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
# UjoImro, 2012
# ProCarPlan s.r.o.
# CeCILL free-software license
# convert image to graph structure
from pink import imview as imview
from pink import cpp as pink
global DEBUG
DEBUG = 1
im = pink.readimage("../images/uo_w.pgm")
imf = pink.frame(im, 255) # adds a white frame inside the image
imf = pink.frame_around(imf, 0) # adds a black frame outside the image
skelim = pink.skeleton(imf, 0, 8) # get rid of simple points
imview(skelim)
skel = pink.image2skel(skelim, 8)
skel.writeskel("_skelpy.skel")
graph = pink.skel2graph(skel, 1)
graph.writegraph("_graphpy.graph")
graph.writeps("_graphpy.ps", 0.3)
# LuM end of file
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 fill_the_hole(image, tbmin=1, tbmax=1):
frame = pink.frame(pink.char_image(image.size), 255)
dist = pink.dist(image, 0)
return pink.toposhrink(inv(frame), inv(dist), 26, tbmin, tbmax, 1, 1,
image)
# ### hint: delete the points for which tb==1
# shrunk = fill_the_hole(tores, 0, 10)
# if debug:
# render(shrunk, tores)
# ### the distance is necessary
# chaise = pink.readimage("../images/chaise.pgm")
# shrunk = fill_the_hole(chaise)
# blank = pink.char_image(chaise.size)
# bad_shrunk = pink.toposhrink( inv(pink.frame(blank,255)), pink.int_image(chaise.size), 26, 0, 10, 1, 1, chaise )
# if debug:
# render(shrunk, chaise)
### application vertebrae
vertebre = pink.frame(pink.readimage("../images/vertebre.pgm"), 0)
#shrunk = fill_the_hole(vertebre, 0, 10)
#if debug:
# render(shrunk, vertebre)
# #### REVISION REQUIRED
# ### introduction of the size parameter
# closed1 = pink.holeclosing(vertebre, 26, 0)
# closed2 = pink.holeclosing(vertebre, 26, 10000)
closed3 = pink.holeclosing(vertebre, 26, 6)
#if debug:
render(closed3, vertebre)
# #### end of REVISION REQUIRED
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
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)
skelcurv = pink.skelcurv(lettre_a, 6, 6)
if debug:
render(lettre_a, pink.inverse(skelcurv))
### curvilinear skeleton of the carotide
skelcurv = pink.skelcurv(carotide_seg, 0, 26)
if debug:
render(skelcurv, skelcurv)
# we can see, that there's a cavity and a cycle in the skeleton
closed = pink.closeball(carotide_seg, 1)
skelcurv = pink.skelcurv(closed, 0, 26)
#if debug: # cde package generation
render(skelcurv)
# now we eliminate the border points
skelcurv = skelcurv - pink.frame(pink.char_image(skelcurv.size), 255)
if debug:
render(skelcurv)
skelcurv = pink.skelcurv(skelcurv, 0, 26)
if debug:
render(carotide_seg, skelcurv)
### the image of the brain
cerveau = pink.readimage("../images/cerveau.pgm")
if debug:
view3d(cerveau)
seuil = pink.seuil(cerveau, 95)
test_tp = pink.skeleton(seuil, 0, 6)
if debug:
render(test_tp)
blank = pink.char_image(cerveau.size)