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_runways(image, brightness_threshold=23, beed_filter_radius=3):
seuil = pink.seuil(image, brightness_threshold)
inv = pink.inverse(seuil)
asf = pink.asfbin(inv, beed_filter_radius)
skeleton = pink.skeleton(asf, 0, 8)
ptcurve = pink.ptcurve(skeleton, 8)
dilated = pink.geodilat(ptcurve, asf, 8)
skelcurv = pink.skelcurv(dilated, 0, 8)
return skelcurv
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 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 extract_cells(image, threshold=24):
# creating the structuring element
elem = pink.char_image([3, 3])
elem.fill(1)
elem.center = [1, 1]
grad = pink.gradmorph(muscle, elem)
seuil = pink.seuil(grad, threshold)
frame = pink.frame(pink.char_image(image.size), 255)
dilated = pink.geodilat(frame, seuil, 8)
skeleton = pink.skeleton(dilated, 0, 8)
inv = pink.inverse(skeleton)
eroded = pink.erosball(inv, 5)
inv = pink.inverse(eroded)
skeleton2 = pink.skeleton(inv, image, 4)
return skeleton2
def remove_touching(image):
frame = pink.frame(image, 0)
seeds = image - frame
#seeds.writeimage("seeds.pgm")
result = image - pink.geodilat(seeds, image, 8, -1)
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
from pink import Imview
from pink import cpp as pink
#ex 3.1-1
#help(pink.geoeros)
#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 find_perforated(image):
noholes = fill_the_holes(image)
holes = noholes - image
objects = pink.geodilat(holes, noholes, 8)
result = pink.min(image, objects)
return result
def fill_the_holes(image):
frame = pink.frame(pink.char_image(image.size), 255)
inv = pink.inverse(image)
dilated = pink.geodilat(frame, inv, 8)
result = pink.inverse(dilated)
return result
def remove_objects(image):
frame = pink.frame(pink.char_image(image.size), 255)
border_objects = pink.geodilat(frame, image, 8)
result = image - border_objects
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
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
nb_grains = 0
grain_size = 0
for J in range(CS):
for I in range(RS):
filename = 'tile%02d.pgm' % (J * CS + I)
tile = pink.readimage(filename)
# separate objects into interior and border objects
frame = pink.frame(pink.char_image(tile.size), 255)
border_objects = pink.geodilat(frame, tile, 8)
interior_objects = tile - border_objects
# measure interior objects
grain_size = grain_size + pink.area(interior_objects)
lab = pink.labelfgd(interior_objects, 8)
nb_grains = nb_grains + pink.minmax(lab)[1]
if DEBUG:
print("I,J,s,n: " + str(I) + " " + str(J) + " " + str(grain_size) +
" " + str(nb_grains))
# deal with border objects
if (I < RS - 1) and (J < CS - 1):
filename_r = 'tile%02d.pgm' % (J * CS + I + 1)
tile_r = pink.readimage(filename_r)
filename_d = 'tile%02d.pgm' % ((J + 1) * CS + I)
tile_d = pink.readimage(filename_d)
filename_rd = 'tile%02d.pgm' % ((J + 1) * CS + I + 1)
# Michel's TP-2
from pink import imview
from pink import cpp as pink
debug = True
#sol_outils1
# extraction of thick simple objects
outils = pink.readimage("../images/outils.pgm")
skeleton = pink.skeleton(outils, 0, 8)
#pink.surimp(outils, skeleton, "skeletonized.ppm")
isolated_points = pink.ptisolated(skeleton, 8)
#pink.surimp(skeleton, isolated_points, "ptisolated.ppm")
simple_objects = pink.geodilat(isolated_points, outils, 8)
#pink.surimp(outils, dilated, "dilated.ppm")
eroded = pink.erosball(simple_objects, 10)
thick = pink.geodilat(eroded, outils, 8)
pink.surimp(outils, thick, "thick.ppm")
# sol_outils2
# extraction of thin simple objects
thin = simple_objects - thick
pink.surimp(outils, thin, "thin.ppm")
# sol_outils3
# extraction of object with more than one holes
junctions = pink.ptjunction(skeleton, 8)
holes = pink.geodilat(junctions, outils, 8)
if debug:
def try_geodilat8(n):
return pink.geodilat(IMAGE2, IMAGE, 8, n)
def try_geodilat4(n):
return pink.geodilat(IMAGE2, IMAGE, 4, n)
