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)
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)
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]"
if opt.verbosity > 1:
rgbfilename = "debug_lines.png"
rgb = p.show_lines()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
rgbfilename = "debug_chars.png"
rgb = p.show_glyphs()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
rgbfilename = "debug_words.png"
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]"
if opt.verbosity > 1:
rgbfilename = "debug_lines.png"
rgb = p.show_lines()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
rgbfilename = "debug_chars.png"
rgb = p.show_glyphs()
rgb.save_PNG(rgbfilename)
print "file '%s' written" % rgbfilename
rgbfilename = "debug_words.png"
