Exemplos de Page em Python

Exemplo n.º 1

Arquivo: import_jp2_and_threshold_test.py Projeto: ryanfb/rigaudon

def filter_and_bbox(imageIn):
    from gamera.toolkits.ocr.classes import Page
    my_filter(imageIn)
    #p = StepTwo(imageIn)
    p = Page(imageIn)
    p.segment()
    return show_lines(p)

Exemplo n.º 2

Arquivo: import_jp2_and_threshold_test.py Projeto: OpenPhilology/rigaudon

def filter_and_bbox(imageIn):
   from gamera.toolkits.ocr.classes import Page
   my_filter(imageIn)
   #p = StepTwo(imageIn)
   p = Page(imageIn)
   p.segment()
   return show_lines(p)

Exemplo n.º 3

Arquivo: wholisticdiacritics.py Projeto: ryanfb/rigaudon

 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)

Exemplo n.º 4

Arquivo: wholisticdiacritics.py Projeto: brobertson/rigaudon

 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)

Exemplo n.º 5

Arquivo: ocr4gamera.py Projeto: Markismus/eMOP

  img = img.rotate(rotation,0)
  if opt.verbosity > 0:
    print "rotated with",rotation,"angle"

if(opt.auto_group):
  cknn = knn.kNNInteractive([], ["aspect_ratio", "volume64regions", "moments", "nholes_extended"], 0)
  cknn.from_xml_filename(opt.trainfile)
  if(opt.ccsfilter):
    the_ccs = ccs
  else:
    the_ccs = img.cc_analysis()
  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])
  p = Page(img, classify_ccs=autogroup)
  if opt.verbosity > 0:
    print "autogrouping glyphs activated."
    print "maximal autogroup distance:", autogroup.grouping_distance
else:
  p = Page(img)

if opt.verbosity > 0:
  print "start page segmentation..."
  t = time.time()

p.segment()

if opt.verbosity > 0:
  t = time.time() - t
  print "\t segmentation done [",t,"sec]"

Exemplo n.º 6

        print "rotated with", rotation, "angle"

if (opt.auto_group):
    cknn = knn.kNNInteractive(
        [], ["aspect_ratio", "volume64regions", "moments", "nholes_extended"],
        0)
    cknn.from_xml_filename(opt.trainfile)
    if (opt.ccsfilter):
        the_ccs = ccs
    else:
        the_ccs = img.cc_analysis()
    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])
    p = Page(img, classify_ccs=autogroup)
    if opt.verbosity > 0:
        print "autogrouping glyphs activated."
        print "maximal autogroup distance:", autogroup.grouping_distance
else:
    p = Page(img)

if opt.verbosity > 0:
    print "start page segmentation..."
    t = time.time()

p.segment()

if opt.verbosity > 0:
    t = time.time() - t
    print "\t segmentation done [", t, "sec]"