.extractAllRangesFromDocument( self.textLines, len(textToFind) )
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for ran in ranges:
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text = ran.text()
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value = Levenshtein.levenshtein( text, textToFind )
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ran.distance = value
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ranges.sort( rangeDistanceComparison )
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if ranges:
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return ranges[0]
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else:
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return None
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def findTagValue(self, tag):
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ranges = []
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for tagData in InvoiceRecognizer.Tags[tag]['tag']:
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ran = self.findText( tagData )
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if ran:
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ranges.append( ran )
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ranges.sort( rangeDistanceComparison )
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#ran = ranges[0]
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distance = ranges[0].distance
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sameDistance = [x for x in ranges if x.distance == distance]
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sameDistance.sort( rangeLengthComparison )
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#print "SECOND 5: ", [x.text().encode('ascii','ignore') for x in sameDistance[:5]]
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ran = sameDistance[-1]
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print "RANGE FOR TAG %s: %s" % ( tag, ran.text().encode('ascii','ignore') )
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# Extract text on the right
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line = self.formatedLine( self.textLines[ ran.line ] )
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rightValue = line[ran.pos+ran.length+1:].strip().split(' ')[0]
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print "R: ", line[ran.pos+ran.length+1:].strip().encode('ascii','ignore')
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print "rightValue: ", rightValue.encode('ascii','ignore')
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print "SAME LINE: ", line.encode('ascii','ignore')
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# Extract text on the bottom
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if ran.line < len(self.textLines)-1:
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line = self.textLines[ran.line+1]
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print "NEXT LINE: ", self.formatedLine( self.textLines[ran.line+1] ).encode('ascii','ignore')
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boxBottom = ran.rect()
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boxBottom.moveTop( line[0].box.y() )
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bottomValue = u''
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for c in line:
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if c.box.intersects( boxBottom ):
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bottomValue += c.character
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else:
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bottomValue = u''
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# Decide which of both values match the given tag type
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type = InvoiceRecognizer.Tags[ tag ][ 'type' ]
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if type == 'numeric':
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if isFloat( rightValue ):
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return textToFloat( rightValue )
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elif isFloat( bottomValue ):
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return textToFloat( bottomValue )
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else:
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return None
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elif type == 'date':
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if isDate( rightValue ):
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return textToDate( rightValue )
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elif isDate( bottomValue ):
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return textToDate( bottomValue )
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else:
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return None
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elif type == 'mostly-numeric':
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if isMostlyNumeric( rightValue ):
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return rightValue
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elif isMostlyNumeric( bottomValue ):
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return bottomValue
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else:
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return rightValue
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else:
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return rightValue
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@ -0,0 +1,19 @@
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# Copyright (C) 2009 by Albert Cervera i Areny
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# albert@nan-tic.com
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the
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# Free Software Foundation, Inc.,
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# 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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107
NanScan/Ocr.py
107
NanScan/Ocr.py
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@ -44,7 +44,7 @@ def boxComparison(x, y):
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else:
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return 0
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## @breif This class allows using an OCR and provides several convenient functions
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## @brief This class allows using an OCR and provides several convenient functions
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# regarding text and image processing such as deskewing or obtaining formated text.
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class Ocr(Analyzer):
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file = ""
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@ -132,12 +132,12 @@ class Ocr(Analyzer):
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## @brief Returns the text of a given region of the image.
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# It's the same as calling formatedText().
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def textInRegion(self, region):
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def textInRegion(self, region=None):
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return self.formatedText( region )
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## @brief Returns the bounding rectangle of the text returned by textInRegion for
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# the given region.
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def featureRectInRegion(self, region):
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def featureRectInRegion(self, region=None):
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lines = self.textLinesWithSpaces( region )
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rect = QRectF()
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for line in lines:
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@ -242,6 +242,58 @@ class Ocr(Analyzer):
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line.sort( boxComparison )
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return lines
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## @brief This function adds spaces between words of a single line of boxes.
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def textLineWithSpaces(self, line):
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width = 0
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count = 0
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left = None
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spacesToAdd = []
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words = []
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for c in line:
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if left:
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# If separtion between previous and current char
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# is greater than a third of the average character
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# width we'll add a space.
