def iabshow(f1, f2=None, f3=None, factor=17):
from ia870 import iabinary, iaframe, iadil, iaunion
from ia870 import iasedisk, iaserot, iasecross, iasesum
assert f1.dtype == bool, 'f1 must be boolean image'
factor = max(factor, 9)
hfactor = factor // 2
if size(f1.shape) == 1:
f1 = f1[newaxis, :]
if f2 != None: f2 = f2[newaxis, :]
if f3 != None: f3 = f3[newaxis, :]
bz = zeros(factor * array(f1.shape)).astype(bool)
b0 = asarray(bz)
b0[hfactor::factor, hfactor::factor] = f1
fr1 = iaframe(zeros((factor, factor), bool))
fr1 = iadil(b0, fr1)
if f2 is not None:
assert f1.shape == f2.shape, 'f1 and f2 must have same shape'
b1 = asarray(bz)
b1[hfactor::factor, hfactor::factor] = f2
fr2 = iadil(b1, iasedisk(hfactor - 4))
fr1 = iaunion(fr1, fr2)
if f3 is not None:
assert f1.shape == f3.shape, 'f1 and f3 must have same shape'
bz[hfactor::factor, hfactor::factor] = f3
fr3 = iadil(bz, iasesum(iaserot(iasecross(1), 45), hfactor - 1))
fr1 = iaunion(fr1, fr3)
return fr1
def iagshow(X, X1=None, X2=None, X3=None, X4=None, X5=None, X6=None):
from ia870 import iaisbinary, iagray, iaunion
from ia870 import iaintersec, ianeg, iaconcat
if iaisbinary(X): X = iagray(X, 'uint8')
r = X
g = X
b = X
if X1 is not None: # red 1 0 0
assert iaisbinary(X1), 'X1 must be binary overlay'
x1 = iagray(X1, 'uint8')
r = iaunion(r, x1)
g = iaintersec(g, ianeg(x1))
b = iaintersec(b, ianeg(x1))
if X2 is not None: # green 0 1 0
assert iaisbinary(X2), 'X2 must be binary overlay'
x2 = iagray(X2, 'uint8')
r = iaintersec(r, ianeg(x2))
g = iaunion(g, x2)
b = iaintersec(b, ianeg(x2))
if X3 is not None: # blue 0 0 1
assert iaisbinary(X3), 'X3 must be binary overlay'
x3 = iagray(X3, 'uint8')
r = iaintersec(r, ianeg(x3))
g = iaintersec(g, ianeg(x3))
b = iaunion(b, x3)
if X4 is not None: # magenta 1 0 1
assert iaisbinary(X4), 'X4 must be binary overlay'
x4 = iagray(X4, 'uint8')
r = iaunion(r, x4)
g = iaintersec(g, ianeg(x4))
b = iaunion(b, x4)
if X5 is not None: # yellow 1 1 0
assert iaisbinary(X5), 'X5 must be binary overlay'
x5 = iagray(X5, 'uint8')
r = iaunion(r, x5)
g = iaunion(g, x5)
b = iaintersec(b, ianeg(x5))
if X6 is not None: # cyan 0 1 1
assert iaisbinary(X6), 'X6 must be binary overlay'
x6 = iagray(X6, 'uint8')
r = iaintersec(r, ianeg(x6))
g = iaunion(g, x6)
b = iaunion(b, x6)
return np.array([r, g, b])
return Y
def ialabel_rec(f, Bc=iasecross()):
assert MT.iaisbinary(f), 'Can only label binary image'
faux = f.copy()
label = 1
y = MT.iagray(f, 'uint16', 0) # zero image (output)
x = faux.ravel().nonzero() # get list of unlabeled pixel
while len(x[0]):
fmark = np.zeros_like(f)
fmark.flat[x[0][0]] = 1 # get the first unlabeled pixel
r = MT.iainfrec(fmark, faux, Bc) # detects all pixels connected to it
faux -= r # remove them from faux
r = MT.iagray(r, 'uint16', label) # label them with the value label
y = MT.iaunion(y, r) # merge them with the labeled image
label = label + 1
x = faux.ravel().nonzero() # get list of unlabeled pixel
return y
def ialabel_rec(f, Bc=iasecross()):
assert MT.iaisbinary(f),'Can only label binary image'
faux=f.copy()
label = 1
y = MT.iagray( f,'uint16',0) # zero image (output)
x = faux.ravel().nonzero() # get list of unlabeled pixel
while len(x[0]):
fmark = np.zeros_like(f)
fmark.flat[x[0][0]] = 1 # get the first unlabeled pixel
r = MT.iainfrec( fmark, faux, Bc) # detects all pixels connected to it
faux -= r # remove them from faux
r = MT.iagray( r,'uint16',label) # label them with the value label
y = MT.iaunion( y, r) # merge them with the labeled image
label = label + 1
x = faux.ravel().nonzero() # get list of unlabeled pixel
return y
def iaareaopen_eq(f, a, Bc=iasecross()):
if f.dtype == np.bool:
fr = MT.ialabel(f,Bc) # binary area open, use area measurement
g = MT.iablob(fr,'area')
y = g >= a
else:
y = np.zeros_like(f)
k1 = f.min()
k2 = f.max()
for k in xrange(k1,k2+1): # gray-scale, use thresholding decomposition
fk = (f >= k)
fo = MT.iaareaopen(fk,a,Bc)
if not fo.any():
break
y = MT.iaunion(y, MT.iagray(fo,f.dtype,k))
return y
def iaareaopen_eq(f, a, Bc=iasecross()):
if f.dtype == np.bool:
fr = MT.ialabel(f, Bc) # binary area open, use area measurement
g = MT.iablob(fr, "area")
y = g >= a
else:
y = np.zeros_like(f)
k1 = f.min()
k2 = f.max()
for k in xrange(k1, k2 + 1): # gray-scale, use thresholding decomposition
fk = f >= k
fo = MT.iaareaopen(fk, a, Bc)
if not fo.any():
break
y = MT.iaunion(y, MT.iagray(fo, f.dtype, k))
return y
def iathin(f, Iab=None, n=-1, theta=45, DIRECTION="CLOCKWISE"):
import ia870 as MT
if Iab is None: Iab = MT.iahomothin()
DIRECTION = upper(DIRECTION)
assert MT.iaisbinary(f),'f must be binary image'
if n == -1: n = product(f.shape)
y = f
zero = MT.iaintersec(f,0)
for i in range(n):
aux = zero
for t in range(0,360,theta):
sup = MT.iasupgen( y, MT.iainterot(Iab, t, DIRECTION))
aux = MT.iaunion( aux, sup)
#y -= sup
y = MT.iasubm( y, sup)
#if iaisequal(aux,zero): break
if not aux.any(): break
return y
