mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-30 02:39:34 +08:00
Andreas Mueller
77 lines
2.0 KiB
Python
77 lines
2.0 KiB
Python
import numpy as np
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from numpy.testing import assert_array_almost_equal as assert_close
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import skimage
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from skimage import data
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from skimage import exposure
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# Test histogram equalization
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# ===========================
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# squeeze image intensities to lower image contrast
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test_img = exposure.rescale_intensity(data.camera() / 5. + 100)
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def test_equalize_ubyte():
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img = skimage.img_as_ubyte(test_img)
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img_eq = exposure.equalize(img)
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cdf, bin_edges = exposure.cumulative_distribution(img_eq)
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check_cdf_slope(cdf)
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def test_equalize_float():
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img = skimage.img_as_float(test_img)
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img_eq = exposure.equalize(img)
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cdf, bin_edges = exposure.cumulative_distribution(img_eq)
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check_cdf_slope(cdf)
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def check_cdf_slope(cdf):
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"""Slope of cdf which should equal 1 for an equalized histogram."""
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norm_intensity = np.linspace(0, 1, len(cdf))
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slope, intercept = np.polyfit(norm_intensity, cdf, 1)
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assert 0.9 < slope < 1.1
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# Test rescale intensity
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# ======================
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def test_rescale_stretch():
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image = np.array([51, 102, 153], dtype=np.uint8)
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out = exposure.rescale_intensity(image)
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assert out.dtype == np.uint8
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assert_close(out, [0, 127, 255])
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def test_rescale_shrink():
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image = np.array([51., 102., 153.])
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out = exposure.rescale_intensity(image)
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assert_close(out, [0, 0.5, 1])
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def test_rescale_in_range():
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image = np.array([51., 102., 153.])
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out = exposure.rescale_intensity(image, in_range=(0, 255))
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assert_close(out, [0.2, 0.4, 0.6])
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def test_rescale_in_range_clip():
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image = np.array([51., 102., 153.])
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out = exposure.rescale_intensity(image, in_range=(0, 102))
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assert_close(out, [0.5, 1, 1])
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def test_rescale_out_range():
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image = np.array([-10, 0, 10], dtype=np.int8)
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out = exposure.rescale_intensity(image, out_range=(0, 127))
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assert out.dtype == np.int8
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assert_close(out, [0, 63, 127])
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if __name__ == '__main__':
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from numpy import testing
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testing.run_module_suite()
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