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if c.box.left() - left > ( width / count ) / 3:
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if spacesToAdd:
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words.append( line[spacesToAdd[-1]:count] )
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spacesToAdd.append( count )
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# c.character is already a unicode string
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left = c.box.right()
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width += c.box.width()
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count += 1
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# Try to find out if they are fixed sized characters
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# We've got some problems with fixed size fonts. In some cases the 'I' letter will
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# have the width of a pipe but the distance between characters will be fixed. In these
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# cases it's very probable our algorithm will add incorrect spaces before and/or after
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# the 'I' letter. This should be fixed by somehow determining if it's a fixed sized
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# font. The commented code below tries to do just that by calculating distances within
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# the letters of each word. We need to find out if something like this can work and
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# use it.
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#for x in words:
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#dist = []
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#for c in range( len(x)-1 ):
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#dist.append( x[c+1].box.center().x() - x[c].box.center().x() )
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#print 'Paraula: ', (u''.join( [i.character for i in x] )).encode( 'ascii', 'ignore')
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#print 'Distancies: ', dist
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# Reverse so indexes are still valid after insertions
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spacesToAdd.reverse()
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previousIdx = None
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for idx in spacesToAdd:
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c = Character()
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c.character = u' '
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c.box = QRectF()
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c.box.setTop( line[idx - 1].box.top() )
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c.box.setBottom( line[idx - 1].box.bottom() )
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c.box.setLeft( line[idx - 1].box.right() )
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c.box.setRight( line[idx].box.left() )
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line.insert( idx, c )
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## @brief This function is similar to textLines() but adds spaces between words.
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# The result is also a list of lines each line being a list of Character objects.
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def textLinesWithSpaces(self, region=None):
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@ -257,54 +309,7 @@ class Ocr(Analyzer):
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# which is quite usual.
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for line in lines:
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width = 0
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count = 0
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left = None
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spacesToAdd = []
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words = []
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for c in line:
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if left:
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# If separtion between previous and current char
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# is greater than a third of the average character
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# width we'll add a space.
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if c.box.left() - left > ( width / count ) / 3:
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if spacesToAdd:
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words.append( line[spacesToAdd[-1]:count] )
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spacesToAdd.append( count )
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# c.character is already a unicode string
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left = c.box.right()
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width += c.box.width()
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count += 1
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# Try to find out if they are fixed sized characters
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# We've got some problems with fixed size fonts. In some cases the 'I' letter will
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# have the width of a pipe but the distance between characters will be fixed. In these
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# cases it's very probable our algorithm will add incorrect spaces before and/or after
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# the 'I' letter. This should be fixed by somehow determining if it's a fixed sized
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# font. The commented code below tries to do just that by calculating distances within
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# the letters of each word. We need to find out if something like this can work and
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# use it.
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#for x in words:
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#dist = []
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#for c in range( len(x)-1 ):
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#dist.append( x[c+1].box.center().x() - x[c].box.center().x() )
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#print 'Paraula: ', (u''.join( [i.character for i in x] )).encode( 'ascii', 'ignore')
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#print 'Distancies: ', dist
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# Reverse so indexes are still valid after insertions
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spacesToAdd.reverse()
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previousIdx = None
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for idx in spacesToAdd:
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c = Character()
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c.character = u' '
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c.box = QRectF()
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c.box.setTop( line[idx - 1].box.top() )
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c.box.setBottom( line[idx - 1].box.bottom() )
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c.box.setLeft( line[idx - 1].box.right() )
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c.box.setRight( line[idx].box.left() )
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line.insert( idx, c )
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self.textLineWithSpaces( line )
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return lines
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@ -29,6 +29,7 @@ from Trigram import *
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from Hamming import *
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from LevenshteinDistance import *
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from Translator import *
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from Range import *
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import tempfile
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@ -70,7 +71,7 @@ class Recognizer(QObject):
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if type in self.analyzers:
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return self.analyzers[type].boxes
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else:
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return None
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return []
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def analyzersAvailable(self):
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return self.analyzers.keys()
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@ -148,11 +149,9 @@ class Recognizer(QObject):
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# 5 (the default) will make the template move 5 millimeter to the right,
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# 5 to the left, 5 to the top and 5 to the bottom. This means 121 positions
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# per template.
