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