def classify_image(self,imgname,ccs = None):
if hasattr(imgname,'ccs'):
mi = imgname
else:
from sheetmusic import MusicImage
self.l.debug("Loading image from file %s",imgname)
mi = MusicImage(imgname)
if ccs is None:
self.l.debug("Getting relevant ccs.")
relevant_cc = mi.ccs(remove_text=True,remove_inside_staffs=True)
else:
relevant_cc = ccs
ret = Classified_image(self,mi,relevant_cc)
self.images.append(ret)
return ret
def classify_image(self, imgname, ccs=None):
if hasattr(imgname, 'ccs'):
mi = imgname
else:
from sheetmusic import MusicImage
self.l.debug("Loading image from file %s", imgname)
mi = MusicImage(imgname)
if ccs is None:
self.l.debug("Getting relevant ccs.")
relevant_cc = mi.ccs(remove_text=True, remove_inside_staffs=True)
else:
relevant_cc = ccs
ret = Classified_image(self, mi, relevant_cc)
self.images.append(ret)
return ret
if __name__ == '__main__':
from gamera.core import *
import sys
import re
import time
from sheetmusic import MusicImage
from within import inout_vertical_ys
from numpy import average
init_gamera()
for i, imgname in enumerate(sys.argv[1:]):
m = re.match(r"^(.*)\.[^\.]+$", imgname)
noend = m.group(1)
start = time.time()
i = MusicImage(imgname)
print "Load image %f" % (time.time() - start)
start = time.time()
spikes = i.possible_text_areas()
print "Spikes %f" % (time.time() - start)
start = time.time()
ccs = i.without_insidestaves_info().cc_analysis()
print "ccanalysis %f" % (time.time() - start)
sys.stdout.flush()
for s in spikes:
cond = inout_vertical_ys([(s['start'], s['stop'])])
cs = [c for c in ccs if cond(c)]
print "%d ccs in ys: %d-%d" % (len(cs), s['start'], s['stop'])
avgaspect = average([c.aspect_ratio() for c in cs])
print "%f mean aspect" % (avgaspect)
print
from sheetmusic import MusicImage
from within import inout_staff_condition
import os.path
if os.path.isfile("lvbp0.tif"):
mi = MusicImage("lvbp0.tif")
rgb = mi.to_rgb().to_onebit().to_rgb()
# Painting inside staff things green
cond = inout_staff_condition(mi.ms().get_staffpos())
ccs = [ c for c in mi.ccs(False,False) if cond(c)]
for c in ccs:
rgb.highlight(c,RGBPixel(0,255,0))
# Painting relevant ccs' red.
ccs = mi.ccs()
for c in ccs:
rgb.highlight(c,RGBPixel(255,0,0))
# Painting text yellow
ccs = mi.possible_text_ccs()
for c in ccs:
rgb.highlight(c,RGBPixel(255,255,0))
rgb.save_PNG("lvbp0_relevant_ccs.png")
mi = MusicImage("debussyp0.tif")
rgb = mi.to_rgb().to_onebit().to_rgb()
cond = inout_staff_condition(mi.ms().get_staffpos())
ccs = [ c for c in mi.ccs(False,False) if cond(c)]
for c in ccs:
rgb.highlight(c,RGBPixel(0,255,0))
ccs = mi.ccs()
for c in ccs:
rgb.highlight(c,RGBPixel(255,0,0))
from sheetmusic import MusicImage
from within import inout_staff_condition
import os.path
if os.path.isfile("lvbp0.tif"):
mi = MusicImage("lvbp0.tif")
rgb = mi.to_rgb().to_onebit().to_rgb()
# Painting inside staff things green
cond = inout_staff_condition(mi.ms().get_staffpos())
ccs = [c for c in mi.ccs(False, False) if cond(c)]
for c in ccs:
rgb.highlight(c, RGBPixel(0, 255, 0))
# Painting relevant ccs' red.
ccs = mi.ccs()
for c in ccs:
rgb.highlight(c, RGBPixel(255, 0, 0))
# Painting text yellow
ccs = mi.possible_text_ccs()
for c in ccs:
rgb.highlight(c, RGBPixel(255, 255, 0))
rgb.save_PNG("lvbp0_relevant_ccs.png")
mi = MusicImage("debussyp0.tif")
rgb = mi.to_rgb().to_onebit().to_rgb()
cond = inout_staff_condition(mi.ms().get_staffpos())
ccs = [c for c in mi.ccs(False, False) if cond(c)]
for c in ccs:
rgb.highlight(c, RGBPixel(0, 255, 0))
ccs = mi.ccs()
for c in ccs:
rgb.highlight(c, RGBPixel(255, 0, 0))
if __name__ == '__main__':
from gamera.core import *
import sys
import re
import time
from sheetmusic import MusicImage
from within import inout_vertical_ys
from numpy import average
init_gamera()
for i,imgname in enumerate(sys.argv[1:]):
m = re.match(r"^(.*)\.[^\.]+$",imgname)
noend = m.group(1)
start = time.time()
i = MusicImage(imgname)
print "Load image %f"%(time.time()-start)
start = time.time()
spikes = i.possible_text_areas()
print "Spikes %f"%(time.time()-start)
start=time.time()
ccs = i.without_insidestaves_info().cc_analysis()
print "ccanalysis %f"%(time.time()-start)
sys.stdout.flush()
for s in spikes:
cond = inout_vertical_ys([(s['start'],s['stop'])])
cs = [ c for c in ccs if cond(c) ]
print "%d ccs in ys: %d-%d"%(len(cs),s['start'],s['stop'])
avgaspect = average([ c.aspect_ratio() for c in cs ])
print "%f mean aspect"%(avgaspect)
print
import sys
import re
import yaml
sys.path.append("..")
from sheetmusic import MusicImage
if __name__ == '__main__':
FORMAT = "%(asctime)-15s %(levelname)s [%(name)s.%(funcName)s] %(message)s"
logging.basicConfig(level=logging.DEBUG,format=FORMAT,filename="counter.log")
init_gamera()
for imgname in sys.argv[1:]:
m = re.match(r"^(.*)\.[^\.]+$",imgname)
noend = m.group(1)
mi = MusicImage(imgname,training_filename="../preomr_edited_cnn.xml")
c = mi.ccs_overall()
cl = dict([ (k,len(v)) for k,v in c.iteritems() ])
outf = "%s-colorseg.yaml"%noend
with open(outf,"w") as f:
data = {'text':{'found':cl['text'],'count':cl['text']},
'dynamics':{'found':cl['classified'], 'count':cl['classified']
}
}
print "%s"%data
yaml.dump(data,f)
logging.debug("Wrote %s",outf)
import re
import yaml
sys.path.append("..")
from sheetmusic import MusicImage
if __name__ == '__main__':
FORMAT = "%(asctime)-15s %(levelname)s [%(name)s.%(funcName)s] %(message)s"
logging.basicConfig(level=logging.DEBUG,
format=FORMAT,
filename="counter.log")
init_gamera()
for imgname in sys.argv[1:]:
m = re.match(r"^(.*)\.[^\.]+$", imgname)
noend = m.group(1)
mi = MusicImage(imgname, training_filename="../preomr_edited_cnn.xml")
c = mi.ccs_overall()
cl = dict([(k, len(v)) for k, v in c.iteritems()])
outf = "%s-colorseg.yaml" % noend
with open(outf, "w") as f:
data = {
'text': {
'found': cl['text'],
'count': cl['text']
},
'dynamics': {
'found': cl['classified'],
'count': cl['classified']
}
}
print "%s" % data
