def test_li_arbitrary_start_point():
cell = data.cell()
max_stationary_point = threshold_li(cell)
low_stationary_point = threshold_li(cell,
initial_guess=np.percentile(cell, 5))
optimum = threshold_li(cell, initial_guess=np.percentile(cell, 95))
assert 67 < max_stationary_point < 68
assert 48 < low_stationary_point < 49
assert 111 < optimum < 112
from cucim.skimage.filters.thresholding import _cross_entropy # _mean_std,
from cucim.skimage.filters.thresholding import (threshold_isodata, threshold_li,
threshold_local, threshold_mean,
threshold_minimum,
threshold_multiotsu,
threshold_niblack,
threshold_otsu,
threshold_sauvola,
threshold_triangle,
threshold_yen,
try_all_threshold)
# transfer images to GPU
astronautd = cp.array(data.astronaut())
camerad = cp.array(data.camera())
celld = cp.array(data.cell())
coinsd = cp.array(data.coins())
moond = cp.array(data.moon())
class TestSimpleImage:
def setup(self):
# fmt: off
self.image = cp.array([[0, 0, 1, 3, 5],
[0, 1, 4, 3, 4],
[1, 2, 5, 4, 1],
[2, 4, 5, 2, 1],
[4, 5, 1, 0, 0]], dtype=int)
# fmt: on
def test_minimum(self):
def test_cell():
""" Test that "cell" image can be loaded."""
data.cell()
.. [1] Li C.H. and Lee C.K. (1993) "Minimum Cross Entropy Thresholding"
Pattern Recognition, 26(4): 617-625
:DOI:`10.1016/0031-3203(93)90115-D`
.. [2] Li C.H. and Tam P.K.S. (1998) "An Iterative Algorithm for Minimum
Cross Entropy Thresholding" Pattern Recognition Letters, 18(8): 771-776
:DOI:`10.1016/S0167-8655(98)00057-9`
"""
import numpy as np
import matplotlib.pyplot as plt
from skimage import data
from skimage import filters
from skimage.filters.thresholding import _cross_entropy
cell = data.cell()
camera = data.camera()
###############################################################################
# First, we let's plot the cross entropy for the :func:`skimage.data.camera`
# image at all possible thresholds.
thresholds = np.arange(np.min(camera) + 1.5, np.max(camera) - 1.5)
entropies = [_cross_entropy(camera, t) for t in thresholds]
optimal_camera_threshold = thresholds[np.argmin(entropies)]
fig, ax = plt.subplots(1, 3, figsize=(8, 3))
ax[0].imshow(camera, cmap='gray')
ax[0].set_title('image')
