mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-30 15:55:16 +08:00
Evgeni Burovski
187 lines
6.4 KiB
Python
187 lines
6.4 KiB
Python
from __future__ import division, print_function, absolute_import
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import os
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import warnings
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import numpy as np
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from numpy.testing import (assert_equal, run_module_suite, assert_raises,
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assert_)
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import scipy.ndimage as ndi
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import skimage
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from skimage import io, draw, data_dir
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from skimage.data import binary_blobs
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from skimage.util import img_as_ubyte
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from skimage.morphology import skeletonize_3d
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# basic behavior tests (mostly copied over from 2D skeletonize)
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def test_skeletonize_wrong_dim():
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im = np.zeros(5, dtype=np.uint8)
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assert_raises(ValueError, skeletonize_3d, im)
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im = np.zeros((5, 5, 5, 5), dtype=np.uint8)
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assert_raises(ValueError, skeletonize_3d, im)
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def test_skeletonize_1D():
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# a corner case of an image of a shape(1, N)
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im = np.ones((5, 1), dtype=np.uint8)
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res = skeletonize_3d(im)
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assert_equal(res, im)
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def test_skeletonize_no_foreground():
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im = np.zeros((5, 5), dtype=np.uint8)
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result = skeletonize_3d(im)
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assert_equal(result, im)
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def test_skeletonize_all_foreground():
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im = np.ones((3, 4), dtype=np.uint8)
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assert_equal(skeletonize_3d(im),
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np.array([[0, 0, 0, 0],
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[1, 1, 1, 1],
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[0, 0, 0, 0]], dtype=np.uint8))
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def test_skeletonize_single_point():
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im = np.zeros((5, 5), dtype=np.uint8)
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im[3, 3] = 1
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result = skeletonize_3d(im)
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assert_equal(result, im)
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def test_skeletonize_already_thinned():
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im = np.zeros((5, 5), dtype=np.uint8)
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im[3, 1:-1] = 1
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im[2, -1] = 1
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im[4, 0] = 1
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result = skeletonize_3d(im)
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assert_equal(result, im)
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def test_dtype_conv():
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# check that the operation does the right thing with floats etc
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# also check non-contiguous input
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img = np.random.random((16, 16))[::2, ::2]
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img[img < 0.5] = 0
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orig = img.copy()
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with warnings.catch_warnings():
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# UserWarning for possible precision loss, expected
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warnings.simplefilter('ignore', UserWarning)
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res = skeletonize_3d(img)
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assert_equal(res.dtype, np.uint8)
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assert_equal(img, orig) # operation does not clobber the original
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assert_equal(res.max(),
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img_as_ubyte(img).max()) # the intensity range is preserved
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def test_input():
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# check that the input is not clobbered
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# for 2D and 3D images of varying dtypes
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imgs = [np.ones((8, 8), dtype=float), np.ones((4, 8, 8), dtype=float),
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np.ones((8, 8), dtype=np.uint8), np.ones((4, 8, 8), dtype=np.uint8),
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np.ones((8, 8), dtype=bool), np.ones((4, 8, 8), dtype=bool)]
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for img in imgs:
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yield check_input, img
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def check_input(img):
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orig = img.copy()
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with warnings.catch_warnings():
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# UserWarning for possible precision loss, expected
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warnings.simplefilter('ignore', UserWarning)
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res = skeletonize_3d(img)
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assert_equal(img, orig)
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def test_skeletonize_num_neighbours():
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# an empty image
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image = np.zeros((300, 300))
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# foreground object 1
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image[10:-10, 10:100] = 1
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image[-100:-10, 10:-10] = 1
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image[10:-10, -100:-10] = 1
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# foreground object 2
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rs, cs = draw.line(250, 150, 10, 280)
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for i in range(10):
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image[rs + i, cs] = 1
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rs, cs = draw.line(10, 150, 250, 280)
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for i in range(20):
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image[rs + i, cs] = 1
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# foreground object 3
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ir, ic = np.indices(image.shape)
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circle1 = (ic - 135)**2 + (ir - 150)**2 < 30**2
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circle2 = (ic - 135)**2 + (ir - 150)**2 < 20**2
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image[circle1] = 1
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image[circle2] = 0
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result = skeletonize_3d(image)
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# there should never be a 2x2 block of foreground pixels in a skeleton
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mask = np.array([[1, 1],
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[1, 1]], np.uint8)
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blocks = ndi.correlate(result, mask, mode='constant')
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assert_(not np.any(blocks == 4))
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def test_two_hole_image():
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# test a simple 2D image against FIJI
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img_o = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0],
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[0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
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[0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
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[0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
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[0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
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[0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0],
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[0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
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dtype=np.uint8)
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img_f = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
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[0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],
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dtype=np.uint8)
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res = skeletonize_3d(img_o)
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assert_equal(res, img_f)
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def test_3d_vs_fiji():
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# generate an image with blobs and compate its skeleton to
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# the skeleton generated by FIJI
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img = binary_blobs(32, 0.05, n_dim=3, seed=1234)
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img = img[:-2, ...]
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img = img.astype(np.uint8)*255
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img_s = skeletonize_3d(img)
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img_f = io.imread(os.path.join(data_dir, "_blobs_3d_fiji_skeleton.tif"))
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assert_equal(img_s, img_f)
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if __name__ == '__main__':
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run_module_suite()
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