def render( image1=0, image2=0 ):
## to be removed later
if (image1==0):
image1 = readimage("/Users/talbot/research/Olivia/images/seg_art_008.pgm")
mesh1 = mcube(image1, 0, 0, 0)
if image2!=0:
mesh2 = mcube(image2, 0, 0, 0)
else:
mesh2 = 0
top = tk.Toplevel(pink.windowing.root)
render_obj=render_class(mesh1, mesh2)
application = app(render_obj, pink.windowing.root)
top.withdraw()
application.mainloop()
application.top.withdraw()
# Michel Couprie, 2011
# CeCILL free-software license
# illustration of filtered Euclidean skeletons
from pink import imview
from pink import manipulate as manipulate
from pink import cpp as pink
global IMAGE
IMAGE = pink.readimage("../images/fish1.pgm")
global LANG
LANG = "en"
def message(mes_en, mes_fr):
if LANG == "fr":
print mes_fr
else:
print mes_en
message("\n\nDemonstration of skeletonization operators",
"\n\nDemonstration des operateurs de squelettisation")
message("Check the 'Superimpose' button in the window",
"Activer l'option 'Superimpose' dans l'interface")
message("Click 'Exit' to close the window and continue",
"Cliquer sur 'Exit' pour passer au suivant")
print(" ----------------")
# ### 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 seg_gray(image, thr1, thr2):
t1 = pink.seuil(image, thr1)
t2 = pink.seuil(image, thr2)
res = pink.asf(t1 - t2, 2)
return (res)
# combine three binary images into one label image
def combine(im1, im2, im3):
i1 = pink.normalize(im1, 0, 1)
i2 = pink.normalize(im2, 0, 2)
i3 = pink.normalize(im3, 0, 3)
return (i1 + i2 + i3)
img = pink.readimage("../images/mortier_3d.pgm")
show_histo(img)
imgf = filtering(img, 2)
white = seg_white(imgf, 197, 80, 80)
if debug:
view3d(img, white)
white.writeamira("_white")
black = seg_black(imgf, 128)
if debug:
view3d(img, black)
black.writeamira("_black")
# UjoImro, 2010
# CeCILL free-software license
# Hugues' TP-2 / Segmentation1
from pink import cpp as pink
# ex 4.1
numbers = pink.readimage("../images/numbers.pgm")
ball = pink.genball(5)
openn = pink.opening(numbers, ball)
normalized = pink.seuil(numbers - openn, 10, 0, 255)
normalized.writeimage("normalized.pgm")
# ex 5.1-1
cell = pink.readimage("../images/cell.pgm")
ball = pink.genball(1)
dcell = pink.dilation(cell, ball)
ecell = pink.erosion(cell, ball)
pink.normalize(dcell - ecell).writeimage("grad.pgm")
# ex 5.1-2
## HELP ME!!!
#ex 6.1-1
bloodcells = pink.readimage("../images/bloodcells.pgm")
marker = pink.char_image(bloodcells.size)
marker[[50, 50]] = 255
marker.writeimage("marker.pgm")
ws = pink.watershed(bloodcells, marker, 8)
from pink import cpp as pink
debug = True
# exo1_1
# filter the image from noise
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
cell = pink.readimage("../images/cell.pgm")
filtered = filter(cell, 2, 2)
print("imview listview test")
imview([cell, filtered])
if debug: imview(filtered)
#filtered.writeimage("cell_filtered.pgm")
# exo1_2
# eliminate the objects touching the border
def remove_objects(image):
frame = pink.frame(pink.char_image(image.size), 255)
border_objects = pink.geodilat(frame, image, 8)
def carbide_detection(image, rad_bth, seuil, rad_op):
es = disk_structuring_element(rad_bth)
if DEBUG:
imview(es)
raw_input("press enter to continue...")
es.writeimage("_es")
bth = black_top_hat(image, es)
if DEBUG:
imview(bth)
raw_input("press enter to continue...")
bth.writeimage("_bth")
thr = pink.seuil(bth, seuil)
if DEBUG:
imview(thr)
raw_input("press enter to continue...")
thr.writeimage("_thr")
opb = pink.openball(thr, rad_op)
if DEBUG:
imview(opb)
raw_input("press enter to continue...")
