update

.CondaPkg/env/Lib/site-packages/skimage/segmentation/tests/test_quickshift.py

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+import numpy as np
+import pytest
+from skimage.segmentation import quickshift
+
+from skimage._shared import testing
+from skimage._shared.testing import (
+    assert_greater,
+    run_in_parallel,
+    assert_equal,
+    assert_array_equal,
+)
+
+
+@run_in_parallel()
+@testing.parametrize('dtype', [np.float32, np.float64])
+def test_grey(dtype):
+    rng = np.random.default_rng(0)
+    img = np.zeros((20, 21))
+    img[:10, 10:] = 0.2
+    img[10:, :10] = 0.4
+    img[10:, 10:] = 0.6
+    img += 0.05 * rng.normal(size=img.shape)
+    img = img.astype(dtype, copy=False)
+    seg = quickshift(img, kernel_size=2, max_dist=3, rng=0, convert2lab=False, sigma=0)
+    quickshift(img, kernel_size=2, max_dist=3, rng=0, convert2lab=False, sigma=0)
+    # we expect 4 segments:
+    assert_equal(len(np.unique(seg)), 4)
+    # that mostly respect the 4 regions:
+    for i in range(4):
+        hist = np.histogram(img[seg == i], bins=[0, 0.1, 0.3, 0.5, 1])[0]
+        assert_greater(hist[i], 20)
+
+
+@testing.parametrize('dtype', [np.float32, np.float64])
+@testing.parametrize('channel_axis', [-3, -2, -1, 0, 1, 2])
+def test_color(dtype, channel_axis):
+    rng = np.random.default_rng(583428449)
+    img = np.zeros((20, 21, 3))
+    img[:10, :10, 0] = 1
+    img[10:, :10, 1] = 1
+    img[10:, 10:, 2] = 1
+    img += 0.01 * rng.normal(size=img.shape)
+    img[img > 1] = 1
+    img[img < 0] = 0
+    img = img.astype(dtype, copy=False)
+
+    img = np.moveaxis(img, source=-1, destination=channel_axis)
+    seg = quickshift(
+        img, rng=0, max_dist=30, kernel_size=10, sigma=0, channel_axis=channel_axis
+    )
+    # we expect 4 segments:
+    assert_equal(len(np.unique(seg)), 4)
+    assert_array_equal(seg[:10, :10], 1)
+    assert_array_equal(seg[10:, :10], 3)
+    assert_array_equal(seg[:10, 10:], 0)
+    assert_array_equal(seg[10:, 10:], 2)
+
+    seg2 = quickshift(
+        img,
+        kernel_size=1,
+        max_dist=2,
+        rng=0,
+        convert2lab=False,
+        sigma=0,
+        channel_axis=channel_axis,
+    )
+    # very oversegmented:
+    assert len(np.unique(seg2)) > 10
+    # still don't cross lines
+    assert (seg2[9, :] != seg2[10, :]).all()
+    assert (seg2[:, 9] != seg2[:, 10]).all()
+
+
+def test_convert2lab_not_rgb():
+    img = np.zeros((20, 21, 2))
+    with pytest.raises(
+        ValueError, match="Only RGB images can be converted to Lab space"
+    ):
+        quickshift(img, convert2lab=True)