imageStack = imagestack

muDivision = np.linspace(0, 0.5, 15)

lambda1Division = np.linspace(0, 4, 15)

lambda2Division = np.linspace(0, 4, 15)

zStack, width, length = np.shape(imageStack)

maxImage = np.max(imageStack, axis=0)

# maxImage = np.max(np.delete(imageStack, 0, 3), axis=0)

# noColorPlan = rgb2gray(maxImage)

mu_0 = 0.25

delta_mu = 0.05

lambda1_0 = 2

lambda2_0 = 4

tol = 1e-3

max_iter = 1000

dt = 0.5

loopPosition = 0

for plan in imageStack:

global falseMatrixActivation

falseMatrixActivation = 0

fig, ax = plt.subplots()

plt.subplots_adjust(left=0.1, bottom=0.3)

graphTitle = 'Interactive segmentation plan ' + str(loopPosition+1)

plt.title(graphTitle)

try:

with open('cv_Parameter.txt', 'r') as cvParameter:

print('cv_Parameter.txt found, loading previous parameters.')

line = cvParameter.read().splitlines()

mu_0 = float(line[0])

lambda1_0 = float(line[1])

lambda2_0 = float(line[2])

delta_mu = 0.05

tol = 1e-3

max_iter = 1000

dt = 0.5

except FileNotFoundError:

mu_0 = 0.25

lambda1_0 = 2

lambda2_0 = 4

delta_mu = 0.05

tol = 1e-3

max_iter = 1000

dt = 0.5

noColorPlan = rgb2gray(plan)

# print(plan, noColorPlan)

cv = chan_vese(noColorPlan, mu=mu_0, lambda1=lambda1_0, lambda2=lambda2_0, tol=tol, max_iter=max_iter / 10, dt=dt,

init_level_set='checkerboard', extended_output=True)

# if 16 bit image

# maxImage2 = maxImage*16

# maxImage3 = skimage.img_as_ubyte(maxImages2)

# ax.imshow(mark_boundaries(maxImage, cv[0]), vmin=0, vmax=4096)

ax.imshow(mark_boundaries(noColorPlan, cv[0]))

# reinitialise value for slider

# mu_0 = 0.25

# lambda1_0 = 2

# lambda2_0 = 4

colorAxe = 'lightgray'

muAxe = plt.axes([0.25, 0.2, 0.5, 0.03], facecolor='lightcoral')

lambda1Axe = plt.axes([0.25, 0.15, 0.5, 0.03], facecolor='yellowgreen')

lambda2Axe = plt.axes([0.25, 0.1, 0.5, 0.03], facecolor='mediumturquoise')

muSlider = Slider(muAxe, '$\mu$', -0.05, 2., valinit=mu_0)

lambda1Slider = Slider(lambda1Axe, '$\lambda_1$', 0., 10.0, valinit=lambda1_0)

lambda2Slider = Slider(lambda2Axe, '$\lambda_2$', 0., 10.0, valinit=lambda2_0)

def update(val):

mu = muSlider.val

lambda1 = lambda1Slider.val

lambda2 = lambda2Slider.val

cv = chan_vese(noColorPlan, mu=mu, lambda1=lambda1, lambda2=lambda2, tol=tol, max_iter=max_iter / 10, dt=dt,

init_level_set='checkerboard', extended_output=True)

ax.imshow(mark_boundaries(noColorPlan, cv[0]), vmin=0, vmax=4096)

#fig.canvas.draw_idle()

muSlider.on_changed(update)

lambda1Slider.on_changed(update)

lambda2Slider.on_changed(update)

resetAxe = plt.axes([0.65, 0.025, 0.1, 0.04])

button = Button(resetAxe, 'Reset', color=colorAxe, hovercolor='0.6')

def reset(event):

muSlider.reset()

lambda1Slider.reset()

lambda2Slider.reset()

try:

with open('cv_Parameter.txt', 'r'):

pass

os.remove('cv_Parameter.txt')

except FileNotFoundError:

pass

button.on_clicked(reset)

def keep_nothing(event):

global falseMatrixActivation

falseMatrixActivation = 1

# print(f'falseMatrixActivation : {falseMatrixActivation}')

plt.close()

keepNothingAxe = plt.axes([0.25, 0.025, 0.2, 0.04])

keepNothingButton = Button(keepNothingAxe, 'Keep Nothing', color=colorAxe, hovercolor='0.6')

keepNothingButton.on_clicked(keep_nothing)

saveAxe = plt.axes([0.5, 0.025, 0.1, 0.04])

saveButton = Button(saveAxe, 'Save', color=colorAxe, hovercolor='0.6')

def save(event):

with open('cv_Parameter.txt', 'w') as cvParameter:

cvParameter.write(str(muSlider.val) + '\n')

cvParameter.write(str(lambda1Slider.val) + '\n')

cvParameter.write(str(lambda2Slider.val) + '\n')

print('Data saved in cv_Parameter.txt')

plt.close()

saveButton.on_clicked(save)

plt.show()

# Segmentation with best parameters or default

if falseMatrixActivation == 1:

imageStack[loopPosition] = np.zeros(np.shape(plan))

print(f'no segmentation done')

else:

try:

with open('cv_Parameter.txt', 'r') as cvParameter:

print('cv_Parameter.txt found, loading best parameters.')

line = cvParameter.read().splitlines()

mu = float(line[0])

lambda1 = float(line[1])

lambda2 = float(line[2])

except FileNotFoundError:

print('cv_Parameter.txt not found, loading default parameters.')

mu = mu_0

lambda1 = lambda1_0

lambda2 = lambda2_0

cv = chan_vese(noColorPlan, mu=mu, lambda1=lambda1, lambda2=lambda2, tol=tol, max_iter=max_iter, dt=dt,

init_level_set='checkerboard', extended_output=True)

print('Segmentation done with parameter $\mu$ : {0}, $\lambda_1$ : {1}, $\lambda_2$ : {2}, '

'tolerance : {3:1.2e}, ''max iteration : {4:1.2e}, dt : {5}.'.format(mu, lambda1, lambda2, tol,

max_iter, dt))

imageStack[loopPosition] = cv[0] * plan

loopPosition += 1

# Treatment and export

segmentedImageName = 'segmented_Image/' + filename + '_segmentedImage.tif'

with skimage.external.tifffile.TiffWriter(segmentedImageName) as tif:

for image in range(imageStack.shape[0]):

tif.save(imageStack[image], compress=0)

return imageStack