def test_convex3():
f = np.array([
[False, False, False, False],
[False, True, True, False],
[False, True, False, False],
[False, False, False, False]], dtype=bool)
assert np.all(fill_convexhull(f) == f)
def test_convex3():
f = np.array([
[False, False, False, False],
[False, True, True, False],
[False, True, False, False],
[False, False, False, False]], dtype=bool)
assert np.all(fill_convexhull(f) == f)
def convexHull(bImg):
label,numLabel=ndimage.label(bImg)
bImg[:]=False
for i in range(1,numLabel+1):
bImgN=label==i
bImgN=fill_convexhull(bImgN)
bImg=numpy.logical_or(bImg,bImgN)
return bImg
# contorno, curvatura
C = contorno(filt, i, 0)
Kurv = curvatura(C, 50)
nbr, L, V = maximos(Kurv, 0.02)
# area, perimetro, convex hull
sss = filt.copy()
sss[filt != i] = 0
sss[filt == i] = 1
sss = sss.astype(int)
# por enquanto removendo convex hull, pois está bugado qhull
#convex = convex_hull_image(sss)
convex = mp.fill_convexhull(sss)
print 'convex hull feito'
Aor = np.sum(sss)
Ac = np.sum(convex)
# guarda a quantidade de picos
qtd_picos.append(nbr)
# fig2.clf()
# plot2 = fig2.add_subplot(221)
# plot2.imshow(convex, cmap=plt.cm.gray, interpolation='nearest')
# plot2 = fig2.add_subplot(222)
# plot2.imshow(sss, cmap=plt.cm.gray, interpolation='nearest')
# plot2 = fig2.add_subplot(223)
# fig2.savefig('foo.png')
# perímetro
peri = len(C)
