def disk_structuring_element(radius):
d = radius + radius + 1
res = pink.char_image([d, d])
res.fill(0)
res.center = [radius, radius]
res[[radius, radius]] = 255
res = pink.dilatball(res, radius)
return (res)
def extract_corne(image, threshold):
seuil = pink.seuil(image, threshold, 0, 255)
opened = pink.openball(seuil, 3)
geodilat = pink.geodilat(opened, seuil, 8)
diff = seuil - geodilat
dilated = pink.dilatball(diff, 4)
opened2 = pink.openball(dilated, 10)
geodilat2 = pink.geodilat(opened2, dilated, 8)
closed = pink.closeball(geodilat2, 4)
border = pink.border(closed, 8)
return border
def extract_fractures(image):
seuil = pink.seuil(image, 123)
inv = pink.inverse(seuil)
skeleton1 = pink.skelcurv(inv, 0, 8)
endpoints = pink.ptend(skeleton1, 8)
dilated = pink.dilatball(endpoints, 1, 8)
sub = skeleton1 - dilated
add = endpoints + sub
inv = pink.inverse(add)
skeleton2 = pink.skeleton(inv, 0, 4)
inv = pink.inverse(skeleton2)
dilated = pink.geodilat(endpoints, inv, 4)
return dilated
def find_the_wires(image, seuil):
# binarize
binary = pink.seuil(image, seuil, 0, 255)
inv = pink.inverse(binary)
# eliminate the little objects
#filtered = filter(inv, 2, 8)
eros = pink.erosball(inv, 2)
filtered = pink.geodilat(eros, inv, 8)
# fill the holes
filled = fill_the_holes(filtered)
# detect the joints
eros = pink.erosball(filled, 6)
dilat = pink.dilatball(eros, 6)
joints = pink.geodilat(dilat, filled, 8, 1)
# extract the wires
result = filled - joints
return result
def filter_noise(image):
eroded = pink.erosball(image, 1, 0)
recons1 = pink.geodilat(eroded, image, 8, 10)
dilated = pink.dilatball(recons1, 2, 0)
result = pink.geoeros(dilated, recons1, 8, 10)
return result
#ex 3.1-2
I = pink.readimage("../images/cells.pgm")
viewer1 = Imview(I)
eroded = pink.erosball(I, 1, 0)
viewer1.show(eroded, "eroded") # spacebar to switch from one image to the next
#ex 3.1-3
recons1 = pink.geodilat(eroded, I, 8, 10)
viewer1.show(recons1, "recons1")
#recons1.writeimage("recons1.pgm")
#ex 3.1-4
# we start from the already partially denoised result
dilated = pink.dilatball(recons1, 1, 0)
recons2 = pink.geoeros(dilated, recons1, 8, 10)
# we save this result
#recons2.writeimage("recons2.pgm")
#ex 3.1-5
# a procedure to do everything as a function
def filter_noise(image):
eroded = pink.erosball(image, 1, 0)
recons1 = pink.geodilat(eroded, image, 8, 10)
dilated = pink.dilatball(recons1, 2, 0)
result = pink.geoeros(dilated, recons1, 8, 10)
return result
def filter(image, radius_opening, radius_closing):
eroded = pink.erosball(image, radius_opening)
recons1 = pink.geodilat(eroded, image, 8)
dilated = pink.dilatball(recons1, radius_closing)
result = pink.geoeros(dilated, recons1, 8)
return result
debug = True
# ## uncomment to perform the debug operations
# debug=True
lettre_a = pink.readimage("../images/lettre_a.pgm")
carotide = pink.readimage("../images/carotide.pgm")
if debug:
view3d(lettre_a)
if debug:
view3d(carotide)
#seuilmesh(carotide)
seuil = pink.seuil(carotide, 105)
dilated = pink.dilatball(seuil, 2)
if debug:
view3d(carotide, dilated)
diff = carotide - dilated
seuil = pink.seuil(diff, 94)
if debug:
view3d(carotide, seuil)
component = pink.selectcomp(seuil, 26, 58, 46, 0)
if debug:
view3d(carotide, component)
carotide_seg = component
### the skeleton operator
axonepair = pink.readimage("../images/axonepair.pgm")
#imview(axonepair) ## HUGUES WRITE ME!
cs = image.size[1]
for j in range(margin, cs-margin):
for i in range(margin, rs-margin):
if random.random() <= p:
image[[i,j]] = 255
rad = 4 # radius of particles
RS = 4 # numbers of tiles in a row
CS = 4 # numbers of tiles in a column
rs = 100 # row size for a tile
cs = 100 # column size for a tile
pr = 0.0004 # proportion of particle centers
img = pink.char_image([RS*rs,CS*cs])
randimage2(img, pr, rad+1)
img = pink.dilatball(img, rad)
img.writeimage("wholeimage.pgm")
imview(img)
grain_size = pink.area(img)
lab = pink.labelfgd(img, 8)
nb_grains = pink.minmax(lab)[1]
print("grain_size = " + str(grain_size))
print("nb_grains = " + str(nb_grains))
img = pink.readimage("wholeimage.pgm")
tile = pink.char_image([rs,cs])
for J in range(CS):
for I in range(RS):
filename = 'tile%02d.pgm'%(J*CS+I)
def try_dilation(radius):
return pink.dilatball(IMAGE, radius)