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
# 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 view(self):
pink.imview(self.get_pink())
def show_histo(img):
print("ici01")
h = pink_histogram(img)
print("ici02")
x = np.array(range(256))
y = np.zeros(256)
fig = plt.figure()
ax1 = fig.add_subplot(111) # 1 row, 1 column, first (upper) plot
ax1.vlines(x, y, h, lw=2)
ax1.grid(True)
ax1.axhline(0, color='black', lw=1)
plt.show()
return
im = pink.readimage("../images/uo.pgm")
imview(im)
ar = image_2_array(im)
im2 = array_2_image(ar)
imview(im2)
if im == im2:
print("Test succeded; the two files are equal")
show_histo(im)
# LuM end of file
# 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)
result = image - border_objects
return result
# convert image to graph structure
# use of external operators acting on files
from pink import imview as imview
from pink import cpp as pink
import os
global DEBUG
DEBUG = 1
def run(cmd):
res = os.system(cmd)
if res != 0:
print "error while executing: " + cmd
global im
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
s = pink.skeleton(imf, 0, 8) # get rid of simple points
imview(s)
s.writeimage("_s")
run("pink.pgm2skel _s 8 _s.skel") # conversion into "skelcurv" format
run("pink.skel2graph _s.skel 1 _s.graph") # conversion into "graph" format
run("pink.graph2ps _s.graph 0.3 _s.ps") # postcript file generation
run("pink.gv _s.ps") # show ps file
# LuM end of file
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
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)
def analj(q):
return analyzejoints(joints, segment(joints, q))
if debug:
d = manipulate(analj, 0, 100, joints)
else:
analyzejoints(joints, seg)
pink.surimp(joints, analj(d), "joints_seg.ppm")
# LuM end of file
#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:
imview([outils, holes])
pink.surimp(outils, holes, "holes.ppm")
# sol_outils4
# objects with one hole
single_hole = outils - (thick + thin + holes)
if debug:
imview([outils, single_hole])
pink.surimp(outils, single_hole, "single_hole.ppm")
# sol_airport
# runway extraction
def extract_runways(image, brightness_threshold=23, beed_filter_radius=3):
seuil = pink.seuil(image, brightness_threshold)
inv = pink.inverse(seuil)
rs = result.size[0]
cs = result.size[1]
for y in range(cs):
for x in range(rs):
R = pow((xc-x)*(xc-x) + (yc-y)*(yc-y), 0.5)
T = (1.0 * result[[x,y]]) - (alpha * R)
if T > 255:
T = 255
if T < 0:
T = 0
result[[x,y]] = int(round(T))
return(result)
img = pink.readimage("../images/mortier_2d.pgm")
xc = 144 # the center is supposed to be known -
yc = 138 # otherwise we have to analyse the 3D image to "guess" it
alpha = find_bias(img, xc, yc)
res = correct_bias(img, xc, yc, alpha)
def sm(q): return pink.seuil(img,q)
def rm(q): return pink.seuil(res,q)
if debug:
imview([img, res])
manipulate(sm, 0, 255)
manipulate(rm, 0, 255)
imview(res)
# LuM end of file
# 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])
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)
for j in range(cs):
for i in range(rs):