opb.writeimage("_opb")
res = pink.attribute(opb, 8, 0, 0, 0)
return res
img = pink.readimage("../images/carbures.pgm")
res = carbide_detection(img, 9, 40, 2)
imview(res)
# LuM end of file
from pink import manipulate as manipulate
from pink import cpp as pink
global LANG
LANG = "en"
def message(mes_en, mes_fr):
if LANG == "fr":
print mes_fr
else:
print mes_en
global IMAGE
IMAGE = pink.readimage("../images/blobs.pgm")
message("\n\nDemonstration of basic morphological operators",
"\n\nDemonstration des operateurs morphologiques de base")
message("Check the 'Superimpose' button in the window",
"Activer l'option 'Superimpose' dans l'interface")
message("Click 'Exit' to close the window and continue",
"Cliquer sur 'Exit' pour passer au suivant")
print(" ----------------")
message("Demonstration of erosions", "demonstration de l'erosion")
message(" - structuring element (se) = 4-distance ball",
" - es = boule de la 4-distance")
if debug:
joint.writeimage("_joint")
jointlen = pink.area(joint)
print("longueur totale des joints : " + str(jointlen))
# extracts coroded parts of joints
corojoint = pink.min(pink.dilation(thinpores, pink.genball(1)), joint)
if debug:
corojoint.writeimage("_corojoint")
pink.surimp(joint, corojoint, "_res")
corojointlen = pink.area(corojoint)
print("longueur des joints corrodes : " + str(corojointlen))
return (corojoint)
joints = pink.readimage("../images/joints.pgm")
def segj(q):
return segment(joints, q)
if debug:
height = manipulate(segj, 0, 15, joints)
else:
height = 7
seg = segment(joints, height)
imview(seg)
# Michel's TP-3 for 3D images
from pink import view3d, render, seuilmesh
from pink import cpp as pink
import pink.windowing as wd
inv = pink.inverse
# ## uncomment to ask before quitting dialogs
# wd.options.silent=False
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)
# UjoImro, 2010
# CeCILL free-software license
# 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
# bias correction
def correctbias(img, alpha):
smooth = pink.gaussianfilter(img, alpha / 200.)
mm = pink.minmax(smooth)
s = smooth - mm[0]
res1 = img - s
minmax = pink.minmax(img)
res = pink.normalize(res1, minmax[0], minmax[1])
return pink.float2byte(res)
global image
#image = pink.readimage("../images/uo.pgm")
image = pink.convert2float(pink.readimage("images/pex1.pgm"))
# try gaussian filtering (acts on global 'image' - for use by 'manipulate')
def gaussian(alpha_int):
alpha = alpha_int / 200.0
res = pink.gaussianfilter(image, alpha)
return res
def ss(q):
return pink.seuil(image, q)
if debug:
manipulate(ss, 0, 255)
# Michel Couprie, 2011
# CeCILL free-software license
# crop image (test)
from pink import cpp as pink
from pink import imview as imview
def crop(image, x, y, w, h):
res = pink.char_image([w, h])
res = pink.insert_image(res, image, [-x, -y])
return res
rs = 100 # row size for a tile
cs = 100 # column size for a tile
big = pink.readimage("wholeimage.pgm")
t0 = crop(big, 0, 0, rs, cs)
t1 = crop(big, rs, 0, rs, cs)
t2 = crop(big, 0, cs, rs, cs)
t3 = crop(big, rs, cs, rs, cs)
imview([big, t0, t1, t2, t3])
# UjoImro,HT, 2010-212
# CeCILL free-software license
# Hugues' TP-1
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")
res = pink.insert_image(res, image, [-x, -y])
return (res)
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)
# 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
global DEBUG
DEBUG=1
# bias correction
def correctbias(img, alpha):
smooth = pink.gaussianfilter(img, alpha/200.)
mm = pink.minmax(smooth)
s = smooth - mm[0]
res1 = img - s
minmax = pink.minmax(img)
res = pink.normalize(res1, minmax[0], minmax[1])
return res
global image
#image = pink.readimage("../images/uo.pgm")
image = pink.readimage("../images/pex2.pgm")
# try gaussian filtering (acts on global 'image' - for use by 'manipulate')
def gaussian(alpha_int):
alpha = alpha_int / 200.0
res = pink.gaussianfilter(image, alpha)
return res
def ss(q): return pink.seuil(image, q)
if debug:
manipulate(ss, 0, 255)
#a_int = manipulate(gaussian, 1, 200) # let the user choose parameter value
def cb(q): return correctbias(image, q)
