def __call__(
self,
image,
window_size=10,
threshold=0,
fill_holes=True,
remove_borderobjects=True,
outline_smoothing=0,
use_watershed=False,
seeding_size=8,
*args,
**kw
):
"""Local adaptive threshold segmentation using a gaussian Kernel"""
thresh = adaptive_threshold(image, window_size, threshold)
if fill_holes:
thresh = ndi.morphology.binary_fill_holes(thresh)
# object don't touch border after outline smoothing
if remove_borderobjects:
thresh = clear_border(thresh)
if outline_smoothing >= 1:
thresh = outlineSmoothing(thresh, outline_smoothing)
if use_watershed:
label_image = watershed(thresh, seeding_size=seeding_size)
else:
label_image = ndi.label(thresh)[0]
return label_image
def threshold(self, image, median_radius, window_size, min_contrast,
remove_borderobjects, fill_holes, norm_min=0, norm_max=255,
use_watershed=True, seeding_size=5, outline_smoothing=1,
*args, **kw):
image = self.normalize(image, norm_min, norm_max)
image = ccore.numpy_to_image(image, copy=True)
image_smoothed = ccore.gaussianFilter(image, median_radius)
label_image = ccore.window_average_threshold(
image_smoothed, window_size, min_contrast)
if fill_holes:
ccore.fill_holes(label_image)
if outline_smoothing >= 1:
label_image = outlineSmoothing(label_image.toArray(),
outline_smoothing)
label_image = ccore.numpy_to_image(label_image, copy=True)
if use_watershed:
label_image = label_image.toArray().copy()
label_image = watershed(label_image, seeding_size=seeding_size)
label_image = ccore.numpy_to_image(
label_image.astype(np.int16), copy=True)
return ccore.ImageMaskContainer(image, label_image,
remove_borderobjects, True, True)
else:
# a static type system sucks!
return ccore.ImageMaskContainer(image, label_image,
remove_borderobjects)
def threshold(self,
image,
median_radius,
window_size,
min_contrast,
remove_borderobjects,
fill_holes,
norm_min=0,
norm_max=255,
use_watershed=True,
seeding_size=5,
outline_smoothing=1,
*args,
**kw):
image = self.normalize(image, norm_min, norm_max)
image = ccore.numpy_to_image(image, copy=True)
image_smoothed = ccore.gaussianFilter(image, median_radius)
label_image = ccore.window_average_threshold(image_smoothed,
window_size, min_contrast)
if fill_holes:
ccore.fill_holes(label_image)
if outline_smoothing >= 1:
label_image = outlineSmoothing(label_image.toArray(),
outline_smoothing)
label_image = ccore.numpy_to_image(label_image, copy=True)
if use_watershed:
label_image = label_image.toArray().copy()
label_image = watershed(label_image, seeding_size=seeding_size)
label_image = ccore.numpy_to_image(label_image.astype(np.int16),
copy=True)
return ccore.ImageMaskContainer(image, label_image,
remove_borderobjects, True, True)
else:
# a static type system sucks!
return ccore.ImageMaskContainer(image, label_image,
remove_borderobjects)