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#
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# Note that the image must have been scanned (using scan() or startScan())
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# before using this function.
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#
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# TODO: Using offsets to find the best template is easy but highly inefficient.
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# a smarter solution should be implemented.
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def findMatchingTemplateByOffset( self, templates, offset = 5 ):
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max = 0
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best = {
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@ -200,9 +199,6 @@ class Recognizer(QObject):
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#
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# Note that the image must have been scanned (using scan() or startScan())
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# before using this function.
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#
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# TODO: Using offsets to find the best template is easy but highly inefficient.
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# a smarter solution should be implemented.
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def findMatchingTemplateByText( self, templates ):
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max = 0
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best = {
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@ -224,7 +220,6 @@ class Recognizer(QObject):
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# Apply template with offset found
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currentDocument = self.extractWithTemplate( template, offset.x(), offset.y() )
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for documentBox in currentDocument.boxes:
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print "Applying..."
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if documentBox.templateBox.type != 'matcher':
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continue
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templateBox = documentBox.templateBox
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@ -373,65 +368,3 @@ class TemplateBoxRangeIterator:
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break
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return result
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def rangeDistanceComparison(x, y):
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if x.distance > y.distance:
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return 1
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elif x.distance < y.distance:
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return -1
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else:
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return 0
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## @brief This class represents a group of characters in a document.
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class Range:
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def __init__(self):
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self.line = 0
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self.pos = 0
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self.length = 0
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self.document = None
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## @brief Returns a unicode string with the text of the current range
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def text(self):
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line = self.document[self.line]
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chars = line[self.pos:self.pos + self.length]
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return u''.join( [x.character for x in chars] )
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## @brief Returns the bounding rectangle of the text in the range
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def rect(self):
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line = self.document[self.line]
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chars = line[self.pos:self.pos + self.length]
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rect = QRectF()
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for c in chars:
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rect = rect.united( c.box )
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return rect
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## @brief Returns a list with all possible ranges of size length of the
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# given document
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@staticmethod
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def extractAllRangesFromDocument(lines, length, width=0):
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if length <= 0:
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return []
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ranges = []
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for line in range(len(lines)):
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if length >= len(lines[line]):
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ran = Range()
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ran.line = line
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ran.pos = 0
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ran.length = len(lines[line])
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ran.document = lines
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#if width:
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# while ran.rect().width() > width:
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# ran.length -= 1
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ranges.append( ran )
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continue
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for pos in range(len(lines[line]) - length + 1):
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ran = Range()
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ran.line = line
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ran.pos = pos
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ran.length = length
