def charseg(self, line):
"""Segment a text line into potential character parts."""
assert mean(line) > 0.5 * amax(line)
line0 = amax(line) - line
ccuts = contourcuts(line0,
maxdist=self.maxdist,
minrange=self.minrange,
mincdist=self.mincdist,
sigma=self.sigma,
r=self.rr,
s=self.s)
line = maximum(0, line0 - ccuts)
# line = line+self.ledge*maximum(0,roll(line,-1,1)-line)
tracks = dplineseg2(line,
imweight=self.imweight,
bweight=self.bweight,
diagweight=self.diagweight,
debug=self.debug,
r=self.r)
tracks = array(tracks < 0.5 * amax(tracks), 'i')
tracks, _ = morph.label(tracks)
self.tracks = tracks
stracks = morph.spread_labels(tracks)
rsegs = stracks * (line0 > 0.5 * amax(line0))
if self.debug:
figure("temp")
subplot(311)
morph.showlabels(tracks)
subplot(312)
morph.showlabels(stracks)
subplot(313)
morph.showlabels(rsegs)
raw_input()
return morph.renumber_by_xcenter(rsegs)
def charseg(self, line):
"""Segment a text line into potential character parts."""
assert mean(line) > 0.5 * amax(line)
line = amax(line) - line
# line = line+self.ledge*maximum(0,roll(line,-1,1)-line)
tracks = dplineseg2(line,
imweight=self.imweight,
bweight=self.bweight,
diagweight=self.diagweight,
debug=self.debug,
r=self.r,
threshold=self.threshold)
tracks = array(tracks < 0.5 * amax(tracks), 'i')
tracks, _ = morph.label(tracks)
self.tracks = tracks # for debuggin
stracks = morph.spread_labels(tracks)
rsegs = stracks * (line > 0.5 * amax(line))
if 0:
figure("temp")
subplot(311)
morph.showlabels(tracks)
subplot(312)
morph.showlabels(stracks)
subplot(313)
morph.showlabels(rsegs)
raw_input()
return morph.renumber_by_xcenter(rsegs)
def remove_noise(line,minsize=8):
"""Remove small pixels from an image."""
if minsize==0: return line
bin = (line>0.5*amax(line))
labels,n = morph.label(bin)
sums = measurements.sum(bin,labels,range(n+1))
sums = sums[labels]
good = minimum(bin,1-(sums>0)*(sums<minsize))
return good
def non_noise_components(seg,threshold=0.1):
"""Estimate the number of non-noise connected components in a character
image. This computes the size of all connected components, and it considers
all components of size less then `threshold` times the size of the largest
component to be noise."""
seg = 1*(seg>0)
labels,n = morph.label(seg)
totals = measurements.sum(seg,labels,range(1,n+1))
return sum(totals>amax(totals)*threshold)
def ccslineseg(image,debug=0):
image = 1.0*(image>0.3*amax(image))
sigma = 10.0
smooth = filters.gaussian_filter(image,(sigma,1.0*sigma),mode='constant')
center = (smooth==amax(smooth,axis=0)[newaxis,:])
center = filters.maximum_filter(center,(3,3))
center = morph.keep_marked(image>0.5,center)
center = filters.maximum_filter(center,(2,2))
center,_ = morph.label(center)
center = morph.spread_labels(center)
center *= image
return center
def ccslineseg(image,debug=0):
image = 1.0*(image>0.3*amax(image))
sigma = 10.0
smooth = filters.gaussian_filter(image,(sigma,1.0*sigma),mode='constant')
center = (smooth==amax(smooth,axis=0)[newaxis,:])
center = filters.maximum_filter(center,(3,3))
center = morph.keep_marked(image>0.5,center)
center = filters.maximum_filter(center,(2,2))
center,_ = morph.label(center)
center = morph.spread_labels(center)
center *= image
return center
def remove_noise(line, minsize=8):
"""Remove small pixels from an image."""
if minsize == 0:
return line
bin = (line > 0.5 * amax(line))
labels, n = morph.label(bin)
print("remove_noise: n=%d labels=%s" % (n, desc(labels)))
sums = measurements.sum(bin, labels, range(n + 1))
sums = sums[labels]
print("sums=%s" % desc(sums))
good = minimum(bin, 1 - (sums > 0) * (sums < minsize))
print("good=%s" % desc(good))
# assert False
return good
def charseg(self,line):
"""Segment a text line into potential character parts."""
assert mean(line)>0.5*amax(line)
line = amax(line)-line
# line = line+self.ledge*maximum(0,roll(line,-1,1)-line)
tracks = dplineseg2(line,imweight=self.imweight,bweight=self.bweight,
diagweight=self.diagweight,debug=self.debug,r=self.r,
threshold=self.threshold)
tracks = array(tracks<0.5*amax(tracks),'i')
tracks,_ = morph.label(tracks)
self.tracks = tracks # for debuggin
stracks = morph.spread_labels(tracks)
rsegs = stracks*(line>0.5*amax(line))
if 0:
figure("temp")
subplot(311); morph.showlabels(tracks)
subplot(312); morph.showlabels(stracks)
subplot(313); morph.showlabels(rsegs)
raw_input()
return morph.renumber_by_xcenter(rsegs)
def charseg(self,line):
"""Segment a text line into potential character parts."""
assert mean(line)>0.5*amax(line)
line0 = amax(line)-line
ccuts = contourcuts(line0,maxdist=self.maxdist,minrange=self.minrange,
mincdist=self.mincdist,sigma=self.sigma,r=self.rr,s=self.s)
line = maximum(0,line0-ccuts)
# line = line+self.ledge*maximum(0,roll(line,-1,1)-line)
tracks = dplineseg2(line,imweight=self.imweight,bweight=self.bweight,
diagweight=self.diagweight,debug=self.debug,r=self.r)
tracks = array(tracks<0.5*amax(tracks),'i')
tracks,_ = morph.label(tracks)
self.tracks = tracks
stracks = morph.spread_labels(tracks)
rsegs = stracks*(line0>0.5*amax(line0))
if self.debug:
figure("temp")
subplot(311); morph.showlabels(tracks)
subplot(312); morph.showlabels(stracks)
subplot(313); morph.showlabels(rsegs)
raw_input()
return morph.renumber_by_xcenter(rsegs)
def number_of_holes(seg):
holes = morphology.binary_fill_holes(seg)-seg
_,n = morph.label(holes)
return n
def binary_objects(binary):
labels, n = morph.label(binary)
objects = morph.find_objects(labels)
return objects
def binary_objects(binary):
labels,n = morph.label(binary)
objects = morph.find_objects(labels)
return objects