def logglobal(img,
holder,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
NUCRAD=10,
magnitude=2,
SHRINK=0,
REGWSHED=10,
HPASS=2.5,
GLAP=3,
CIRC_THRESH=0.8):
logimg = np.log(img)
highpassImg = highpassfilter(logimg, NUCRAD * HPASS)
sharpLogimg = logimg + magnitude * highpassImg
lapSharpLogimg = gaussian_laplace(sharpLogimg, NUCRAD / GLAP)
lapSharpLogimg = lapSharpLogimg - lapSharpLogimg.min()
lapSharpLogimg = lapSharpLogimg.max() - lapSharpLogimg
img = lapSharpLogimg
global_thresh = skifilter.threshold_otsu(img)
bw = img > global_thresh
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = circularity_thresh(label, CIRC_THRES)
label = skilabel(clear_border(label, buffer_size=2))
return label
def lapgauss_adaptive(img,
holder,
RATIO=3.0,
FILTERINGSIZE=50,
SIGMA=2.5,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
SHRINK=0,
REGWSHED=10,
COPEN=1,
THINERODE=4,
CIRC_THRES=0.8):
bw = extract_foreground_adaptive(img, RATIO, FILTERINGSIZE)
cimg = calc_lapgauss(img, SIGMA)
bw[cimg > 0] = 0
bw = binary_fill_holes(bw)
bw = skimorph.remove_small_objects(bw, DEBRISAREA, connectivity=4)
bw = binary_opening(bw, np.ones((int(COPEN), int(COPEN))))
bw = remove_thin_objects(bw, THINERODE)
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = circularity_thresh(label, CIRC_THRES)
label = skilabel(clear_border(label, buffer_size=2))
return label
def lapgauss_constant(img,
holder,
SIGMA=2.5,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
SHRINK=0,
REGWSHED=10,
THRES=0.3,
COPEN=1,
THINERODE=4,
CIRC_THRES=0.8):
cimg = calc_lapgauss(img, SIGMA)
bw = cimg > THRES
bw = binary_fill_holes(bw)
bw = skimorph.remove_small_objects(bw, DEBRISAREA, connectivity=4)
bw = binary_opening(bw, np.ones((COPEN, COPEN)))
bw = remove_thin_objects(bw, THINERODE)
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = circularity_thresh(label, CIRC_THRES)
label = skilabel(clear_border(label, buffer_size=2))
return label
def logadaptivegauss(img,
holder,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
magnitude=2,
NUCRAD=10,
FILTERINGSIZE=100,
T=10,
SHRINK=0,
REGWSHED=10,
GLAP=3,
HPASS=2.5):
logimg = np.log(img)
highpassImg = highpassfilter(logimg, NUCRAD * HPASS)
sharpLogimg = logimg + magnitude * highpassImg
lapSharpLogimg = gaussian_laplace(sharpLogimg, NUCRAD / GLAP)
lapSharpLogimg = lapSharpLogimg - lapSharpLogimg.min()
lapSharpLogimg = lapSharpLogimg.max() - lapSharpLogimg
img = lapSharpLogimg
fim = gaussian_filter(img, FILTERINGSIZE)
bw = img > fim * (1. + T / 100.)
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = skilabel(clear_border(label, buffer_size=2))
return label
def adaptivethreshwithglobal_neckcut(img,
holder,
ADAPTIVEBLOCK=21,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
FILTERSIZE=1,
THRESHRELATIVE=1,
SHRINK=0,
REGWSHED=10,
THRES_ANGLE=181,
EDGELEN=5):
img = gaussian_filter(img, FILTERSIZE)
global_thresh = skifilter.threshold_otsu(img)
bw = skifilter.threshold_adaptive(img, ADAPTIVEBLOCK, 'gaussian')
bw = bw * img > global_thresh * THRESHRELATIVE
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
cl_label = clear_border(label)
outlines = labels2outlines(cl_label)
rps = regionprops(outlines)
good_coords = []
for cell in rps:
score, coords = calc_neck_score_thres(cell.coords,
edgelen=EDGELEN,
thres=THRES_ANGLE)
if len(score) > 1:
r0, c0 = coords[0, :]
# Find candidates
for cand in coords[1:, :]:
cut_label = cut_neck(cl_label == cell.label, r0, c0, cand[0],
cand[1])
cand_label = skilabel(cut_label)
cand_rps = regionprops(cand_label)
cand_rps = [i for i in cand_rps if i.area > DEBRISAREA]
if len(cand_rps) > 1:
good_coords.append([r0, c0, cand[0], cand[1]])
break
# Reflect cut in the label
for gc in good_coords:
cut_neck(label, *gc)
return label
def global_otsu(img,
holder,
FILTERSIZE=1,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
SHRINK=0,
REGWSHED=10):
img = gaussian_filter(img, FILTERSIZE)
global_thresh = skifilter.threshold_otsu(img)
bw = img > global_thresh
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = skilabel(clear_border(label, buffer_size=2))
return label
def adaptivethresh2blocks(img,
holder,
ADAPTIVEBLOCK=21,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
FILTERSIZE=1,
SHRINK=0,
REGWSHED=10):
img = gaussian_filter(img, FILTERSIZE)
bw = skifilter.threshold_adaptive(img, ADAPTIVEBLOCK, 'gaussian')
bw2 = skifilter.threshold_adaptive(img, img.shape[0] / 4, 'gaussian')
bw = bw * bw2
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = skilabel(clear_border(label, buffer_size=2))
return label
def adaptivethreshwithglobal(img,
holder,
ADAPTIVEBLOCK=21,
DEBRISAREA=50,
MAXSIZE=1000,
OPENING=2,
FILTERSIZE=1,
THRESHRELATIVE=1,
SHRINK=0,
REGWSHED=10):
img = gaussian_filter(img, FILTERSIZE)
global_thresh = skifilter.threshold_otsu(img)
bw = skifilter.threshold_adaptive(img, ADAPTIVEBLOCK, 'gaussian')
bw = bw * img > global_thresh * THRESHRELATIVE
bw = sizefilterandopen(bw, DEBRISAREA, MAXSIZE, OPENING)
if SHRINK > 0:
bw = binary_erosion(bw, np.ones((SHRINK, SHRINK)))
label = devide_and_label_objects(bw, REGWSHED)
label = sizefilter_for_label(label, DEBRISAREA, MAXSIZE, OPENING)
label = skilabel(clear_border(label, buffer_size=2))
return label