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ran.document = lines
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#if width:
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# while ran.rect().width() > width:
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# ran.length -= 1
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ranges.append( ran )
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return ranges
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@ -1,5 +1,5 @@
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from PyQt4.QtGui import *
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from scandialog import *
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from ScanDialog import *
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import sys
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import os
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@ -10,7 +10,7 @@ dialog = ScanDialog()
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if os.name == 'nt':
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FileSaveThreaded.directory = 'c:\\images'
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else:
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FileSaveThreaded.directory = '/tmp'
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FileSaveThreaded.directory = '/tmp/scan'
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dialog.exec_()
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@ -454,6 +454,7 @@ class MainWindow(QMainWindow):
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self.connect( self.actionUnzoom, SIGNAL('triggered()'), self.unzoom )
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self.connect( self.actionFindMatchingTemplateByOffset, SIGNAL('triggered()'), self.findMatchingTemplateByOffset )
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self.connect( self.actionFindMatchingTemplateByText, SIGNAL('triggered()'), self.findMatchingTemplateByText )
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self.connect( self.actionRecognizeInvoice, SIGNAL('triggered()'), self.recognizeInvoice )
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self.toggleImageBoxes()
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QTimer.singleShot( 1000, self.setup )
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self.updateTitle()
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@ -486,6 +487,12 @@ class MainWindow(QMainWindow):
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def findMatchingTemplateByText(self):
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self.findMatchingTemplate( 'text' )
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def recognizeInvoice(self):
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from NanScan.Generics.InvoiceRecognizer import InvoiceRecognizer
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p = InvoiceRecognizer()
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result = p.recognize( self.recognizer )
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QMessageBox.information( self, _('Invoice Recognition'), result )
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def findMatchingTemplate(self, type):
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if type == 'offset':
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title = _('Template search by offset')
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@ -13,14 +13,6 @@
|
|||
<string>Planta</string>
|
||||
</property>
|
||||
<widget class="QWidget" name="centralwidget" >
|
||||
<property name="geometry" >
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>48</y>
|
||||
<width>709</width>
|
||||
<height>439</height>
|
||||
</rect>
|
||||
</property>
|
||||
<layout class="QHBoxLayout" name="horizontalLayout_2" >
|
||||
<item>
|
||||
<layout class="QVBoxLayout" >
|
||||
|
|
@ -35,16 +27,7 @@
|
|||
<property name="windowTitle" >
|
||||
<string/>
|
||||
</property>
|
||||
<widget class="QWidget" name="dockWidgetContents" >
|
||||
<property name="geometry" >
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>20</y>
|
||||
<width>70</width>
|
||||
<height>399</height>
|
||||
</rect>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QWidget" name="dockWidgetContents" />
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
|
|
@ -111,7 +94,7 @@
|
|||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>709</width>
|
||||
<height>22</height>
|
||||
<height>25</height>
|
||||
</rect>
|
||||
</property>
|
||||
<widget class="QMenu" name="menuFile" >
|
||||
|
|
@ -150,6 +133,7 @@
|
|||
<addaction name="actionFindMatchingTemplateByOffset" />
|
||||
<addaction name="actionFindMatchingTemplateByText" />
|
||||
<addaction name="actionDeskew" />
|
||||
<addaction name="actionRecognizeInvoice" />
|
||||
</widget>
|
||||
<addaction name="menuFile" />
|
||||
<addaction name="menuEdit" />
|
||||
|
|
@ -157,14 +141,6 @@
|
|||
<addaction name="menuView" />
|
||||
</widget>
|
||||
<widget class="QToolBar" name="toolBar" >
|
||||
<property name="geometry" >
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>22</y>
|
||||
<width>709</width>
|
||||
<height>26</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle" >
|
||||
<string>toolBar</string>
|
||||
</property>
|
||||
|
|
@ -297,6 +273,11 @@
|
|||
<string>Deskew</string>
|
||||
</property>
|
||||
</action>
|
||||
<action name="actionRecognizeInvoice" >
|
||||
<property name="text" >
|
||||
<string>Recognize Invoice</string>
|
||||
</property>
|
||||
</action>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
|
|
|
|||
|
|
@ -4,4 +4,5 @@
|
|||
#export PYTHONPATH=/home/albert/python/lib/python:../../bin:../../..
|
||||
# NanScan
|
||||
export PYTHONPATH=..:/home/albert/d/koo
|
||||
export LD_LIBRARY_PATH=/usr/lib
|
||||
./planta.py $1
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
# Project related configuration options
|
||||
#---------------------------------------------------------------------------
|
||||
DOXYFILE_ENCODING = UTF-8
|
||||
PROJECT_NAME = NaNScaN
|
||||
PROJECT_NAME = NanScan
|
||||
PROJECT_NUMBER = 1.0
|
||||
OUTPUT_DIRECTORY = .
|
||||
CREATE_SUBDIRS = NO
|
||||
|
|
@ -87,7 +87,7 @@ WARN_LOGFILE =
|
|||
#---------------------------------------------------------------------------
|
||||
# configuration options related to the input files
|
||||
#---------------------------------------------------------------------------
|
||||
INPUT = ../../NaNScaN
|
||||
INPUT = ../../NanScan
|
||||
INPUT_ENCODING = UTF-8
|
||||
FILE_PATTERNS = *.c \
|
||||
*.cc \
|
||||
|
|
|
|||
Loading…
Reference in New Issue