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Forward-merge branch-25.04 into branch-25.06 #857

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Mar 26, 2025
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Forward-merge branch-25.04 into branch-25.06 #857

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20 changes: 12 additions & 8 deletions python/cucim/src/cucim/skimage/segmentation/_chan_vese.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def _fused_variance_kernel2(
return out


def _cv_calculate_variation(image, phi, mu, lambda1, lambda2, dt):
def _cv_calculate_variation(image, phi, mu, lambda1, lambda2, dt, eta):
"""Returns the variation of level set 'phi' based on algorithm parameters.

This corresponds to equation (22) of the paper by Pascal Getreuer,
Expand All @@ -89,7 +89,6 @@ def _cv_calculate_variation(image, phi, mu, lambda1, lambda2, dt):
similar approach is used by Rami Cohen, and it is from there that the
C1-4 notation is taken.
"""
eta = 1e-16
P = pad(phi, 1, mode="edge")

x_end = P[1:-1, 2:]
Expand Down Expand Up @@ -413,6 +412,15 @@ def chan_vese(
raise ValueError("Input image should be a 2D array.")

float_dtype = _supported_float_type(image.dtype)

# cast Python float constants to device scalars of matching precision
mu = cp.asarray(mu, dtype=float_dtype)
lambda1 = cp.asarray(lambda1, dtype=float_dtype)
lambda2 = cp.asarray(lambda2, dtype=float_dtype)
dt = cp.asarray(dt, dtype=float_dtype)
tol = cp.asarray(tol, dtype=float_dtype)
eta = cp.asarray(1e-16, dtype=float_dtype)

phi = _cv_init_level_set(init_level_set, image.shape, dtype=float_dtype)
if type(phi) != cp.ndarray or phi.shape != image.shape:
raise ValueError(
Expand All @@ -429,18 +437,14 @@ def chan_vese(
if extended_output:
old_energy = _cv_energy(image, phi, mu, lambda1, lambda2)
energies = []
phivar = tol + 1

dt = cp.asarray(dt, dtype=float_dtype)
mu = cp.asarray(mu, dtype=float_dtype)
lambda1 = cp.asarray(lambda1, dtype=float_dtype)
lambda2 = cp.asarray(lambda2, dtype=float_dtype)
phivar = tol + 1
while phivar > tol and i < max_num_iter:
# Save old level set values
oldphi = phi

# Calculate new level set
phi = _cv_calculate_variation(image, phi, mu, lambda1, lambda2, dt)
phi = _cv_calculate_variation(image, phi, mu, lambda1, lambda2, dt, eta)
phivar = phi - oldphi
phivar *= phivar
phivar = cp.sqrt(phivar.mean())
Expand Down
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