import numpy as np from skimage.segmentation import quickshift from skimage._shared import testing from skimage._shared.testing import (assert_greater, test_parallel, assert_equal, assert_array_equal) @test_parallel() @testing.parametrize('dtype', [np.float32, np.float64]) def test_grey(dtype): rnd = 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 * rnd.normal(size=img.shape) img = img.astype(dtype, copy=False) seg = quickshift(img, kernel_size=2, max_dist=3, random_seed=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): rnd = 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 * rnd.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, random_seed=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, random_seed=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()